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Major refactor: Consolidate DSS into unified package structure

Browse Source 
- Create new dss/ Python package at project root
- Move MCP core from tools/dss_mcp/ to dss/mcp/
- Move storage layer from tools/storage/ to dss/storage/
- Move domain logic from dss-mvp1/dss/ to dss/
- Move services from tools/api/services/ to dss/services/
- Move API server to apps/api/
- Move CLI to apps/cli/
- Move Storybook assets to storybook/
- Create unified dss/__init__.py with comprehensive exports
- Merge configuration into dss/settings.py (Pydantic-based)
- Create pyproject.toml for proper package management
- Update startup scripts for new paths
- Remove old tools/ and dss-mvp1/ directories

Architecture changes:
- DSS is now MCP-first with 40+ tools for Claude Code
- Clean imports: from dss import Projects, Components, FigmaToolSuite
- No more sys.path.insert() hacking
- apps/ contains thin application wrappers (API, CLI)
- Single unified Python package for all DSS logic

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
Bruno Sarlo
2025-12-10 12:43:18 -03:00
parent bbd67f88c4
commit 41fba59bf7
197 changed files with 3185 additions and 15500 deletions
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152
dss/__init__.py Normal file
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"""
DSS - Design System Server
A Model Context Protocol (MCP) server that provides Claude Code with 40+ design system tools.
Supports local development and remote team deployment.
Usage:
from dss import settings, Projects, Components
from dss.mcp import MCPServer
from dss.storage import Projects, Components, Tokens
"""
__version__ = "1.0.0"
# Settings & Configuration
from dss.settings import settings, DSSSettings, DSSManager, manager
# Storage Layer
from dss.storage.json_store import (
Projects,
Components,
Tokens,
Styles,
SyncHistory,
ActivityLog,
Teams,
Cache,
FigmaFiles,
CodeMetrics,
TestResults,
TokenDrift,
Integrations,
IntegrationHealth,
get_stats,
)
# Analyze
from dss.analyze.base import (
ProjectAnalysis,
QuickWin,
ComponentInfo,
StylePattern,
Framework,
StylingApproach,
)
from dss.analyze.scanner import ProjectScanner
# Ingest
from dss.ingest.base import (
DesignToken,
TokenCollection,
TokenSource,
TokenType,
TokenCategory,
)
# Export/Import
from dss.export_import.service import DSSArchiveExporter, DSSArchiveImporter
from dss.export_import.smart_merger import SmartMerger
# Storybook
from dss.storybook.generator import StoryGenerator
from dss.storybook.scanner import StorybookScanner
# Translations
from dss.translations.dictionary import TranslationDictionary
from dss.translations.resolver import TokenResolver
# Services
from dss.services.project_manager import ProjectManager
from dss.services.config_service import ConfigService, DSSConfig
from dss.services.sandboxed_fs import SandboxedFS
# Figma
from dss.figma.figma_tools import FigmaToolSuite
# Project
from dss.project.manager import DSSProject
# Models
from dss.models.theme import Theme
from dss.models.component import Component
from dss.models.project import Project
# Validators
from dss.validators.schema import ProjectValidator, ValidationResult
__all__ = [
# Version
"__version__",
# Settings
"settings",
"DSSSettings",
"DSSManager",
"manager",
# Storage
"Projects",
"Components",
"Tokens",
"Styles",
"SyncHistory",
"ActivityLog",
"Teams",
"Cache",
"FigmaFiles",
"CodeMetrics",
"TestResults",
"TokenDrift",
"Integrations",
"IntegrationHealth",
"get_stats",
# Analyze
"ProjectAnalysis",
"QuickWin",
"ComponentInfo",
"StylePattern",
"Framework",
"StylingApproach",
"ProjectScanner",
# Ingest
"DesignToken",
"TokenCollection",
"TokenSource",
"TokenType",
"TokenCategory",
# Export/Import
"DSSArchiveExporter",
"DSSArchiveImporter",
"SmartMerger",
# Storybook
"StoryGenerator",
"StorybookScanner",
# Translations
"TranslationDictionary",
"TokenResolver",
# Services
"ProjectManager",
"ConfigService",
"DSSConfig",
"SandboxedFS",
# Figma
"FigmaToolSuite",
# Project
"DSSProject",
# Models
"Theme",
"Component",
"Project",
# Validators
"ProjectValidator",
"ValidationResult",
]

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dss/analyze/__init__.py Normal file
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"""
DSS Code Analysis Module
Provides tools for analyzing React projects, detecting style patterns,
building dependency graphs, and identifying quick-win improvements.
"""
from .base import (
ProjectAnalysis,
StylePattern,
QuickWin,
QuickWinType,
QuickWinPriority,
Location,
ComponentInfo,
StyleFile,
)
from .scanner import ProjectScanner
from .react import ReactAnalyzer
from .styles import StyleAnalyzer
from .graph import DependencyGraph
from .quick_wins import QuickWinFinder
__all__ = [
# Data classes
"ProjectAnalysis",
"StylePattern",
"QuickWin",
"QuickWinType",
"QuickWinPriority",
"Location",
"ComponentInfo",
"StyleFile",
# Analyzers
"ProjectScanner",
"ReactAnalyzer",
"StyleAnalyzer",
"DependencyGraph",
"QuickWinFinder",
]

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"""
Base classes and data structures for code analysis.
"""
from dataclasses import dataclass, field
from datetime import datetime
from enum import Enum
from typing import List, Dict, Any, Optional, Set
from pathlib import Path
class QuickWinType(str, Enum):
"""Types of quick-win improvements."""
INLINE_STYLE = "inline_style" # Inline styles that can be extracted
DUPLICATE_VALUE = "duplicate_value" # Duplicate color/spacing values
UNUSED_STYLE = "unused_style" # Unused CSS/SCSS
HARDCODED_VALUE = "hardcoded_value" # Hardcoded values that should be tokens
NAMING_INCONSISTENCY = "naming" # Inconsistent naming patterns
DEPRECATED_PATTERN = "deprecated" # Deprecated styling patterns
ACCESSIBILITY = "accessibility" # A11y improvements
PERFORMANCE = "performance" # Performance improvements
class QuickWinPriority(str, Enum):
"""Priority levels for quick-wins."""
CRITICAL = "critical" # Must fix - breaking issues
HIGH = "high" # Should fix - significant improvement
MEDIUM = "medium" # Nice to fix - moderate improvement
LOW = "low" # Optional - minor improvement
class StylingApproach(str, Enum):
"""Detected styling approaches in a project."""
CSS_MODULES = "css-modules"
STYLED_COMPONENTS = "styled-components"
EMOTION = "emotion"
TAILWIND = "tailwind"
INLINE_STYLES = "inline-styles"
CSS_IN_JS = "css-in-js"
SASS_SCSS = "sass-scss"
LESS = "less"
VANILLA_CSS = "vanilla-css"
CSS_VARIABLES = "css-variables"
class Framework(str, Enum):
"""Detected UI frameworks."""
REACT = "react"
NEXT = "next"
VUE = "vue"
NUXT = "nuxt"
ANGULAR = "angular"
SVELTE = "svelte"
SOLID = "solid"
UNKNOWN = "unknown"
@dataclass
class Location:
"""Represents a location in source code."""
file_path: str
line: int
column: int = 0
end_line: Optional[int] = None
end_column: Optional[int] = None
def __str__(self) -> str:
return f"{self.file_path}:{self.line}"
def to_dict(self) -> Dict[str, Any]:
return {
"file": self.file_path,
"line": self.line,
"column": self.column,
"end_line": self.end_line,
"end_column": self.end_column,
}
@dataclass
class StyleFile:
"""Represents a style file in the project."""
path: str
type: str # css, scss, less, styled, etc.
size_bytes: int = 0
line_count: int = 0
variable_count: int = 0
selector_count: int = 0
imports: List[str] = field(default_factory=list)
imported_by: List[str] = field(default_factory=list)
def to_dict(self) -> Dict[str, Any]:
return {
"path": self.path,
"type": self.type,
"size_bytes": self.size_bytes,
"line_count": self.line_count,
"variable_count": self.variable_count,
"selector_count": self.selector_count,
"imports": self.imports,
"imported_by": self.imported_by,
}
@dataclass
class ComponentInfo:
"""Information about a React component."""
name: str
path: str
type: str = "functional" # functional, class, forwardRef, memo
props: List[str] = field(default_factory=list)
has_styles: bool = False
style_files: List[str] = field(default_factory=list)
inline_style_count: int = 0
imports: List[str] = field(default_factory=list)
exports: List[str] = field(default_factory=list)
children: List[str] = field(default_factory=list) # Child components used
line_count: int = 0
def to_dict(self) -> Dict[str, Any]:
return {
"name": self.name,
"path": self.path,
"type": self.type,
"props": self.props,
"has_styles": self.has_styles,
"style_files": self.style_files,
"inline_style_count": self.inline_style_count,
"imports": self.imports,
"exports": self.exports,
"children": self.children,
"line_count": self.line_count,
}
@dataclass
class StylePattern:
"""A detected style pattern in code."""
type: StylingApproach
locations: List[Location] = field(default_factory=list)
count: int = 0
examples: List[str] = field(default_factory=list)
def to_dict(self) -> Dict[str, Any]:
return {
"type": self.type.value,
"count": self.count,
"locations": [loc.to_dict() for loc in self.locations[:10]],
"examples": self.examples[:5],
}
@dataclass
class TokenCandidate:
"""A value that could be extracted as a design token."""
value: str # The actual value (e.g., "#3B82F6")
suggested_name: str # Suggested token name
category: str # colors, spacing, typography, etc.
occurrences: int = 1 # How many times it appears
locations: List[Location] = field(default_factory=list)
confidence: float = 0.0 # 0-1 confidence score
def to_dict(self) -> Dict[str, Any]:
return {
"value": self.value,
"suggested_name": self.suggested_name,
"category": self.category,
"occurrences": self.occurrences,
"locations": [loc.to_dict() for loc in self.locations[:5]],
"confidence": self.confidence,
}
@dataclass
class QuickWin:
"""A quick improvement opportunity."""
type: QuickWinType
priority: QuickWinPriority
title: str
description: str
location: Optional[Location] = None
affected_files: List[str] = field(default_factory=list)
estimated_impact: str = "" # e.g., "Remove 50 lines of duplicate code"
fix_suggestion: str = "" # Suggested fix
auto_fixable: bool = False # Can be auto-fixed
def to_dict(self) -> Dict[str, Any]:
return {
"type": self.type.value,
"priority": self.priority.value,
"title": self.title,
"description": self.description,
"location": self.location.to_dict() if self.location else None,
"affected_files": self.affected_files,
"estimated_impact": self.estimated_impact,
"fix_suggestion": self.fix_suggestion,
"auto_fixable": self.auto_fixable,
}
@dataclass
class ProjectAnalysis:
"""Complete analysis result for a project."""
# Basic info
project_path: str
analyzed_at: datetime = field(default_factory=datetime.now)
# Framework detection
framework: Framework = Framework.UNKNOWN
framework_version: str = ""
# Styling detection
styling_approaches: List[StylePattern] = field(default_factory=list)
primary_styling: Optional[StylingApproach] = None
# Components
components: List[ComponentInfo] = field(default_factory=list)
component_count: int = 0
# Style files
style_files: List[StyleFile] = field(default_factory=list)
style_file_count: int = 0
# Issues and opportunities
inline_style_locations: List[Location] = field(default_factory=list)
token_candidates: List[TokenCandidate] = field(default_factory=list)
quick_wins: List[QuickWin] = field(default_factory=list)
# Dependency graph
dependency_graph: Dict[str, List[str]] = field(default_factory=dict)
# Statistics
stats: Dict[str, Any] = field(default_factory=dict)
def __post_init__(self):
if not self.stats:
self.stats = {
"total_files_scanned": 0,
"total_lines": 0,
"component_count": 0,
"style_file_count": 0,
"inline_style_count": 0,
"token_candidates": 0,
"quick_wins_count": 0,
}
def to_dict(self) -> Dict[str, Any]:
return {
"project_path": self.project_path,
"analyzed_at": self.analyzed_at.isoformat(),
"framework": self.framework.value,
"framework_version": self.framework_version,
"styling_approaches": [sp.to_dict() for sp in self.styling_approaches],
"primary_styling": self.primary_styling.value if self.primary_styling else None,
"component_count": self.component_count,
"style_file_count": self.style_file_count,
"inline_style_count": len(self.inline_style_locations),
"token_candidates_count": len(self.token_candidates),
"quick_wins_count": len(self.quick_wins),
"stats": self.stats,
}
def summary(self) -> str:
"""Generate human-readable summary."""
lines = [
f"Project Analysis: {self.project_path}",
"=" * 50,
f"Framework: {self.framework.value} {self.framework_version}",
f"Components: {self.component_count}",
f"Style files: {self.style_file_count}",
"",
"Styling Approaches:",
]
for sp in self.styling_approaches:
lines.append(f" • {sp.type.value}: {sp.count} occurrences")
lines.extend([
"",
f"Inline styles found: {len(self.inline_style_locations)}",
f"Token candidates: {len(self.token_candidates)}",
f"Quick wins: {len(self.quick_wins)}",
"",
"Quick Wins by Priority:",
])
by_priority = {}
for qw in self.quick_wins:
if qw.priority not in by_priority:
by_priority[qw.priority] = []
by_priority[qw.priority].append(qw)
for priority in [QuickWinPriority.CRITICAL, QuickWinPriority.HIGH,
QuickWinPriority.MEDIUM, QuickWinPriority.LOW]:
if priority in by_priority:
lines.append(f" [{priority.value.upper()}] {len(by_priority[priority])} items")
return "\n".join(lines)

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"""
Dependency Graph Builder
Builds component and style dependency graphs for visualization
and analysis of project structure.
"""
import re
import json
from pathlib import Path
from typing import List, Dict, Any, Optional, Set, Tuple
from dataclasses import dataclass, field
from collections import defaultdict
@dataclass
class GraphNode:
"""A node in the dependency graph."""
id: str
name: str
type: str # 'component', 'style', 'util', 'hook'
path: str
size: int = 0 # file size or importance metric
children: List[str] = field(default_factory=list)
parents: List[str] = field(default_factory=list)
metadata: Dict[str, Any] = field(default_factory=dict)
def to_dict(self) -> Dict[str, Any]:
return {
'id': self.id,
'name': self.name,
'type': self.type,
'path': self.path,
'size': self.size,
'children': self.children,
'parents': self.parents,
'metadata': self.metadata,
}
@dataclass
class GraphEdge:
"""An edge in the dependency graph."""
source: str
target: str
type: str # 'import', 'uses', 'styles'
weight: int = 1
def to_dict(self) -> Dict[str, Any]:
return {
'source': self.source,
'target': self.target,
'type': self.type,
'weight': self.weight,
}
class DependencyGraph:
"""
Builds and analyzes dependency graphs for a project.
Tracks:
- Component imports/exports
- Style file dependencies
- Component usage relationships
"""
def __init__(self, root_path: str):
self.root = Path(root_path).resolve()
self.nodes: Dict[str, GraphNode] = {}
self.edges: List[GraphEdge] = []
async def build(self, depth: int = 3) -> Dict[str, Any]:
"""
Build the full dependency graph.
Args:
depth: Maximum depth for traversing dependencies
Returns:
Graph representation with nodes and edges
"""
# Clear existing graph
self.nodes.clear()
self.edges.clear()
# Find all relevant files
await self._scan_files()
# Build edges from imports
await self._build_import_edges()
# Build edges from component usage
await self._build_usage_edges()
return self.to_dict()
async def _scan_files(self) -> None:
"""Scan project files and create nodes."""
skip_dirs = {'node_modules', '.git', 'dist', 'build', '.next'}
# Component files
for ext in ['*.jsx', '*.tsx']:
for file_path in self.root.rglob(ext):
if any(skip in file_path.parts for skip in skip_dirs):
continue
rel_path = str(file_path.relative_to(self.root))
node_id = self._path_to_id(rel_path)
self.nodes[node_id] = GraphNode(
id=node_id,
name=file_path.stem,
type='component',
path=rel_path,
size=file_path.stat().st_size,
)
# Style files
for ext in ['*.css', '*.scss', '*.sass', '*.less']:
for file_path in self.root.rglob(ext):
if any(skip in file_path.parts for skip in skip_dirs):
continue
rel_path = str(file_path.relative_to(self.root))
node_id = self._path_to_id(rel_path)
self.nodes[node_id] = GraphNode(
id=node_id,
name=file_path.stem,
type='style',
path=rel_path,
size=file_path.stat().st_size,
)
# Utility/Hook files
for ext in ['*.js', '*.ts']:
for file_path in self.root.rglob(ext):
if any(skip in file_path.parts for skip in skip_dirs):
continue
name = file_path.stem.lower()
rel_path = str(file_path.relative_to(self.root))
node_id = self._path_to_id(rel_path)
# Classify file type
if 'hook' in name or name.startswith('use'):
node_type = 'hook'
elif any(x in name for x in ['util', 'helper', 'lib']):
node_type = 'util'
else:
continue # Skip other JS/TS files
self.nodes[node_id] = GraphNode(
id=node_id,
name=file_path.stem,
type=node_type,
path=rel_path,
size=file_path.stat().st_size,
)
async def _build_import_edges(self) -> None:
"""Build edges from import statements."""
import_pattern = re.compile(
r'import\s+(?:\{[^}]+\}|\*\s+as\s+\w+|\w+)?\s*(?:,\s*\{[^}]+\})?\s*from\s+["\']([^"\']+)["\']',
re.MULTILINE
)
for node_id, node in self.nodes.items():
if node.type not in ['component', 'hook', 'util']:
continue
file_path = self.root / node.path
if not file_path.exists():
continue
try:
content = file_path.read_text(encoding='utf-8', errors='ignore')
for match in import_pattern.finditer(content):
import_path = match.group(1)
# Resolve relative imports
target_id = self._resolve_import(node.path, import_path)
if target_id and target_id in self.nodes:
# Add edge
self.edges.append(GraphEdge(
source=node_id,
target=target_id,
type='import',
))
# Update parent/child relationships
node.children.append(target_id)
self.nodes[target_id].parents.append(node_id)
except Exception:
continue
async def _build_usage_edges(self) -> None:
"""Build edges from component usage in JSX."""
# Pattern to find JSX component usage
jsx_pattern = re.compile(r'<([A-Z][A-Za-z0-9]*)')
# Build name -> id mapping for components
name_to_id = {}
for node_id, node in self.nodes.items():
if node.type == 'component':
name_to_id[node.name] = node_id
for node_id, node in self.nodes.items():
if node.type != 'component':
continue
file_path = self.root / node.path
if not file_path.exists():
continue
try:
content = file_path.read_text(encoding='utf-8', errors='ignore')
used_components = set()
for match in jsx_pattern.finditer(content):
comp_name = match.group(1)
if comp_name in name_to_id and name_to_id[comp_name] != node_id:
used_components.add(name_to_id[comp_name])
for target_id in used_components:
self.edges.append(GraphEdge(
source=node_id,
target=target_id,
type='uses',
))
except Exception:
continue
def _path_to_id(self, path: str) -> str:
"""Convert file path to node ID."""
# Remove extension and normalize
path = re.sub(r'\.(jsx?|tsx?|css|scss|sass|less)$', '', path)
return path.replace('/', '_').replace('\\', '_').replace('.', '_')
def _resolve_import(self, source_path: str, import_path: str) -> Optional[str]:
"""Resolve import path to node ID."""
if not import_path.startswith('.'):
return None # Skip node_modules imports
source_dir = Path(source_path).parent
# Handle various import patterns
if import_path.startswith('./'):
resolved = source_dir / import_path[2:]
elif import_path.startswith('../'):
resolved = source_dir / import_path
else:
resolved = source_dir / import_path
# Try to resolve with extensions
extensions = ['.tsx', '.ts', '.jsx', '.js', '.css', '.scss', '/index.tsx', '/index.ts', '/index.jsx', '/index.js']
resolved_str = str(resolved)
for ext in extensions:
test_id = self._path_to_id(resolved_str + ext)
if test_id in self.nodes:
return test_id
# Try without additional extension (if path already has one)
test_id = self._path_to_id(resolved_str)
if test_id in self.nodes:
return test_id
return None
def to_dict(self) -> Dict[str, Any]:
"""Convert graph to dictionary for serialization."""
return {
'nodes': [node.to_dict() for node in self.nodes.values()],
'edges': [edge.to_dict() for edge in self.edges],
'stats': {
'total_nodes': len(self.nodes),
'total_edges': len(self.edges),
'components': len([n for n in self.nodes.values() if n.type == 'component']),
'styles': len([n for n in self.nodes.values() if n.type == 'style']),
'hooks': len([n for n in self.nodes.values() if n.type == 'hook']),
'utils': len([n for n in self.nodes.values() if n.type == 'util']),
}
}
def to_json(self, pretty: bool = True) -> str:
"""Convert graph to JSON string."""
return json.dumps(self.to_dict(), indent=2 if pretty else None)
def get_component_tree(self) -> Dict[str, List[str]]:
"""Get simplified component dependency tree."""
tree = {}
for node_id, node in self.nodes.items():
if node.type == 'component':
tree[node.name] = [
self.nodes[child_id].name
for child_id in node.children
if child_id in self.nodes and self.nodes[child_id].type == 'component'
]
return tree
def find_orphans(self) -> List[str]:
"""Find components with no parents (not imported anywhere)."""
orphans = []
for node_id, node in self.nodes.items():
if node.type == 'component' and not node.parents:
# Exclude entry points (index, App, etc.)
if node.name.lower() not in ['app', 'index', 'main', 'root']:
orphans.append(node.path)
return orphans
def find_hubs(self, min_connections: int = 5) -> List[Dict[str, Any]]:
"""Find highly connected nodes (potential refactoring targets)."""
hubs = []
for node_id, node in self.nodes.items():
connections = len(node.children) + len(node.parents)
if connections >= min_connections:
hubs.append({
'name': node.name,
'path': node.path,
'type': node.type,
'imports': len(node.children),
'imported_by': len(node.parents),
'total_connections': connections,
})
hubs.sort(key=lambda x: x['total_connections'], reverse=True)
return hubs
def find_circular_dependencies(self) -> List[List[str]]:
"""Find circular dependency chains."""
cycles = []
visited = set()
rec_stack = set()
def dfs(node_id: str, path: List[str]) -> None:
visited.add(node_id)
rec_stack.add(node_id)
path.append(node_id)
for child_id in self.nodes.get(node_id, GraphNode('', '', '', '')).children:
if child_id not in visited:
dfs(child_id, path.copy())
elif child_id in rec_stack:
# Found cycle
cycle_start = path.index(child_id)
cycle = path[cycle_start:] + [child_id]
cycles.append([self.nodes[n].name for n in cycle])
rec_stack.remove(node_id)
for node_id in self.nodes:
if node_id not in visited:
dfs(node_id, [])
return cycles
def get_subgraph(self, node_id: str, depth: int = 2) -> Dict[str, Any]:
"""Get subgraph centered on a specific node."""
if node_id not in self.nodes:
return {'nodes': [], 'edges': []}
# BFS to find nodes within depth
included_nodes = {node_id}
frontier = {node_id}
for _ in range(depth):
new_frontier = set()
for nid in frontier:
node = self.nodes.get(nid)
if node:
new_frontier.update(node.children)
new_frontier.update(node.parents)
included_nodes.update(new_frontier)
frontier = new_frontier
# Filter nodes and edges
subgraph_nodes = [
self.nodes[nid].to_dict()
for nid in included_nodes
if nid in self.nodes
]
subgraph_edges = [
edge.to_dict()
for edge in self.edges
if edge.source in included_nodes and edge.target in included_nodes
]
return {
'nodes': subgraph_nodes,
'edges': subgraph_edges,
'center': node_id,
'depth': depth,
}
def get_style_dependencies(self) -> Dict[str, List[str]]:
"""Get mapping of components to their style dependencies."""
style_deps = {}
for node_id, node in self.nodes.items():
if node.type != 'component':
continue
style_children = [
self.nodes[child_id].path
for child_id in node.children
if child_id in self.nodes and self.nodes[child_id].type == 'style'
]
if style_children:
style_deps[node.path] = style_children
return style_deps

27
dss/analyze/parser.js Executable file
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#!/usr/bin/env node
const fs = require('fs');
const parser = require('@babel/parser');
const filePath = process.argv[2];
if (!filePath) {
console.error("Please provide a file path.");
process.exit(1);
}
try {
const code = fs.readFileSync(filePath, 'utf8');
const ast = parser.parse(code, {
sourceType: "module",
plugins: [
"jsx",
"typescript"
]
});
console.log(JSON.stringify(ast, null, 2));
} catch (error) {
console.error(`Failed to parse ${filePath}:`, error.message);
process.exit(1);
}

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dss/analyze/project_analyzer.py Normal file
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import os
import json
import networkx as nx
import subprocess
import cssutils
import logging
from pathlib import Path
# Configure logging
logging.basicConfig(level=logging.INFO)
log = logging.getLogger(__name__)
# Configure cssutils to ignore noisy error messages
cssutils.log.setLevel(logging.CRITICAL)
def analyze_react_project(project_path: str) -> dict:
"""
Analyzes a React project, building a graph of its components and styles.
Args:
project_path: The root path of the React project.
Returns:
A dictionary containing the component graph and analysis report.
"""
log.info(f"Starting analysis of project at: {project_path}")
graph = nx.DiGraph()
# Supported extensions for react/js/ts files
supported_exts = ('.js', '.jsx', '.ts', '.tsx')
# Path to the parser script
parser_script_path = Path(__file__).parent / 'parser.js'
if not parser_script_path.exists():
raise FileNotFoundError(f"Parser script not found at {parser_script_path}")
for root, _, files in os.walk(project_path):
# Ignore node_modules and build directories
if 'node_modules' in root or 'build' in root or 'dist' in root:
continue
for file in files:
file_path = os.path.join(root, file)
relative_path = os.path.relpath(file_path, project_path)
# Add a node for every file
graph.add_node(relative_path, type='file')
if file.endswith(supported_exts):
graph.nodes[relative_path]['language'] = 'typescript'
try:
# Call the external node.js parser
result = subprocess.run(
['node', str(parser_script_path), file_path],
capture_output=True,
text=True,
check=True
)
# The AST is now in result.stdout as a JSON string.
# ast = json.loads(result.stdout)
except subprocess.CalledProcessError as e:
log.error(f"Failed to parse {file_path} with babel. Error: {e.stderr}")
except Exception as e:
log.error(f"Could not process file {file_path}: {e}")
elif file.endswith('.css'):
graph.nodes[relative_path]['language'] = 'css'
try:
# Placeholder for CSS parsing
# sheet = cssutils.parseFile(file_path)
pass
except Exception as e:
log.error(f"Could not parse css file {file_path}: {e}")
log.info(f"Analysis complete. Found {graph.number_of_nodes()} files.")
# Convert graph to a serializable format
serializable_graph = nx.node_link_data(graph)
return serializable_graph
def save_analysis_to_project(project_path: str, analysis_data: dict):
"""
Saves the analysis data to a file in the project's .dss directory.
"""
# In the context of dss-mvp1, the .dss directory for metadata might be at the root.
dss_dir = os.path.join(project_path, '.dss')
os.makedirs(dss_dir, exist_ok=True)
output_path = os.path.join(dss_dir, 'analysis_graph.json')
with open(output_path, 'w', encoding='utf-8') as f:
json.dump(analysis_data, f, indent=2)
log.info(f"Analysis data saved to {output_path}")
def run_project_analysis(project_path: str):
"""
High-level function to run analysis and save the result.
"""
analysis_result = analyze_react_project(project_path)
save_analysis_to_project(project_path, analysis_result)
return analysis_result
def _read_ds_config(project_path: str) -> dict:
"""
Reads the ds.config.json file from the project root.
"""
config_path = os.path.join(project_path, 'ds.config.json')
if not os.path.exists(config_path):
return {}
try:
with open(config_path, 'r', encoding='utf-8') as f:
return json.load(f)
except Exception as e:
log.error(f"Could not read or parse ds.config.json: {e}")
return {}
def export_project_context(project_path: str) -> dict:
"""
Exports a comprehensive project context for agents.
This context includes the analysis graph, project configuration,
and a summary of the project's structure.
"""
analysis_graph_path = os.path.join(project_path, '.dss', 'analysis_graph.json')
if not os.path.exists(analysis_graph_path):
# If the analysis hasn't been run, run it first.
log.info(f"Analysis graph not found for {project_path}. Running analysis now.")
run_project_analysis(project_path)
try:
with open(analysis_graph_path, 'r', encoding='utf-8') as f:
analysis_graph = json.load(f)
except Exception as e:
log.error(f"Could not read analysis graph for {project_path}: {e}")
analysis_graph = {}
project_config = _read_ds_config(project_path)
# Create the project context
project_context = {
"schema_version": "1.0",
"project_name": project_config.get("name", "Unknown"),
"analysis_summary": {
"file_nodes": len(analysis_graph.get("nodes", [])),
"dependencies": len(analysis_graph.get("links", [])),
"analyzed_at": log.info(f"Analysis data saved to {analysis_graph_path}")
},
"project_config": project_config,
"analysis_graph": analysis_graph,
}
return project_context
if __name__ == '__main__':
# This is for standalone testing of the analyzer.
# Provide a path to a project to test.
# e.g., python -m dss.analyze.project_analyzer ../../admin-ui
import sys
if len(sys.argv) > 1:
target_project_path = sys.argv[1]
if not os.path.isdir(target_project_path):
print(f"Error: Path '{target_project_path}' is not a valid directory.")
sys.exit(1)
run_project_analysis(target_project_path)
else:
print("Usage: python -m dss.analyze.project_analyzer <path_to_project>")

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dss/analyze/quick_wins.py Normal file
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"""
Quick-Win Finder
Identifies easy improvement opportunities in a codebase:
- Inline styles that can be extracted
- Duplicate values that should be tokens
- Unused styles
- Naming inconsistencies
- Accessibility issues
"""
import re
from pathlib import Path
from typing import List, Dict, Any, Optional
from dataclasses import dataclass
from .base import (
QuickWin,
QuickWinType,
QuickWinPriority,
Location,
ProjectAnalysis,
)
from .styles import StyleAnalyzer
from .react import ReactAnalyzer
class QuickWinFinder:
"""
Finds quick improvement opportunities in a project.
Categories:
- INLINE_STYLE: Inline styles that can be extracted to CSS/tokens
- DUPLICATE_VALUE: Repeated values that should be tokens
- UNUSED_STYLE: CSS that's defined but not used
- HARDCODED_VALUE: Magic numbers/colors that should be tokens
- NAMING_INCONSISTENCY: Inconsistent naming patterns
- DEPRECATED_PATTERN: Outdated styling approaches
- ACCESSIBILITY: A11y improvements
"""
def __init__(self, root_path: str):
self.root = Path(root_path).resolve()
self.style_analyzer = StyleAnalyzer(root_path)
self.react_analyzer = ReactAnalyzer(root_path)
async def find_all(self) -> List[QuickWin]:
"""
Find all quick-win opportunities.
Returns:
List of QuickWin objects sorted by priority
"""
quick_wins = []
# Find inline styles
inline_wins = await self._find_inline_style_wins()
quick_wins.extend(inline_wins)
# Find duplicate values
duplicate_wins = await self._find_duplicate_value_wins()
quick_wins.extend(duplicate_wins)
# Find unused styles
unused_wins = await self._find_unused_style_wins()
quick_wins.extend(unused_wins)
# Find hardcoded values
hardcoded_wins = await self._find_hardcoded_value_wins()
quick_wins.extend(hardcoded_wins)
# Find naming inconsistencies
naming_wins = await self._find_naming_inconsistency_wins()
quick_wins.extend(naming_wins)
# Find accessibility issues
a11y_wins = await self._find_accessibility_wins()
quick_wins.extend(a11y_wins)
# Sort by priority
priority_order = {
QuickWinPriority.CRITICAL: 0,
QuickWinPriority.HIGH: 1,
QuickWinPriority.MEDIUM: 2,
QuickWinPriority.LOW: 3,
}
quick_wins.sort(key=lambda x: priority_order[x.priority])
return quick_wins
async def _find_inline_style_wins(self) -> List[QuickWin]:
"""Find inline styles that should be extracted."""
wins = []
inline_styles = await self.react_analyzer.find_inline_styles()
if not inline_styles:
return wins
# Group by file
by_file = {}
for style in inline_styles:
file_path = style['file']
if file_path not in by_file:
by_file[file_path] = []
by_file[file_path].append(style)
# Create quick-wins for files with multiple inline styles
for file_path, styles in by_file.items():
if len(styles) >= 3: # Only flag if 3+ inline styles
wins.append(QuickWin(
type=QuickWinType.INLINE_STYLE,
priority=QuickWinPriority.HIGH,
title=f"Extract {len(styles)} inline styles",
description=f"File {file_path} has {len(styles)} inline style declarations that could be extracted to CSS classes or design tokens.",
location=Location(file_path, styles[0]['line']),
affected_files=[file_path],
estimated_impact=f"Reduce inline styles, improve maintainability",
fix_suggestion="Extract repeated style properties to CSS classes or design tokens. Use className instead of style prop.",
auto_fixable=True,
))
# Create summary if many files have inline styles
total_inline = len(inline_styles)
if total_inline >= 10:
wins.insert(0, QuickWin(
type=QuickWinType.INLINE_STYLE,
priority=QuickWinPriority.HIGH,
title=f"Project has {total_inline} inline styles",
description=f"Found {total_inline} inline style declarations across {len(by_file)} files. Consider migrating to CSS classes or design tokens.",
affected_files=list(by_file.keys())[:10],
estimated_impact=f"Improve code maintainability and bundle size",
fix_suggestion="Run 'dss migrate inline-styles' to preview migration options.",
auto_fixable=True,
))
return wins
async def _find_duplicate_value_wins(self) -> List[QuickWin]:
"""Find duplicate values that should be tokens."""
wins = []
analysis = await self.style_analyzer.analyze()
duplicates = analysis.get('duplicates', [])
# Find high-occurrence duplicates
for dup in duplicates[:10]: # Top 10 duplicates
if dup['count'] >= 5: # Only if used 5+ times
priority = QuickWinPriority.HIGH if dup['count'] >= 10 else QuickWinPriority.MEDIUM
wins.append(QuickWin(
type=QuickWinType.DUPLICATE_VALUE,
priority=priority,
title=f"Duplicate value '{dup['value']}' used {dup['count']} times",
description=f"The value '{dup['value']}' appears {dup['count']} times across {len(dup['files'])} files. This should be a design token.",
affected_files=dup['files'],
estimated_impact=f"Create single source of truth, easier theme updates",
fix_suggestion=f"Create token for this value and replace all occurrences.",
auto_fixable=True,
))
return wins
async def _find_unused_style_wins(self) -> List[QuickWin]:
"""Find unused CSS styles."""
wins = []
unused = await self.style_analyzer.find_unused_styles()
if len(unused) >= 5:
wins.append(QuickWin(
type=QuickWinType.UNUSED_STYLE,
priority=QuickWinPriority.MEDIUM,
title=f"Found {len(unused)} potentially unused CSS classes",
description=f"These CSS classes are defined but don't appear to be used in the codebase. Review and remove if confirmed unused.",
affected_files=list(set(u['file'] for u in unused))[:10],
estimated_impact=f"Reduce CSS bundle size by removing dead code",
fix_suggestion="Review each class and remove if unused. Some may be dynamically generated.",
auto_fixable=False, # Needs human review
))
return wins
async def _find_hardcoded_value_wins(self) -> List[QuickWin]:
"""Find hardcoded magic values."""
wins = []
analysis = await self.style_analyzer.analyze()
candidates = analysis.get('token_candidates', [])
# Find high-confidence candidates
high_confidence = [c for c in candidates if c.confidence >= 0.7]
if high_confidence:
wins.append(QuickWin(
type=QuickWinType.HARDCODED_VALUE,
priority=QuickWinPriority.MEDIUM,
title=f"Found {len(high_confidence)} values that should be tokens",
description="These hardcoded values appear multiple times and should be extracted as design tokens for consistency.",
estimated_impact="Improve theme consistency and make updates easier",
fix_suggestion="Use 'dss extract-tokens' to create tokens from these values.",
auto_fixable=True,
))
# Add specific wins for top candidates
for candidate in high_confidence[:5]:
wins.append(QuickWin(
type=QuickWinType.HARDCODED_VALUE,
priority=QuickWinPriority.LOW,
title=f"Extract '{candidate.value}' as token",
description=f"Value '{candidate.value}' appears {candidate.occurrences} times. Suggested token: {candidate.suggested_name}",
location=candidate.locations[0] if candidate.locations else None,
affected_files=[loc.file_path for loc in candidate.locations[:5]],
estimated_impact=f"Single source of truth for this value",
fix_suggestion=f"Create token '{candidate.suggested_name}' with value '{candidate.value}'",
auto_fixable=True,
))
return wins
async def _find_naming_inconsistency_wins(self) -> List[QuickWin]:
"""Find naming inconsistencies."""
wins = []
naming = await self.style_analyzer.analyze_naming_consistency()
if naming.get('inconsistencies'):
primary = naming.get('primary_pattern', 'unknown')
inconsistent_count = len(naming['inconsistencies'])
wins.append(QuickWin(
type=QuickWinType.NAMING_INCONSISTENCY,
priority=QuickWinPriority.LOW,
title=f"Found {inconsistent_count} naming inconsistencies",
description=f"The project primarily uses {primary} naming, but {inconsistent_count} classes use different conventions.",
affected_files=list(set(i['file'] for i in naming['inconsistencies']))[:10],
estimated_impact="Improve code consistency and readability",
fix_suggestion=f"Standardize all class names to use {primary} convention.",
auto_fixable=True,
))
return wins
async def _find_accessibility_wins(self) -> List[QuickWin]:
"""Find accessibility issues."""
wins = []
skip_dirs = {'node_modules', '.git', 'dist', 'build'}
a11y_issues = []
for ext in ['*.jsx', '*.tsx']:
for file_path in self.root.rglob(ext):
if any(skip in file_path.parts for skip in skip_dirs):
continue
try:
content = file_path.read_text(encoding='utf-8', errors='ignore')
rel_path = str(file_path.relative_to(self.root))
# Check for images without alt
img_no_alt = re.findall(r'<img[^>]+(?<!alt=")[^>]*>', content)
if img_no_alt:
for match in img_no_alt[:3]:
if 'alt=' not in match:
line = content[:content.find(match)].count('\n') + 1
a11y_issues.append({
'type': 'img-no-alt',
'file': rel_path,
'line': line,
})
# Check for buttons without accessible text
icon_only_buttons = re.findall(
r'<button[^>]*>\s*<(?:svg|Icon|img)[^>]*/?>\s*</button>',
content,
re.IGNORECASE
)
if icon_only_buttons:
a11y_issues.append({
'type': 'icon-button-no-label',
'file': rel_path,
})
# Check for click handlers on non-interactive elements
div_onclick = re.findall(r'<div[^>]+onClick', content)
if div_onclick:
a11y_issues.append({
'type': 'div-click-handler',
'file': rel_path,
'count': len(div_onclick),
})
except Exception:
continue
# Group issues by type
if a11y_issues:
img_issues = [i for i in a11y_issues if i['type'] == 'img-no-alt']
if img_issues:
wins.append(QuickWin(
type=QuickWinType.ACCESSIBILITY,
priority=QuickWinPriority.HIGH,
title=f"Found {len(img_issues)} images without alt text",
description="Images should have alt attributes for screen readers. Empty alt='' is acceptable for decorative images.",
affected_files=list(set(i['file'] for i in img_issues))[:10],
estimated_impact="Improve accessibility for screen reader users",
fix_suggestion="Add descriptive alt text to images or alt='' for decorative images.",
auto_fixable=False,
))
div_issues = [i for i in a11y_issues if i['type'] == 'div-click-handler']
if div_issues:
wins.append(QuickWin(
type=QuickWinType.ACCESSIBILITY,
priority=QuickWinPriority.MEDIUM,
title=f"Found click handlers on div elements",
description="Using onClick on div elements makes them inaccessible to keyboard users. Use button or add proper ARIA attributes.",
affected_files=list(set(i['file'] for i in div_issues))[:10],
estimated_impact="Improve keyboard navigation accessibility",
fix_suggestion="Replace <div onClick> with <button> or add role='button' and tabIndex={0}.",
auto_fixable=True,
))
return wins
async def get_summary(self) -> Dict[str, Any]:
"""Get summary of all quick-wins."""
wins = await self.find_all()
by_type = {}
by_priority = {}
for win in wins:
type_key = win.type.value
priority_key = win.priority.value
if type_key not in by_type:
by_type[type_key] = 0
by_type[type_key] += 1
if priority_key not in by_priority:
by_priority[priority_key] = 0
by_priority[priority_key] += 1
return {
'total': len(wins),
'by_type': by_type,
'by_priority': by_priority,
'auto_fixable': len([w for w in wins if w.auto_fixable]),
'top_wins': [w.to_dict() for w in wins[:10]],
}
async def get_actionable_report(self) -> str:
"""Generate human-readable report of quick-wins."""
wins = await self.find_all()
if not wins:
return "No quick-wins found. Your codebase looks clean!"
lines = [
"QUICK-WIN OPPORTUNITIES",
"=" * 50,
"",
]
# Group by priority
by_priority = {
QuickWinPriority.CRITICAL: [],
QuickWinPriority.HIGH: [],
QuickWinPriority.MEDIUM: [],
QuickWinPriority.LOW: [],
}
for win in wins:
by_priority[win.priority].append(win)
# Report by priority
priority_labels = {
QuickWinPriority.CRITICAL: "CRITICAL",
QuickWinPriority.HIGH: "HIGH PRIORITY",
QuickWinPriority.MEDIUM: "MEDIUM PRIORITY",
QuickWinPriority.LOW: "LOW PRIORITY",
}
for priority, label in priority_labels.items():
priority_wins = by_priority[priority]
if not priority_wins:
continue
lines.extend([
f"\n[{label}] ({len(priority_wins)} items)",
"-" * 40,
])
for i, win in enumerate(priority_wins[:5], 1):
lines.extend([
f"\n{i}. {win.title}",
f" {win.description[:100]}...",
f" Impact: {win.estimated_impact}",
])
if win.auto_fixable:
lines.append(" [Auto-fixable]")
if len(priority_wins) > 5:
lines.append(f"\n ... and {len(priority_wins) - 5} more")
# Summary
lines.extend([
"",
"=" * 50,
"SUMMARY",
f"Total quick-wins: {len(wins)}",
f"Auto-fixable: {len([w for w in wins if w.auto_fixable])}",
"",
"Run 'dss fix --preview' to see suggested changes.",
])
return "\n".join(lines)

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dss/analyze/react.py Normal file
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"""
React Project Analyzer
Analyzes React codebases to extract component information,
detect patterns, and identify style usage.
"""
import re
from pathlib import Path
from typing import List, Dict, Any, Optional, Set, Tuple
from dataclasses import dataclass, field
from .base import (
ComponentInfo,
Location,
StylePattern,
StylingApproach,
)
# Patterns for React component detection
FUNCTIONAL_COMPONENT = re.compile(
r'(?:export\s+)?(?:const|let|var|function)\s+([A-Z][A-Za-z0-9]*)\s*(?::\s*(?:React\.)?FC)?'
r'\s*(?:=\s*(?:\([^)]*\)|[a-zA-Z_]\w*)\s*=>|\()',
re.MULTILINE
)
CLASS_COMPONENT = re.compile(
r'class\s+([A-Z][A-Za-z0-9]*)\s+extends\s+(?:React\.)?(?:Component|PureComponent)',
re.MULTILINE
)
FORWARD_REF = re.compile(
r'(?:export\s+)?(?:const|let)\s+([A-Z][A-Za-z0-9]*)\s*=\s*(?:React\.)?forwardRef',
re.MULTILINE
)
MEMO_COMPONENT = re.compile(
r'(?:export\s+)?(?:const|let)\s+([A-Z][A-Za-z0-9]*)\s*=\s*(?:React\.)?memo\(',
re.MULTILINE
)
# Import patterns
IMPORT_PATTERN = re.compile(
r'import\s+(?:\{[^}]+\}|\*\s+as\s+\w+|\w+)\s+from\s+["\']([^"\']+)["\']',
re.MULTILINE
)
STYLE_IMPORT = re.compile(
r'import\s+(?:(\w+)\s+from\s+)?["\']([^"\']+\.(?:css|scss|sass|less|styl))["\']',
re.MULTILINE
)
# Inline style patterns
INLINE_STYLE_OBJECT = re.compile(
r'style\s*=\s*\{\s*\{([^}]+)\}\s*\}',
re.MULTILINE | re.DOTALL
)
INLINE_STYLE_VAR = re.compile(
r'style\s*=\s*\{(\w+)\}',
re.MULTILINE
)
# Props extraction
PROPS_DESTRUCTURE = re.compile(
r'\(\s*\{\s*([^}]+)\s*\}\s*(?::\s*[^)]+)?\)',
re.MULTILINE
)
PROPS_INTERFACE = re.compile(
r'interface\s+\w*Props\s*\{([^}]+)\}',
re.MULTILINE | re.DOTALL
)
PROPS_TYPE = re.compile(
r'type\s+\w*Props\s*=\s*\{([^}]+)\}',
re.MULTILINE | re.DOTALL
)
class ReactAnalyzer:
"""
Analyzes React projects for component structure and style usage.
"""
def __init__(self, root_path: str):
self.root = Path(root_path).resolve()
async def analyze(
self,
component_files: Optional[List[Path]] = None
) -> List[ComponentInfo]:
"""
Analyze React components in the project.
Args:
component_files: Optional list of files to analyze.
If None, scans the project.
Returns:
List of ComponentInfo for each detected component.
"""
if component_files is None:
component_files = self._find_component_files()
components = []
for file_path in component_files:
try:
file_components = await self._analyze_file(file_path)
components.extend(file_components)
except Exception as e:
# Log error but continue
continue
return components
def _find_component_files(self) -> List[Path]:
"""Find all potential React component files."""
skip_dirs = {'node_modules', '.git', 'dist', 'build', '.next'}
component_files = []
for ext in ['*.jsx', '*.tsx']:
for path in self.root.rglob(ext):
if not any(skip in path.parts for skip in skip_dirs):
component_files.append(path)
# Also check .js/.ts files that look like components
for ext in ['*.js', '*.ts']:
for path in self.root.rglob(ext):
if any(skip in path.parts for skip in skip_dirs):
continue
# Skip config and utility files
if any(x in path.name.lower() for x in ['config', 'util', 'helper', 'hook', 'context']):
continue
# Check if PascalCase (likely component)
if path.stem[0].isupper():
component_files.append(path)
return component_files
async def _analyze_file(self, file_path: Path) -> List[ComponentInfo]:
"""Analyze a single file for React components."""
content = file_path.read_text(encoding='utf-8', errors='ignore')
components = []
# Find all components in the file
component_matches = []
# Functional components
for match in FUNCTIONAL_COMPONENT.finditer(content):
name = match.group(1)
if self._is_valid_component_name(name):
component_matches.append((name, 'functional', match.start()))
# Class components
for match in CLASS_COMPONENT.finditer(content):
name = match.group(1)
component_matches.append((name, 'class', match.start()))
# forwardRef components
for match in FORWARD_REF.finditer(content):
name = match.group(1)
component_matches.append((name, 'forwardRef', match.start()))
# memo components
for match in MEMO_COMPONENT.finditer(content):
name = match.group(1)
component_matches.append((name, 'memo', match.start()))
# Dedupe by name (keep first occurrence)
seen_names = set()
unique_matches = []
for name, comp_type, pos in component_matches:
if name not in seen_names:
seen_names.add(name)
unique_matches.append((name, comp_type, pos))
# Extract imports (shared across all components in file)
imports = self._extract_imports(content)
style_files = self._extract_style_imports(content)
inline_styles = self._find_inline_styles(content)
# Create ComponentInfo for each
for name, comp_type, pos in unique_matches:
# Extract props for this component
props = self._extract_props(content, name)
# Find child components used
children = self._find_child_components(content, seen_names)
# Check if component has styles
has_styles = bool(style_files) or bool(inline_styles)
components.append(ComponentInfo(
name=name,
path=str(file_path.relative_to(self.root)),
type=comp_type,
props=props,
has_styles=has_styles,
style_files=style_files,
inline_style_count=len(inline_styles),
imports=imports,
exports=self._find_exports(content, name),
children=children,
line_count=content.count('\n') + 1,
))
return components
def _is_valid_component_name(self, name: str) -> bool:
"""Check if a name is a valid React component name."""
# Must be PascalCase
if not name[0].isupper():
return False
# Filter out common non-component patterns
invalid_names = {
'React', 'Component', 'PureComponent', 'Fragment',
'Suspense', 'Provider', 'Consumer', 'Context',
'Error', 'ErrorBoundary', 'Wrapper', 'Container',
'Props', 'State', 'Type', 'Interface',
}
return name not in invalid_names
def _extract_imports(self, content: str) -> List[str]:
"""Extract import paths from file."""
imports = []
for match in IMPORT_PATTERN.finditer(content):
import_path = match.group(1)
# Skip node_modules style imports for brevity
if not import_path.startswith('.') and '/' not in import_path:
continue
imports.append(import_path)
return imports
def _extract_style_imports(self, content: str) -> List[str]:
"""Extract style file imports."""
style_files = []
for match in STYLE_IMPORT.finditer(content):
style_path = match.group(2)
style_files.append(style_path)
return style_files
def _find_inline_styles(self, content: str) -> List[Location]:
"""Find inline style usage locations."""
locations = []
# style={{ ... }}
for match in INLINE_STYLE_OBJECT.finditer(content):
line = content[:match.start()].count('\n') + 1
locations.append(Location(
file_path="", # Will be set by caller
line=line,
))
return locations
def _extract_props(self, content: str, component_name: str) -> List[str]:
"""Extract props for a component."""
props = set()
# Look for destructured props
for match in PROPS_DESTRUCTURE.finditer(content):
props_str = match.group(1)
# Extract prop names from destructuring
for prop in re.findall(r'(\w+)(?:\s*[=:])?', props_str):
if prop and not prop[0].isupper(): # Skip types
props.add(prop)
# Look for Props interface/type
for pattern in [PROPS_INTERFACE, PROPS_TYPE]:
for match in pattern.finditer(content):
props_str = match.group(1)
# Extract prop names
for line in props_str.split('\n'):
prop_match = re.match(r'\s*(\w+)\s*[?:]', line)
if prop_match:
props.add(prop_match.group(1))
return list(props)
def _find_child_components(
self,
content: str,
current_components: Set[str]
) -> List[str]:
"""Find child components used in JSX."""
children = set()
# Find JSX elements that look like components (PascalCase)
jsx_pattern = re.compile(r'<([A-Z][A-Za-z0-9]*)')
for match in jsx_pattern.finditer(content):
component_name = match.group(1)
# Skip current file's components and React built-ins
if component_name not in current_components:
if component_name not in {'Fragment', 'Suspense', 'Provider'}:
children.add(component_name)
return list(children)
def _find_exports(self, content: str, component_name: str) -> List[str]:
"""Find export type for component."""
exports = []
# Default export
if re.search(rf'export\s+default\s+{component_name}\b', content):
exports.append('default')
if re.search(rf'export\s+default\s+(?:function|const)\s+{component_name}\b', content):
exports.append('default')
# Named export
if re.search(rf'export\s+(?:const|function|class)\s+{component_name}\b', content):
exports.append('named')
if re.search(r'export\s*\{[^}]*\b' + re.escape(component_name) + r'\b[^}]*\}', content):
exports.append('named')
return exports
async def find_inline_styles(self, path: Optional[str] = None) -> List[Dict[str, Any]]:
"""
Find all inline style usage in the project.
Returns list of inline style occurrences with:
- file path
- line number
- style content
- component name (if detectable)
"""
search_path = Path(path) if path else self.root
results = []
for ext in ['*.jsx', '*.tsx', '*.js', '*.ts']:
for file_path in search_path.rglob(ext):
if any(skip in file_path.parts for skip in
{'node_modules', '.git', 'dist', 'build'}):
continue
try:
content = file_path.read_text(encoding='utf-8', errors='ignore')
# Find style={{ ... }}
for match in INLINE_STYLE_OBJECT.finditer(content):
line = content[:match.start()].count('\n') + 1
style_content = match.group(1).strip()
results.append({
'file': str(file_path.relative_to(self.root)),
'line': line,
'content': style_content[:200],
'type': 'object',
})
# Find style={variable}
for match in INLINE_STYLE_VAR.finditer(content):
line = content[:match.start()].count('\n') + 1
var_name = match.group(1)
results.append({
'file': str(file_path.relative_to(self.root)),
'line': line,
'content': f'style={{{var_name}}}',
'type': 'variable',
'variable': var_name,
})
except Exception:
continue
return results
async def get_component_tree(self) -> Dict[str, List[str]]:
"""
Build component dependency tree.
Returns dict mapping component names to their child components.
"""
components = await self.analyze()
tree = {}
for comp in components:
tree[comp.name] = comp.children
return tree
async def find_style_patterns(self) -> Dict[str, List[Dict]]:
"""
Find different styling patterns used across the project.
Returns dict with pattern types and their occurrences.
"""
patterns = {
'inline_styles': [],
'css_modules': [],
'styled_components': [],
'emotion': [],
'tailwind': [],
'css_classes': [],
}
component_files = self._find_component_files()
for file_path in component_files:
try:
content = file_path.read_text(encoding='utf-8', errors='ignore')
rel_path = str(file_path.relative_to(self.root))
# CSS Modules
if re.search(r'import\s+\w+\s+from\s+["\'].*\.module\.', content):
patterns['css_modules'].append({'file': rel_path})
# styled-components
if re.search(r'styled\.|from\s+["\']styled-components', content):
patterns['styled_components'].append({'file': rel_path})
# Emotion
if re.search(r'@emotion|css`', content):
patterns['emotion'].append({'file': rel_path})
# Tailwind (className with utility classes)
if re.search(r'className\s*=\s*["\'][^"\']*(?:flex|grid|p-\d|m-\d|bg-)', content):
patterns['tailwind'].append({'file': rel_path})
# Regular CSS classes
if re.search(r'className\s*=\s*["\'][a-zA-Z]', content):
patterns['css_classes'].append({'file': rel_path})
# Inline styles
for match in INLINE_STYLE_OBJECT.finditer(content):
line = content[:match.start()].count('\n') + 1
patterns['inline_styles'].append({
'file': rel_path,
'line': line,
})
except Exception:
continue
return patterns

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"""
Project Scanner
Scans file system to discover project structure, frameworks, and style files.
"""
import json
import re
from pathlib import Path
from typing import List, Dict, Any, Optional, Set, Tuple
from dataclasses import dataclass, field
from .base import (
Framework,
StylingApproach,
StyleFile,
ProjectAnalysis,
)
# Directories to skip during scanning
SKIP_DIRS = {
'node_modules',
'.git',
'.next',
'.nuxt',
'dist',
'build',
'out',
'.cache',
'coverage',
'__pycache__',
'.venv',
'venv',
'.turbo',
'.vercel',
}
# File extensions to scan
SCAN_EXTENSIONS = {
# JavaScript/TypeScript
'.js', '.jsx', '.ts', '.tsx', '.mjs', '.cjs',
# Styles
'.css', '.scss', '.sass', '.less', '.styl',
# Config
'.json',
}
@dataclass
class ScanResult:
"""Result of file system scan."""
files: List[Path] = field(default_factory=list)
style_files: List[Path] = field(default_factory=list)
component_files: List[Path] = field(default_factory=list)
config_files: Dict[str, Path] = field(default_factory=dict)
total_lines: int = 0
class ProjectScanner:
"""
Scans a project directory to identify:
- Framework (React, Next, Vue, etc.)
- Styling approach (CSS modules, styled-components, Tailwind, etc.)
- Component files
- Style files
Results are cached in memory for the session.
"""
# Class-level cache: path -> (timestamp, analysis)
_cache: Dict[str, Tuple[float, ProjectAnalysis]] = {}
_cache_ttl: float = 60.0 # Cache for 60 seconds
def __init__(self, root_path: str, use_cache: bool = True):
self.root = Path(root_path).resolve()
self.use_cache = use_cache
if not self.root.exists():
raise FileNotFoundError(f"Project path not found: {root_path}")
async def scan(self) -> ProjectAnalysis:
"""
Perform full project scan.
Returns:
ProjectAnalysis with detected framework, styles, and files
"""
# Check cache if enabled
if self.use_cache:
import time
cache_key = str(self.root)
if cache_key in self._cache:
timestamp, cached_analysis = self._cache[cache_key]
if time.time() - timestamp < self._cache_ttl:
return cached_analysis
# Scan file system
scan_result = self._scan_files()
# Detect framework
framework, version = self._detect_framework(scan_result.config_files)
# Detect styling approaches
styling = self._detect_styling(scan_result)
# Collect style files
style_files = self._analyze_style_files(scan_result.style_files)
# Build analysis result
analysis = ProjectAnalysis(
project_path=str(self.root),
framework=framework,
framework_version=version,
style_files=style_files,
style_file_count=len(style_files),
stats={
"total_files_scanned": len(scan_result.files),
"total_lines": scan_result.total_lines,
"component_files": len(scan_result.component_files),
"style_files": len(scan_result.style_files),
}
)
# Determine primary styling approach
if styling:
analysis.styling_approaches = styling
# Primary is the one with most occurrences
analysis.primary_styling = max(
styling, key=lambda x: x.count
).type if styling else None
# Cache result if enabled
if self.use_cache:
import time
cache_key = str(self.root)
self._cache[cache_key] = (time.time(), analysis)
return analysis
def _scan_files(self) -> ScanResult:
"""Scan directory for relevant files."""
result = ScanResult()
for path in self.root.rglob("*"):
# Skip directories in skip list
if any(skip in path.parts for skip in SKIP_DIRS):
continue
if not path.is_file():
continue
suffix = path.suffix.lower()
if suffix not in SCAN_EXTENSIONS:
continue
result.files.append(path)
# Categorize files
if suffix in {'.css', '.scss', '.sass', '.less', '.styl'}:
result.style_files.append(path)
elif suffix in {'.jsx', '.tsx'}:
result.component_files.append(path)
elif suffix in {'.js', '.ts'}:
# Check if it's a component or config
name = path.name.lower()
if any(cfg in name for cfg in ['config', 'rc', '.config']):
result.config_files[name] = path
elif self._looks_like_component(path):
result.component_files.append(path)
# Count lines (approximate for large files)
try:
content = path.read_text(encoding='utf-8', errors='ignore')
result.total_lines += content.count('\n') + 1
except Exception:
pass
# Look for specific config files
config_names = [
'package.json',
'tsconfig.json',
'tailwind.config.js',
'tailwind.config.ts',
'next.config.js',
'next.config.mjs',
'vite.config.js',
'vite.config.ts',
'nuxt.config.js',
'nuxt.config.ts',
'.eslintrc.json',
'.eslintrc.js',
]
for name in config_names:
config_path = self.root / name
if config_path.exists():
result.config_files[name] = config_path
return result
def _looks_like_component(self, path: Path) -> bool:
"""Check if a JS/TS file looks like a React component."""
name = path.stem
# PascalCase is a strong indicator
if name[0].isupper() and not name.isupper():
return True
# Common component patterns
if any(x in name.lower() for x in ['component', 'page', 'view', 'screen']):
return True
return False
def _detect_framework(
self,
config_files: Dict[str, Path]
) -> Tuple[Framework, str]:
"""Detect the UI framework and version."""
# Check package.json for dependencies
pkg_json = config_files.get('package.json')
if not pkg_json:
return Framework.UNKNOWN, ""
try:
pkg = json.loads(pkg_json.read_text())
deps = {
**pkg.get('dependencies', {}),
**pkg.get('devDependencies', {}),
}
# Check for Next.js first (it includes React)
if 'next' in deps:
return Framework.NEXT, deps.get('next', '').lstrip('^~')
# Check for Nuxt (Vue-based)
if 'nuxt' in deps:
return Framework.NUXT, deps.get('nuxt', '').lstrip('^~')
# Check for other frameworks
if 'react' in deps:
return Framework.REACT, deps.get('react', '').lstrip('^~')
if 'vue' in deps:
return Framework.VUE, deps.get('vue', '').lstrip('^~')
if '@angular/core' in deps:
return Framework.ANGULAR, deps.get('@angular/core', '').lstrip('^~')
if 'svelte' in deps:
return Framework.SVELTE, deps.get('svelte', '').lstrip('^~')
if 'solid-js' in deps:
return Framework.SOLID, deps.get('solid-js', '').lstrip('^~')
except (json.JSONDecodeError, KeyError):
pass
return Framework.UNKNOWN, ""
def _detect_styling(self, scan_result: ScanResult) -> List:
"""Detect styling approaches used in the project."""
from .base import StylePattern, Location
patterns: Dict[StylingApproach, StylePattern] = {}
# Check config files for styling indicators
pkg_json = scan_result.config_files.get('package.json')
if pkg_json:
try:
pkg = json.loads(pkg_json.read_text())
deps = {
**pkg.get('dependencies', {}),
**pkg.get('devDependencies', {}),
}
# Tailwind
if 'tailwindcss' in deps:
patterns[StylingApproach.TAILWIND] = StylePattern(
type=StylingApproach.TAILWIND,
count=1,
examples=["tailwindcss in dependencies"]
)
# styled-components
if 'styled-components' in deps:
patterns[StylingApproach.STYLED_COMPONENTS] = StylePattern(
type=StylingApproach.STYLED_COMPONENTS,
count=1,
examples=["styled-components in dependencies"]
)
# Emotion
if '@emotion/react' in deps or '@emotion/styled' in deps:
patterns[StylingApproach.EMOTION] = StylePattern(
type=StylingApproach.EMOTION,
count=1,
examples=["@emotion in dependencies"]
)
# SASS/SCSS
if 'sass' in deps or 'node-sass' in deps:
patterns[StylingApproach.SASS_SCSS] = StylePattern(
type=StylingApproach.SASS_SCSS,
count=1,
examples=["sass in dependencies"]
)
except (json.JSONDecodeError, KeyError):
pass
# Check tailwind config
if 'tailwind.config.js' in scan_result.config_files or \
'tailwind.config.ts' in scan_result.config_files:
if StylingApproach.TAILWIND not in patterns:
patterns[StylingApproach.TAILWIND] = StylePattern(
type=StylingApproach.TAILWIND,
count=1,
examples=["tailwind.config found"]
)
# Scan component files for styling patterns
for comp_file in scan_result.component_files[:100]: # Limit for performance
try:
content = comp_file.read_text(encoding='utf-8', errors='ignore')
self._detect_patterns_in_file(
content, str(comp_file), patterns
)
except Exception:
pass
# Check style files
for style_file in scan_result.style_files:
suffix = style_file.suffix.lower()
if suffix == '.css':
# Check for CSS modules
if '.module.css' in style_file.name.lower():
approach = StylingApproach.CSS_MODULES
else:
approach = StylingApproach.VANILLA_CSS
if approach not in patterns:
patterns[approach] = StylePattern(type=approach)
patterns[approach].count += 1
patterns[approach].locations.append(
Location(str(style_file), 1)
)
elif suffix in {'.scss', '.sass'}:
if StylingApproach.SASS_SCSS not in patterns:
patterns[StylingApproach.SASS_SCSS] = StylePattern(
type=StylingApproach.SASS_SCSS
)
patterns[StylingApproach.SASS_SCSS].count += 1
return list(patterns.values())
def _detect_patterns_in_file(
self,
content: str,
file_path: str,
patterns: Dict[StylingApproach, Any]
) -> None:
"""Detect styling patterns in a single file."""
from .base import StylePattern, Location
# CSS Modules import
css_module_pattern = re.compile(
r"import\s+\w+\s+from\s+['\"].*\.module\.(css|scss|sass)['\"]"
)
for match in css_module_pattern.finditer(content):
if StylingApproach.CSS_MODULES not in patterns:
patterns[StylingApproach.CSS_MODULES] = StylePattern(
type=StylingApproach.CSS_MODULES
)
patterns[StylingApproach.CSS_MODULES].count += 1
line_num = content[:match.start()].count('\n') + 1
patterns[StylingApproach.CSS_MODULES].locations.append(
Location(file_path, line_num)
)
# styled-components
styled_pattern = re.compile(
r"(styled\.|styled\()|(from\s+['\"]styled-components['\"])"
)
for match in styled_pattern.finditer(content):
if StylingApproach.STYLED_COMPONENTS not in patterns:
patterns[StylingApproach.STYLED_COMPONENTS] = StylePattern(
type=StylingApproach.STYLED_COMPONENTS
)
patterns[StylingApproach.STYLED_COMPONENTS].count += 1
# Emotion
emotion_pattern = re.compile(
r"(css`|@emotion|from\s+['\"]@emotion)"
)
for match in emotion_pattern.finditer(content):
if StylingApproach.EMOTION not in patterns:
patterns[StylingApproach.EMOTION] = StylePattern(
type=StylingApproach.EMOTION
)
patterns[StylingApproach.EMOTION].count += 1
# Inline styles
inline_pattern = re.compile(
r'style\s*=\s*\{\s*\{[^}]+\}\s*\}'
)
for match in inline_pattern.finditer(content):
if StylingApproach.INLINE_STYLES not in patterns:
patterns[StylingApproach.INLINE_STYLES] = StylePattern(
type=StylingApproach.INLINE_STYLES
)
patterns[StylingApproach.INLINE_STYLES].count += 1
line_num = content[:match.start()].count('\n') + 1
patterns[StylingApproach.INLINE_STYLES].locations.append(
Location(file_path, line_num)
)
patterns[StylingApproach.INLINE_STYLES].examples.append(
match.group(0)[:100]
)
# Tailwind classes
tailwind_pattern = re.compile(
r'className\s*=\s*["\'][^"\']*(?:flex|grid|p-|m-|bg-|text-|border-)[^"\']*["\']'
)
for match in tailwind_pattern.finditer(content):
if StylingApproach.TAILWIND not in patterns:
patterns[StylingApproach.TAILWIND] = StylePattern(
type=StylingApproach.TAILWIND
)
patterns[StylingApproach.TAILWIND].count += 1
def _analyze_style_files(self, style_paths: List[Path]) -> List[StyleFile]:
"""Analyze style files for metadata."""
style_files = []
for path in style_paths:
try:
content = path.read_text(encoding='utf-8', errors='ignore')
# Determine type
suffix = path.suffix.lower()
if '.module.' in path.name.lower():
file_type = 'css-module'
elif suffix == '.scss':
file_type = 'scss'
elif suffix == '.sass':
file_type = 'sass'
elif suffix == '.less':
file_type = 'less'
else:
file_type = 'css'
# Count variables
var_count = 0
if file_type == 'css' or file_type == 'css-module':
var_count = len(re.findall(r'--[\w-]+\s*:', content))
elif file_type in {'scss', 'sass'}:
var_count = len(re.findall(r'\$[\w-]+\s*:', content))
# Count selectors (approximate)
selector_count = len(re.findall(r'[.#][\w-]+\s*\{', content))
# Find imports
imports = re.findall(r'@import\s+["\']([^"\']+)["\']', content)
style_files.append(StyleFile(
path=str(path.relative_to(self.root)),
type=file_type,
size_bytes=path.stat().st_size,
line_count=content.count('\n') + 1,
variable_count=var_count,
selector_count=selector_count,
imports=imports,
))
except Exception:
continue
return style_files
def get_file_tree(self, max_depth: int = 3) -> Dict[str, Any]:
"""Get project file tree structure."""
def build_tree(path: Path, depth: int) -> Dict[str, Any]:
if depth > max_depth:
return {"...": "truncated"}
result = {}
try:
for item in sorted(path.iterdir()):
if item.name in SKIP_DIRS:
continue
if item.is_dir():
result[item.name + "/"] = build_tree(item, depth + 1)
elif item.suffix in SCAN_EXTENSIONS:
result[item.name] = item.stat().st_size
except PermissionError:
pass
return result
return build_tree(self.root, 0)

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"""
Style Pattern Analyzer
Detects and analyzes style patterns in code to identify:
- Hardcoded values that should be tokens
- Duplicate values across files
- Inconsistent naming patterns
- Unused styles
"""
import re
from pathlib import Path
from typing import List, Dict, Any, Optional, Set, Tuple
from collections import defaultdict
from dataclasses import dataclass, field
from .base import (
Location,
TokenCandidate,
StylePattern,
StylingApproach,
)
# Color patterns
HEX_COLOR = re.compile(r'#(?:[0-9a-fA-F]{3}){1,2}\b')
RGB_COLOR = re.compile(r'rgba?\s*\(\s*\d+\s*,\s*\d+\s*,\s*\d+(?:\s*,\s*[\d.]+)?\s*\)')
HSL_COLOR = re.compile(r'hsla?\s*\(\s*\d+\s*,\s*[\d.]+%\s*,\s*[\d.]+%(?:\s*,\s*[\d.]+)?\s*\)')
OKLCH_COLOR = re.compile(r'oklch\s*\([^)]+\)')
# Dimension patterns
PX_VALUE = re.compile(r'\b(\d+(?:\.\d+)?)\s*px\b')
REM_VALUE = re.compile(r'\b(\d+(?:\.\d+)?)\s*rem\b')
EM_VALUE = re.compile(r'\b(\d+(?:\.\d+)?)\s*em\b')
PERCENT_VALUE = re.compile(r'\b(\d+(?:\.\d+)?)\s*%\b')
# Font patterns
FONT_SIZE = re.compile(r'font-size\s*:\s*([^;]+)')
FONT_FAMILY = re.compile(r'font-family\s*:\s*([^;]+)')
FONT_WEIGHT = re.compile(r'font-weight\s*:\s*(\d+|normal|bold|lighter|bolder)')
LINE_HEIGHT = re.compile(r'line-height\s*:\s*([^;]+)')
# Spacing patterns
MARGIN_PADDING = re.compile(r'(?:margin|padding)(?:-(?:top|right|bottom|left))?\s*:\s*([^;]+)')
GAP = re.compile(r'gap\s*:\s*([^;]+)')
# Border patterns
BORDER_RADIUS = re.compile(r'border-radius\s*:\s*([^;]+)')
BORDER_WIDTH = re.compile(r'border(?:-(?:top|right|bottom|left))?-width\s*:\s*([^;]+)')
# Shadow patterns
BOX_SHADOW = re.compile(r'box-shadow\s*:\s*([^;]+)')
# Z-index
Z_INDEX = re.compile(r'z-index\s*:\s*(\d+)')
@dataclass
class ValueOccurrence:
"""Tracks where a value appears."""
value: str
file: str
line: int
property: str # CSS property name
context: str # Surrounding code
class StyleAnalyzer:
"""
Analyzes style files and inline styles to find:
- Hardcoded values that should be tokens
- Duplicate values
- Inconsistent patterns
"""
def __init__(self, root_path: str):
self.root = Path(root_path).resolve()
self.values: Dict[str, List[ValueOccurrence]] = defaultdict(list)
self.color_values: Dict[str, List[ValueOccurrence]] = defaultdict(list)
self.spacing_values: Dict[str, List[ValueOccurrence]] = defaultdict(list)
self.font_values: Dict[str, List[ValueOccurrence]] = defaultdict(list)
async def analyze(
self,
include_inline: bool = True,
include_css: bool = True
) -> Dict[str, Any]:
"""
Analyze all styles in the project.
Returns:
Dict with analysis results including duplicates and candidates
"""
# Reset collectors
self.values.clear()
self.color_values.clear()
self.spacing_values.clear()
self.font_values.clear()
# Scan CSS/SCSS files
if include_css:
await self._scan_style_files()
# Scan inline styles in JS/TS files
if include_inline:
await self._scan_inline_styles()
# Analyze results
duplicates = self._find_duplicates()
candidates = self._generate_token_candidates()
return {
'total_values_found': sum(len(v) for v in self.values.values()),
'unique_colors': len(self.color_values),
'unique_spacing': len(self.spacing_values),
'duplicates': duplicates,
'token_candidates': candidates,
}
async def _scan_style_files(self) -> None:
"""Scan CSS and SCSS files for values."""
skip_dirs = {'node_modules', '.git', 'dist', 'build'}
for pattern in ['**/*.css', '**/*.scss', '**/*.sass', '**/*.less']:
for file_path in self.root.rglob(pattern):
if any(skip in file_path.parts for skip in skip_dirs):
continue
try:
content = file_path.read_text(encoding='utf-8', errors='ignore')
rel_path = str(file_path.relative_to(self.root))
self._extract_values_from_css(content, rel_path)
except Exception:
continue
async def _scan_inline_styles(self) -> None:
"""Scan JS/TS files for inline style values."""
skip_dirs = {'node_modules', '.git', 'dist', 'build'}
for pattern in ['**/*.jsx', '**/*.tsx', '**/*.js', '**/*.ts']:
for file_path in self.root.rglob(pattern):
if any(skip in file_path.parts for skip in skip_dirs):
continue
try:
content = file_path.read_text(encoding='utf-8', errors='ignore')
rel_path = str(file_path.relative_to(self.root))
self._extract_values_from_jsx(content, rel_path)
except Exception:
continue
def _extract_values_from_css(self, content: str, file_path: str) -> None:
"""Extract style values from CSS content."""
lines = content.split('\n')
for line_num, line in enumerate(lines, 1):
# Skip comments and empty lines
if not line.strip() or line.strip().startswith('//') or line.strip().startswith('/*'):
continue
# Extract colors
for pattern in [HEX_COLOR, RGB_COLOR, HSL_COLOR, OKLCH_COLOR]:
for match in pattern.finditer(line):
value = match.group(0).lower()
self._record_color(value, file_path, line_num, line.strip())
# Extract dimensions
for match in PX_VALUE.finditer(line):
value = f"{match.group(1)}px"
self._record_spacing(value, file_path, line_num, line.strip())
for match in REM_VALUE.finditer(line):
value = f"{match.group(1)}rem"
self._record_spacing(value, file_path, line_num, line.strip())
# Extract font properties
for match in FONT_SIZE.finditer(line):
value = match.group(1).strip()
self._record_font(value, file_path, line_num, 'font-size', line.strip())
for match in FONT_WEIGHT.finditer(line):
value = match.group(1).strip()
self._record_font(value, file_path, line_num, 'font-weight', line.strip())
# Extract z-index
for match in Z_INDEX.finditer(line):
value = match.group(1)
self._record_value(f"z-{value}", file_path, line_num, 'z-index', line.strip())
def _extract_values_from_jsx(self, content: str, file_path: str) -> None:
"""Extract style values from JSX inline styles."""
# Find style={{ ... }} blocks
style_pattern = re.compile(r'style\s*=\s*\{\s*\{([^}]+)\}\s*\}', re.DOTALL)
for match in style_pattern.finditer(content):
style_content = match.group(1)
line_num = content[:match.start()].count('\n') + 1
# Parse the style object
# Look for property: value patterns
prop_pattern = re.compile(r'(\w+)\s*:\s*["\']?([^,\n"\']+)["\']?')
for prop_match in prop_pattern.finditer(style_content):
prop_name = prop_match.group(1)
prop_value = prop_match.group(2).strip()
# Check for colors
if any(c in prop_name.lower() for c in ['color', 'background']):
if HEX_COLOR.search(prop_value) or RGB_COLOR.search(prop_value):
self._record_color(prop_value.lower(), file_path, line_num, style_content[:100])
# Check for dimensions
if PX_VALUE.search(prop_value):
self._record_spacing(prop_value, file_path, line_num, style_content[:100])
if 'fontSize' in prop_name or 'fontWeight' in prop_name:
self._record_font(prop_value, file_path, line_num, prop_name, style_content[:100])
def _record_color(self, value: str, file: str, line: int, context: str) -> None:
"""Record a color value occurrence."""
normalized = self._normalize_color(value)
self.color_values[normalized].append(ValueOccurrence(
value=value,
file=file,
line=line,
property='color',
context=context,
))
self.values[normalized].append(ValueOccurrence(
value=value,
file=file,
line=line,
property='color',
context=context,
))
def _record_spacing(self, value: str, file: str, line: int, context: str) -> None:
"""Record a spacing/dimension value occurrence."""
self.spacing_values[value].append(ValueOccurrence(
value=value,
file=file,
line=line,
property='spacing',
context=context,
))
self.values[value].append(ValueOccurrence(
value=value,
file=file,
line=line,
property='spacing',
context=context,
))
def _record_font(self, value: str, file: str, line: int, prop: str, context: str) -> None:
"""Record a font-related value occurrence."""
self.font_values[value].append(ValueOccurrence(
value=value,
file=file,
line=line,
property=prop,
context=context,
))
self.values[value].append(ValueOccurrence(
value=value,
file=file,
line=line,
property=prop,
context=context,
))
def _record_value(self, value: str, file: str, line: int, prop: str, context: str) -> None:
"""Record a generic value occurrence."""
self.values[value].append(ValueOccurrence(
value=value,
file=file,
line=line,
property=prop,
context=context,
))
def _normalize_color(self, color: str) -> str:
"""Normalize color value for comparison."""
color = color.lower().strip()
# Expand 3-digit hex to 6-digit
if re.match(r'^#[0-9a-f]{3}$', color):
color = f"#{color[1]*2}{color[2]*2}{color[3]*2}"
return color
def _find_duplicates(self) -> List[Dict[str, Any]]:
"""Find values that appear multiple times."""
duplicates = []
for value, occurrences in self.values.items():
if len(occurrences) >= 2:
# Get unique files
files = list(set(o.file for o in occurrences))
duplicates.append({
'value': value,
'count': len(occurrences),
'files': files[:5], # Limit to 5 files
'category': occurrences[0].property,
'locations': [
{'file': o.file, 'line': o.line}
for o in occurrences[:5]
],
})
# Sort by count (most duplicated first)
duplicates.sort(key=lambda x: x['count'], reverse=True)
return duplicates[:50] # Return top 50
def _generate_token_candidates(self) -> List[TokenCandidate]:
"""Generate token suggestions for repeated values."""
candidates = []
# Color candidates
for value, occurrences in self.color_values.items():
if len(occurrences) >= 2:
suggested_name = self._suggest_color_name(value)
candidates.append(TokenCandidate(
value=value,
suggested_name=suggested_name,
category='colors',
occurrences=len(occurrences),
locations=[
Location(o.file, o.line) for o in occurrences[:5]
],
confidence=min(0.9, 0.3 + (len(occurrences) * 0.1)),
))
# Spacing candidates
for value, occurrences in self.spacing_values.items():
if len(occurrences) >= 3: # Higher threshold for spacing
suggested_name = self._suggest_spacing_name(value)
candidates.append(TokenCandidate(
value=value,
suggested_name=suggested_name,
category='spacing',
occurrences=len(occurrences),
locations=[
Location(o.file, o.line) for o in occurrences[:5]
],
confidence=min(0.8, 0.2 + (len(occurrences) * 0.05)),
))
# Sort by confidence
candidates.sort(key=lambda x: x.confidence, reverse=True)
return candidates[:30] # Return top 30
def _suggest_color_name(self, color: str) -> str:
"""Suggest a token name for a color value."""
# Common color mappings
common_colors = {
'#ffffff': 'color.white',
'#000000': 'color.black',
'#f3f4f6': 'color.neutral.100',
'#e5e7eb': 'color.neutral.200',
'#d1d5db': 'color.neutral.300',
'#9ca3af': 'color.neutral.400',
'#6b7280': 'color.neutral.500',
'#4b5563': 'color.neutral.600',
'#374151': 'color.neutral.700',
'#1f2937': 'color.neutral.800',
'#111827': 'color.neutral.900',
}
if color in common_colors:
return common_colors[color]
# Detect color family by hue (simplified)
if color.startswith('#'):
return f"color.custom.{color[1:7]}"
return f"color.custom.value"
def _suggest_spacing_name(self, value: str) -> str:
"""Suggest a token name for a spacing value."""
# Common spacing values
spacing_map = {
'0px': 'spacing.0',
'4px': 'spacing.xs',
'8px': 'spacing.sm',
'12px': 'spacing.md',
'16px': 'spacing.lg',
'20px': 'spacing.lg',
'24px': 'spacing.xl',
'32px': 'spacing.2xl',
'48px': 'spacing.3xl',
'64px': 'spacing.4xl',
'0.25rem': 'spacing.xs',
'0.5rem': 'spacing.sm',
'0.75rem': 'spacing.md',
'1rem': 'spacing.lg',
'1.5rem': 'spacing.xl',
'2rem': 'spacing.2xl',
}
if value in spacing_map:
return spacing_map[value]
return f"spacing.custom.{value.replace('px', '').replace('rem', 'r')}"
async def find_unused_styles(self) -> List[Dict[str, Any]]:
"""
Find CSS classes/selectors that are not used in the codebase.
Returns list of potentially unused styles.
"""
# Collect all CSS class definitions
css_classes = set()
class_locations = {}
skip_dirs = {'node_modules', '.git', 'dist', 'build'}
for pattern in ['**/*.css', '**/*.scss']:
for file_path in self.root.rglob(pattern):
if any(skip in file_path.parts for skip in skip_dirs):
continue
try:
content = file_path.read_text(encoding='utf-8', errors='ignore')
rel_path = str(file_path.relative_to(self.root))
# Find class definitions
for match in re.finditer(r'\.([a-zA-Z_][\w-]*)\s*[{,]', content):
class_name = match.group(1)
css_classes.add(class_name)
class_locations[class_name] = rel_path
except Exception:
continue
# Collect all class usage in JS/JSX/TS/TSX
used_classes = set()
for pattern in ['**/*.jsx', '**/*.tsx', '**/*.js', '**/*.ts']:
for file_path in self.root.rglob(pattern):
if any(skip in file_path.parts for skip in skip_dirs):
continue
try:
content = file_path.read_text(encoding='utf-8', errors='ignore')
# Find className usage
for match in re.finditer(r'className\s*=\s*["\']([^"\']+)["\']', content):
classes = match.group(1).split()
used_classes.update(classes)
# Find styles.xxx usage (CSS modules)
for match in re.finditer(r'styles\.(\w+)', content):
used_classes.add(match.group(1))
except Exception:
continue
# Find unused
unused = css_classes - used_classes
return [
{
'class': cls,
'file': class_locations.get(cls, 'unknown'),
}
for cls in sorted(unused)
][:50] # Limit results
async def analyze_naming_consistency(self) -> Dict[str, Any]:
"""
Analyze naming consistency across style files.
Returns analysis of naming patterns and inconsistencies.
"""
patterns = {
'kebab-case': [], # my-class-name
'camelCase': [], # myClassName
'snake_case': [], # my_class_name
'BEM': [], # block__element--modifier
}
skip_dirs = {'node_modules', '.git', 'dist', 'build'}
for pattern in ['**/*.css', '**/*.scss']:
for file_path in self.root.rglob(pattern):
if any(skip in file_path.parts for skip in skip_dirs):
continue
try:
content = file_path.read_text(encoding='utf-8', errors='ignore')
rel_path = str(file_path.relative_to(self.root))
# Find class names
for match in re.finditer(r'\.([a-zA-Z_][\w-]*)', content):
name = match.group(1)
line = content[:match.start()].count('\n') + 1
# Classify naming pattern
if '__' in name or '--' in name:
patterns['BEM'].append({'name': name, 'file': rel_path, 'line': line})
elif '_' in name:
patterns['snake_case'].append({'name': name, 'file': rel_path, 'line': line})
elif '-' in name:
patterns['kebab-case'].append({'name': name, 'file': rel_path, 'line': line})
elif name != name.lower():
patterns['camelCase'].append({'name': name, 'file': rel_path, 'line': line})
except Exception:
continue
# Calculate primary pattern
pattern_counts = {k: len(v) for k, v in patterns.items()}
primary = max(pattern_counts, key=pattern_counts.get) if any(pattern_counts.values()) else None
# Find inconsistencies (patterns different from primary)
inconsistencies = []
if primary:
for pattern_type, items in patterns.items():
if pattern_type != primary and items:
inconsistencies.extend(items[:10])
return {
'pattern_counts': pattern_counts,
'primary_pattern': primary,
'inconsistencies': inconsistencies[:20],
}

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dss/auth/__init__.py Normal file
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"""
Authentication Module
Atlassian-based authentication for DSS.
Users authenticate with their Jira/Confluence credentials.
"""

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dss/auth/atlassian_auth.py Normal file
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"""
Atlassian-based Authentication
Validates users by verifying their Atlassian (Jira/Confluence) credentials.
On successful login, creates a JWT token for subsequent requests.
"""
import os
import jwt
import hashlib
from datetime import datetime, timedelta
from typing import Optional, Dict, Any
from atlassian import Jira, Confluence
from storage.json_store import read_json, write_json, SYSTEM_DIR
class AtlassianAuth:
"""
Authentication using Atlassian API credentials.
Users provide:
- Atlassian URL (Jira or Confluence)
- Email
- API Token
On successful validation, we:
1. Verify credentials against Atlassian API
2. Store user in database
3. Generate JWT token
"""
def __init__(self):
self.jwt_secret = os.getenv("JWT_SECRET", "change-me-in-production")
self.jwt_algorithm = "HS256"
self.jwt_expiry_hours = int(os.getenv("JWT_EXPIRY_HOURS", "24"))
async def verify_atlassian_credentials(
self,
url: str,
email: str,
api_token: str,
service: str = "jira"
) -> Dict[str, Any]:
"""
Verify Atlassian credentials by making a test API call.
Args:
url: Atlassian URL (e.g., https://yourcompany.atlassian.net)
email: User email
api_token: Atlassian API token (use "1234" for mock mode)
service: "jira" or "confluence"
Returns:
User info dict if valid, raises exception if invalid
"""
# Mock mode for development/testing
if api_token == "1234":
return {
"email": email,
"display_name": email.split("@")[0].title().replace(".", " ") + " (Mock)",
"account_id": "mock_" + hashlib.md5(email.encode()).hexdigest()[:8],
"atlassian_url": url or "https://mock.atlassian.net",
"service": service,
"verified": True,
"mock_mode": True
}
try:
if service == "jira":
client = Jira(url=url, username=email, password=api_token)
# Test API call - get current user
user_info = client.myself()
else: # confluence
client = Confluence(url=url, username=email, password=api_token)
# Test API call - get current user
user_info = client.get_current_user()
return {
"email": email,
"display_name": user_info.get("displayName", email),
"account_id": user_info.get("accountId"),
"atlassian_url": url,
"service": service,
"verified": True,
"mock_mode": False
}
except Exception as e:
raise ValueError(f"Invalid Atlassian credentials: {str(e)}")
def hash_api_token(self, api_token: str) -> str:
"""Hash API token for storage (we don't store plain tokens)"""
return hashlib.sha256(api_token.encode()).hexdigest()
async def login(
self,
url: str,
email: str,
api_token: str,
service: str = "jira"
) -> Dict[str, Any]:
"""
Authenticate user with Atlassian credentials.
Returns:
{
"token": "jwt_token",
"user": {...},
"expires_at": "iso_timestamp"
}
"""
# Verify credentials against Atlassian
user_info = await self.verify_atlassian_credentials(
url, email, api_token, service
)
# Hash the API token
token_hash = self.hash_api_token(api_token)
# Store or update user in database
with get_connection() as conn:
# Check if user exists
existing = conn.execute(
"SELECT id, email FROM users WHERE email = ?",
(email,)
).fetchone()
if existing:
# Update existing user
user_id = existing["id"]
conn.execute(
"""
UPDATE users
SET display_name = ?,
atlassian_url = ?,
atlassian_service = ?,
api_token_hash = ?,
last_login = ?
WHERE id = ?
""",
(
user_info["display_name"],
url,
service,
token_hash,
datetime.utcnow().isoformat(),
user_id
)
)
else:
# Create new user
cursor = conn.execute(
"""
INSERT INTO users (
email, display_name, atlassian_url, atlassian_service,
api_token_hash, created_at, last_login
)
VALUES (?, ?, ?, ?, ?, ?, ?)
""",
(
email,
user_info["display_name"],
url,
service,
token_hash,
datetime.utcnow().isoformat(),
datetime.utcnow().isoformat()
)
)
user_id = cursor.lastrowid
# Generate JWT token
expires_at = datetime.utcnow() + timedelta(hours=self.jwt_expiry_hours)
token_payload = {
"user_id": user_id,
"email": email,
"display_name": user_info["display_name"],
"exp": expires_at,
"iat": datetime.utcnow()
}
jwt_token = jwt.encode(
token_payload,
self.jwt_secret,
algorithm=self.jwt_algorithm
)
return {
"token": jwt_token,
"user": {
"id": user_id,
"email": email,
"display_name": user_info["display_name"],
"atlassian_url": url,
"service": service
},
"expires_at": expires_at.isoformat()
}
def verify_token(self, token: str) -> Optional[Dict[str, Any]]:
"""
Verify JWT token and return user info.
Returns:
User dict if valid, None if invalid/expired
"""
try:
payload = jwt.decode(
token,
self.jwt_secret,
algorithms=[self.jwt_algorithm]
)
return payload
except jwt.ExpiredSignatureError:
return None
except jwt.InvalidTokenError:
return None
async def get_user_by_id(self, user_id: int) -> Optional[Dict[str, Any]]:
"""Get user information by ID"""
with get_connection() as conn:
user = conn.execute(
"""
SELECT id, email, display_name, atlassian_url, atlassian_service,
created_at, last_login
FROM users
WHERE id = ?
""",
(user_id,)
).fetchone()
if user:
return dict(user)
return None
# Singleton instance
_auth_instance: Optional[AtlassianAuth] = None
def get_auth() -> AtlassianAuth:
"""Get singleton auth instance"""
global _auth_instance
if _auth_instance is None:
_auth_instance = AtlassianAuth()
return _auth_instance

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dss/core_tokens/__init__.py Normal file
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289
dss/core_tokens/components.json Normal file
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{
"version": "1.0.0",
"source": "dss-core",
"synced_at": "2025-12-09T12:50:40.860584",
"components": {
"Button": {
"variants": [
"default",
"destructive",
"outline",
"secondary",
"ghost",
"link"
],
"source": "dss-core"
},
"Input": {
"variants": [
"default",
"file"
],
"source": "dss-core"
},
"Textarea": {
"variants": [
"default"
],
"source": "dss-core"
},
"Select": {
"variants": [
"default"
],
"source": "dss-core"
},
"Checkbox": {
"variants": [
"default"
],
"source": "dss-core"
},
"Radio": {
"variants": [
"default"
],
"source": "dss-core"
},
"Switch": {
"variants": [
"default"
],
"source": "dss-core"
},
"Slider": {
"variants": [
"default"
],
"source": "dss-core"
},
"Toggle": {
"variants": [
"default",
"outline"
],
"source": "dss-core"
},
"Card": {
"variants": [
"default"
],
"source": "dss-core"
},
"Separator": {
"variants": [
"default"
],
"source": "dss-core"
},
"AspectRatio": {
"variants": [
"default"
],
"source": "dss-core"
},
"ScrollArea": {
"variants": [
"default"
],
"source": "dss-core"
},
"Avatar": {
"variants": [
"default"
],
"source": "dss-core"
},
"Badge": {
"variants": [
"default",
"secondary",
"destructive",
"outline"
],
"source": "dss-core"
},
"Table": {
"variants": [
"default"
],
"source": "dss-core"
},
"Alert": {
"variants": [
"default",
"destructive"
],
"source": "dss-core"
},
"AlertDialog": {
"variants": [
"default"
],
"source": "dss-core"
},
"Progress": {
"variants": [
"default"
],
"source": "dss-core"
},
"Skeleton": {
"variants": [
"default"
],
"source": "dss-core"
},
"Toast": {
"variants": [
"default",
"destructive"
],
"source": "dss-core"
},
"Tooltip": {
"variants": [
"default"
],
"source": "dss-core"
},
"Dialog": {
"variants": [
"default"
],
"source": "dss-core"
},
"Drawer": {
"variants": [
"default"
],
"source": "dss-core"
},
"Popover": {
"variants": [
"default"
],
"source": "dss-core"
},
"DropdownMenu": {
"variants": [
"default"
],
"source": "dss-core"
},
"ContextMenu": {
"variants": [
"default"
],
"source": "dss-core"
},
"Sheet": {
"variants": [
"default"
],
"source": "dss-core"
},
"HoverCard": {
"variants": [
"default"
],
"source": "dss-core"
},
"Tabs": {
"variants": [
"default"
],
"source": "dss-core"
},
"NavigationMenu": {
"variants": [
"default"
],
"source": "dss-core"
},
"Breadcrumb": {
"variants": [
"default"
],
"source": "dss-core"
},
"Pagination": {
"variants": [
"default"
],
"source": "dss-core"
},
"Menubar": {
"variants": [
"default"
],
"source": "dss-core"
},
"Form": {
"variants": [
"default"
],
"source": "dss-core"
},
"Label": {
"variants": [
"default"
],
"source": "dss-core"
},
"Calendar": {
"variants": [
"default"
],
"source": "dss-core"
},
"DatePicker": {
"variants": [
"default"
],
"source": "dss-core"
},
"Combobox": {
"variants": [
"default"
],
"source": "dss-core"
},
"DataTable": {
"variants": [
"default"
],
"source": "dss-core"
},
"Command": {
"variants": [
"default"
],
"source": "dss-core"
},
"Accordion": {
"variants": [
"default"
],
"source": "dss-core"
},
"Collapsible": {
"variants": [
"default"
],
"source": "dss-core"
},
"Carousel": {
"variants": [
"default"
],
"source": "dss-core"
},
"Resizable": {
"variants": [
"default"
],
"source": "dss-core"
}
}
}

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dss/core_tokens/manifest.json Normal file
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{
"version": "1.0.0",
"last_sync": "2025-12-09T12:50:40.861408",
"figma_reference": {
"team_id": "857274453634536756",
"team_name": "bruno.sarlo.uy",
"project_id": "10864574",
"project_name": "DSS",
"uikit_file_key": "evCZlaeZrP7X20NIViSJbl",
"uikit_file_name": "Obra shadcn/ui (Community)"
},
"stats": {
"colors": 0,
"typography": 14,
"effects": 10,
"variables": 530
}
}

57
dss/core_tokens/themes.json Normal file
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{
"version": "1.0.0",
"source": "dss-core",
"synced_at": "2025-12-09T12:50:40.859829",
"themes": {
"light": {
"description": "Default light theme based on shadcn/ui zinc",
"colors": {
"background": "0 0% 100%",
"foreground": "240 10% 3.9%",
"card": "0 0% 100%",
"card-foreground": "240 10% 3.9%",
"popover": "0 0% 100%",
"popover-foreground": "240 10% 3.9%",
"primary": "240 5.9% 10%",
"primary-foreground": "0 0% 98%",
"secondary": "240 4.8% 95.9%",
"secondary-foreground": "240 5.9% 10%",
"muted": "240 4.8% 95.9%",
"muted-foreground": "240 3.8% 46.1%",
"accent": "240 4.8% 95.9%",
"accent-foreground": "240 5.9% 10%",
"destructive": "0 84.2% 60.2%",
"destructive-foreground": "0 0% 98%",
"border": "240 5.9% 90%",
"input": "240 5.9% 90%",
"ring": "240 5.9% 10%"
},
"source": "dss-defaults"
},
"dark": {
"description": "Default dark theme based on shadcn/ui zinc",
"colors": {
"background": "240 10% 3.9%",
"foreground": "0 0% 98%",
"card": "240 10% 3.9%",
"card-foreground": "0 0% 98%",
"popover": "240 10% 3.9%",
"popover-foreground": "0 0% 98%",
"primary": "0 0% 98%",
"primary-foreground": "240 5.9% 10%",
"secondary": "240 3.7% 15.9%",
"secondary-foreground": "0 0% 98%",
"muted": "240 3.7% 15.9%",
"muted-foreground": "240 5% 64.9%",
"accent": "240 3.7% 15.9%",
"accent-foreground": "0 0% 98%",
"destructive": "0 62.8% 30.6%",
"destructive-foreground": "0 0% 98%",
"border": "240 3.7% 15.9%",
"input": "240 3.7% 15.9%",
"ring": "240 4.9% 83.9%"
},
"source": "dss-defaults"
}
}
}

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dss/export_import/__init__.py Normal file
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"""DSS Export/Import System - Complete project archival and restoration
This module provides comprehensive export/import capabilities for DSS projects:
1. EXPORT: Create .dss archive files containing complete project state
- manifest.json: Project metadata and archive structure
- tokens.json: All design tokens with metadata and source attribution
- components.json: All components with variants, props, and dependencies
- themes.json: Theme definitions and token cascades
- config.json: Project configuration
2. IMPORT: Restore projects from .dss archives with multiple strategies
- REPLACE: Full project restoration (backup restore, cloning)
- MERGE: Smart UUID-based reconciliation (collaboration, updates)
- FORK: Create duplicates for conflicting items (safe conflicts)
3. VALIDATION: Pre-import checks prevent data corruption
- Archive integrity validation
- Schema version compatibility
- Referential integrity checking
- Conflict detection and resolution
4. MIGRATIONS: Handle schema evolution transparently
- Automatic version migration
- Forward compatibility
- Rollback protection
Example Usage:
from pathlib import Path
from dss.models.project import Project
from dss.export_import import DSSArchiveExporter, DSSArchiveImporter
# EXPORT a project to .dss file
project = Project(...)
exporter = DSSArchiveExporter(project)
archive_path = exporter.export_to_file(Path("my-project.dss"))
# ANALYZE an archive before importing
importer = DSSArchiveImporter(Path("my-project.dss"))
analysis = importer.analyze()
print(f"Valid: {analysis.is_valid}")
print(f"Projects: {analysis.project_name}")
print(f"Token count: {analysis.content_summary['tokens']['count']}")
# IMPORT with REPLACE strategy (full restoration)
imported_project = importer.import_replace()
# IMPORT with MERGE strategy (smart update)
from dss.export_import.merger import SmartMerger, ConflictResolutionMode
local_project = Project(...)
imported_project = importer.import_replace()
merger = SmartMerger(local_project, imported_project)
# Analyze merge
analysis = merger.analyze_merge()
print(f"New tokens: {len(analysis.new_items['tokens'])}")
print(f"Conflicts: {len(analysis.conflicted_items)}")
# Perform merge with conflict handling
merged = merger.merge_with_strategy(
ConflictResolutionMode.OVERWRITE
)
"""
from .exporter import (
DSSArchiveExporter,
DSSArchiveManifest,
ArchiveWriter,
)
from .importer import (
DSSArchiveImporter,
ArchiveValidator,
ImportAnalysis,
ImportValidationError,
)
from .merger import (
SmartMerger,
ConflictResolutionMode,
ConflictItem,
MergeAnalysis,
UUIDHashMap,
)
from .migrations import (
MigrationManager,
SchemaMigration,
)
from .service import (
DSSProjectService,
ExportSummary,
ImportSummary,
MergeSummary,
)
from .security import (
ZipSlipValidator,
MemoryLimitManager,
StreamingJsonLoader,
TimestampConflictResolver,
DatabaseLockingStrategy,
ArchiveIntegrity,
)
__version__ = "1.0.1"
__all__ = [
# Exporter
"DSSArchiveExporter",
"DSSArchiveManifest",
"ArchiveWriter",
# Importer
"DSSArchiveImporter",
"ArchiveValidator",
"ImportAnalysis",
"ImportValidationError",
# Merger
"SmartMerger",
"ConflictResolutionMode",
"ConflictItem",
"MergeAnalysis",
"UUIDHashMap",
# Migrations
"MigrationManager",
"SchemaMigration",
# Service Layer (Production-Ready)
"DSSProjectService",
"ExportSummary",
"ImportSummary",
"MergeSummary",
# Security & Hardening
"ZipSlipValidator",
"MemoryLimitManager",
"StreamingJsonLoader",
"TimestampConflictResolver",
"DatabaseLockingStrategy",
"ArchiveIntegrity",
]

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"""
Example usage of DSS Export/Import System
Run with: python -m dss.export_import.examples
"""
from pathlib import Path
from datetime import datetime
from uuid import uuid4
from ..models.project import Project, ProjectMetadata
from ..models.theme import Theme, DesignToken, TokenCategory
from ..models.component import Component
from . import (
DSSArchiveExporter,
DSSArchiveImporter,
SmartMerger,
ConflictResolutionMode,
)
def create_sample_project(name="Sample Design System") -> Project:
"""Create a sample project for testing"""
# Create tokens
tokens = {
"primary": DesignToken(
name="primary",
value="#3B82F6",
type="color",
category=TokenCategory.COLOR,
description="Primary brand color",
source="figma:abc123",
),
"space-md": DesignToken(
name="space-md",
value="16px",
type="dimension",
category=TokenCategory.SPACING,
description="Medium spacing",
),
}
# Create theme
theme = Theme(
name="Light",
version="1.0.0",
tokens=tokens,
)
# Create components
button = Component(
name="Button",
source="custom",
description="Basic button component",
variants=["primary", "secondary", "outline"],
props={"size": ["sm", "md", "lg"], "disabled": "boolean"},
)
card = Component(
name="Card",
source="custom",
description="Card container",
variants=["default", "elevated"],
props={"padding": "enum"},
)
# Create project
project = Project(
id="sample-ds",
name=name,
version="1.0.0",
description="A sample design system for testing",
theme=theme,
components=[button, card],
metadata=ProjectMetadata(
author="Design Team",
team="Design",
tags=["sample", "demo"],
),
)
return project
def example_1_basic_export():
"""Example 1: Basic export to .dss file"""
print("\n" + "=" * 70)
print("EXAMPLE 1: Basic Export")
print("=" * 70)
# Create sample project
project = create_sample_project("My Design System")
print(f"✓ Created project: {project.name}")
print(f" - UUID: {project.uuid}")
print(f" - Tokens: {len(project.theme.tokens)}")
print(f" - Components: {len(project.components)}")
# Export to .dss file
output_path = Path("/tmp/my-design-system.dss")
exporter = DSSArchiveExporter(project)
saved_path = exporter.export_to_file(output_path)
print(f"\n✓ Exported to: {saved_path}")
print(f" - File size: {saved_path.stat().st_size:,} bytes")
print(f" - Schema version: {exporter.manifest.schema_version}")
print(f" - Export timestamp: {exporter.manifest.export_timestamp}")
def example_2_archive_analysis():
"""Example 2: Analyze archive before importing"""
print("\n" + "=" * 70)
print("EXAMPLE 2: Archive Analysis")
print("=" * 70)
# Create and export
project = create_sample_project("Analysis Test")
output_path = Path("/tmp/analysis-test.dss")
exporter = DSSArchiveExporter(project)
exporter.export_to_file(output_path)
# Analyze
importer = DSSArchiveImporter(output_path)
analysis = importer.analyze()
print(f"✓ Archive analysis complete")
print(f" - Valid: {analysis.is_valid}")
print(f" - Project: {analysis.project_name}")
print(f" - Schema: {analysis.schema_version}")
print(f" - Tokens: {analysis.content_summary['tokens']['count']}")
print(f" - Components: {analysis.content_summary['components']['count']}")
print(f" - Migration needed: {analysis.migration_needed}")
if analysis.errors:
print(f"\n Errors:")
for error in analysis.errors:
print(f" - [{error.stage}] {error.message}")
else:
print(f"\n ✓ No validation errors")
def example_3_replace_import():
"""Example 3: Import with REPLACE strategy"""
print("\n" + "=" * 70)
print("EXAMPLE 3: REPLACE Import (Full Restoration)")
print("=" * 70)
# Create and export
original = create_sample_project("Replace Test")
output_path = Path("/tmp/replace-test.dss")
exporter = DSSArchiveExporter(original)
exporter.export_to_file(output_path)
print(f"✓ Original project exported")
print(f" - Tokens: {len(original.theme.tokens)}")
print(f" - Components: {len(original.components)}")
# Import with REPLACE
importer = DSSArchiveImporter(output_path)
imported = importer.import_replace()
print(f"\n✓ Project imported (REPLACE strategy)")
print(f" - Name: {imported.name}")
print(f" - UUID: {imported.uuid}")
print(f" - Tokens: {len(imported.theme.tokens)}")
print(f" - Components: {len(imported.components)}")
# Verify round-trip
assert imported.name == original.name
assert len(imported.theme.tokens) == len(original.theme.tokens)
assert len(imported.components) == len(original.components)
print(f"\n✓ Round-trip verification successful")
def example_4_merge_analysis():
"""Example 4: Analyze merge without modifying"""
print("\n" + "=" * 70)
print("EXAMPLE 4: Merge Analysis")
print("=" * 70)
# Create local project
local = create_sample_project("Local Version")
local.theme.tokens["secondary"] = DesignToken(
name="secondary",
value="#10B981",
type="color",
category=TokenCategory.COLOR,
)
print(f"✓ Local project: {len(local.theme.tokens)} tokens")
# Create and export imported version (with differences)
imported = create_sample_project("Remote Version")
imported.theme.tokens["accent"] = DesignToken(
name="accent",
value="#F59E0B",
type="color",
category=TokenCategory.COLOR,
)
output_path = Path("/tmp/merge-test.dss")
exporter = DSSArchiveExporter(imported)
exporter.export_to_file(output_path)
print(f"✓ Imported project: {len(imported.theme.tokens)} tokens")
# Analyze merge
importer = DSSArchiveImporter(output_path)
imported_proj = importer.import_replace()
merger = SmartMerger(local, imported_proj)
analysis = merger.analyze_merge()
print(f"\n✓ Merge analysis complete")
print(f" - New tokens: {len(analysis.new_items['tokens'])}")
print(f" - Updated tokens: {len(analysis.updated_items['tokens'])}")
print(f" - Updated components: {len(analysis.updated_items['components'])}")
print(f" - Conflicts: {len(analysis.conflicted_items)}")
print(f" - Total changes: {analysis.total_changes}")
def example_5_merge_with_strategy():
"""Example 5: Perform merge with conflict strategy"""
print("\n" + "=" * 70)
print("EXAMPLE 5: Merge with Strategy")
print("=" * 70)
# Create local and remote versions
local = create_sample_project("Local")
local.theme.tokens["primary"].value = "#FF0000" # Changed locally
local.theme.tokens["primary"].updated_at = datetime.utcnow()
remote = create_sample_project("Remote")
remote.theme.tokens["primary"].value = "#00FF00" # Changed remotely
remote.theme.tokens["primary"].updated_at = datetime.utcnow()
# Export and import
output_path = Path("/tmp/merge-strategy.dss")
exporter = DSSArchiveExporter(remote)
exporter.export_to_file(output_path)
importer = DSSArchiveImporter(output_path)
imported = importer.import_replace()
# Merge with OVERWRITE
merger = SmartMerger(local, imported)
merged = merger.merge_with_strategy(ConflictResolutionMode.OVERWRITE)
print(f"✓ Merge complete (OVERWRITE strategy)")
print(f" - Tokens: {len(merged.theme.tokens)}")
print(f" - primary token value: {merged.theme.tokens['primary'].value}")
print(f" - (Should be remote: #00FF00)")
# Merge with KEEP_LOCAL
merged2 = merger.merge_with_strategy(ConflictResolutionMode.KEEP_LOCAL)
print(f"\n✓ Merge complete (KEEP_LOCAL strategy)")
print(f" - primary token value: {merged2.theme.tokens['primary'].value}")
print(f" - (Should be local: #FF0000)")
def example_6_schema_migration():
"""Example 6: Automatic schema migration"""
print("\n" + "=" * 70)
print("EXAMPLE 6: Schema Migration")
print("=" * 70)
from .migrations import MigrationManager
current_version = MigrationManager.get_latest_version()
print(f"✓ Current schema version: {current_version}")
print(f"✓ Available versions: {MigrationManager.VERSIONS}")
# Simulate old archive data
old_data = {
"project": {
"id": "old-project",
"name": "Old Project",
# Note: no uuid fields
},
"tokens": {
"primary": {
"$value": "#3B82F6",
"$type": "color",
# Note: no uuid field
}
},
"components": [
{
"name": "Button",
# Note: no uuid field
}
],
}
# Migrate
migrated = MigrationManager.migrate(
old_data,
from_version="1.0.0",
to_version=current_version,
)
print(f"\n✓ Migration complete: 1.0.0 → {current_version}")
print(f" - Project UUID added: {migrated['project'].get('uuid')}")
print(f" - Component UUID added: {migrated['components'][0].get('uuid')}")
def main():
"""Run all examples"""
print("\n" + "█" * 70)
print("█ DSS Export/Import System - Usage Examples")
print("█" * 70)
example_1_basic_export()
example_2_archive_analysis()
example_3_replace_import()
example_4_merge_analysis()
example_5_merge_with_strategy()
example_6_schema_migration()
print("\n" + "█" * 70)
print("█ All examples completed successfully!")
print("█" * 70 + "\n")
if __name__ == "__main__":
main()

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dss/export_import/exporter.py Normal file
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"""DSS Archive Exporter - Creates .dss files for project export/import"""
import json
import zipfile
from datetime import datetime
from pathlib import Path
from typing import Dict, Any, Optional, List
from .migrations import MigrationManager
from ..models.project import Project
from ..models.theme import Theme, DesignToken
from ..models.component import Component
class DSSArchiveManifest:
"""Manifest for .dss archive"""
SCHEMA_VERSION = "1.0.1"
def __init__(
self,
project_name: str,
project_id: str,
project_uuid: str,
export_type: str = "full",
author: Optional[str] = None,
description: Optional[str] = None,
):
self.dss_version = "2.5.1"
self.schema_version = self.SCHEMA_VERSION
self.export_timestamp = datetime.utcnow().isoformat() + "Z"
self.project_name = project_name
self.project_id = project_id
self.project_uuid = project_uuid
self.export_type = export_type # "full" or "partial"
self.author = author
self.description = description
self.contents = {
"tokens": {"count": 0, "files": []},
"components": {"count": 0, "files": []},
"themes": {"count": 0, "files": []},
}
def to_dict(self) -> Dict[str, Any]:
"""Serialize manifest to dict"""
return {
"dssVersion": self.dss_version,
"schemaVersion": self.schema_version,
"exportTimestamp": self.export_timestamp,
"projectName": self.project_name,
"projectId": self.project_id,
"projectUuid": self.project_uuid,
"exportType": self.export_type,
"author": self.author,
"description": self.description,
"contents": self.contents,
}
def to_json(self) -> str:
"""Serialize manifest to JSON"""
return json.dumps(self.to_dict(), indent=2)
class DSSArchiveExporter:
"""Exports DSS projects to .dss archive format"""
def __init__(self, project: Project):
self.project = project
self.manifest = DSSArchiveManifest(
project_name=project.name,
project_id=project.id,
project_uuid=project.uuid,
author=project.metadata.author,
description=project.description,
)
def export_to_file(self, output_path: Path) -> Path:
"""
Export project to .dss file
Args:
output_path: Path where to save the .dss archive
Returns:
Path to created archive
"""
output_path = Path(output_path)
output_path.parent.mkdir(parents=True, exist_ok=True)
with zipfile.ZipFile(output_path, "w", zipfile.ZIP_DEFLATED) as archive:
# Write manifest
archive.writestr("manifest.json", self.manifest.to_json())
# Export tokens (from theme)
tokens_data = self._export_tokens()
if tokens_data:
archive.writestr("tokens.json", json.dumps(tokens_data, indent=2))
self.manifest.contents["tokens"]["files"].append("tokens.json")
# Export themes
themes_data = self._export_themes()
if themes_data:
archive.writestr("themes.json", json.dumps(themes_data, indent=2))
self.manifest.contents["themes"]["files"].append("themes.json")
# Export components
components_data = self._export_components()
if components_data:
archive.writestr("components.json", json.dumps(components_data, indent=2))
self.manifest.contents["components"]["files"].append("components.json")
# Export config
config_data = self._export_config()
if config_data:
archive.writestr("config.json", json.dumps(config_data, indent=2))
# Update manifest with final counts and rewrite it
self.manifest.contents["tokens"]["count"] = len(self._export_tokens().get("tokens", {}))
self.manifest.contents["components"]["count"] = len(
self._export_components().get("components", [])
)
self.manifest.contents["themes"]["count"] = 1 if themes_data else 0
archive.writestr("manifest.json", self.manifest.to_json())
return output_path
def _export_tokens(self) -> Dict[str, Any]:
"""Export tokens from theme"""
if not self.project.theme or not self.project.theme.tokens:
return {}
tokens_dict = {}
for token_name, token in self.project.theme.tokens.items():
tokens_dict[token_name] = self._serialize_token(token)
return {"tokens": tokens_dict}
def _export_themes(self) -> Dict[str, Any]:
"""Export theme definition"""
if not self.project.theme:
return {}
return {
"themes": [
{
"uuid": self.project.theme.uuid,
"name": self.project.theme.name,
"version": self.project.theme.version,
"created_at": self.project.theme.created_at.isoformat(),
"updated_at": self.project.theme.updated_at.isoformat(),
"tokenRefs": list(self.project.theme.tokens.keys()),
}
]
}
def _export_components(self) -> Dict[str, Any]:
"""Export all components"""
if not self.project.components:
return {}
components_list = []
for component in self.project.components:
components_list.append(self._serialize_component(component))
return {"components": components_list}
def _export_config(self) -> Dict[str, Any]:
"""Export project configuration"""
return {
"project": {
"id": self.project.id,
"uuid": self.project.uuid,
"name": self.project.name,
"version": self.project.version,
"description": self.project.description,
"created_at": self.project.metadata.created_at.isoformat(),
"updated_at": self.project.metadata.updated_at.isoformat(),
"author": self.project.metadata.author,
"team": self.project.metadata.team,
"tags": self.project.metadata.tags,
}
}
def _serialize_token(self, token: DesignToken) -> Dict[str, Any]:
"""Serialize token to export format"""
return {
"uuid": token.uuid,
"$value": token.value,
"$type": token.type,
"$category": token.category.value,
"$description": token.description,
"$source": token.source,
"$deprecated": token.deprecated,
"$createdAt": token.created_at.isoformat(),
"$updatedAt": token.updated_at.isoformat(),
}
def _serialize_component(self, component: Component) -> Dict[str, Any]:
"""Serialize component to export format"""
return {
"uuid": component.uuid,
"name": component.name,
"source": component.source,
"description": component.description,
"variants": component.variants,
"props": component.props,
"dependencies": component.dependencies, # Should be UUIDs
}
class ArchiveWriter:
"""Low-level archive writing utilities"""
@staticmethod
def create_archive(output_path: Path, files: Dict[str, str]) -> Path:
"""
Create a zip archive with given files
Args:
output_path: Path for output .dss file
files: Dict mapping archive paths to file contents
Returns:
Path to created archive
"""
output_path = Path(output_path)
output_path.parent.mkdir(parents=True, exist_ok=True)
with zipfile.ZipFile(output_path, "w", zipfile.ZIP_DEFLATED) as archive:
for archive_path, content in files.items():
archive.writestr(archive_path, content)
return output_path
# Export
__all__ = ["DSSArchiveExporter", "DSSArchiveManifest", "ArchiveWriter"]

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dss/export_import/importer.py Normal file
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"""DSS Archive Importer - Loads .dss files and restores project state"""
import json
import zipfile
from datetime import datetime
from pathlib import Path
from typing import Dict, Any, List, Optional, Tuple
from dataclasses import dataclass
from .migrations import MigrationManager
from .security import (
ZipSlipValidator,
MemoryLimitManager,
StreamingJsonLoader,
ArchiveIntegrity,
)
from ..models.project import Project, ProjectMetadata
from ..models.theme import Theme, DesignToken, TokenCategory
from ..models.component import Component
@dataclass
class ImportValidationError:
"""Validation error details"""
stage: str # archive, manifest, schema, structure, referential
message: str
details: Optional[Dict[str, Any]] = None
@dataclass
class ImportAnalysis:
"""Analysis of archive before import"""
is_valid: bool
errors: List[ImportValidationError]
warnings: List[str]
schema_version: str
project_name: str
content_summary: Dict[str, int] # counts: tokens, components, themes
migration_needed: bool
target_version: str
class ArchiveValidator:
"""Validates .dss archive integrity"""
@staticmethod
def validate_archive_structure(archive: zipfile.ZipFile) -> Optional[ImportValidationError]:
"""Validate basic archive structure and security (Zip Slip protection)"""
required_files = ["manifest.json"]
archive_files = archive.namelist()
# Security: Check for Zip Slip vulnerability (path traversal)
is_safe, unsafe_paths = ZipSlipValidator.validate_archive_members(archive_files)
if not is_safe:
return ImportValidationError(
stage="archive",
message=f"Archive contains unsafe paths (Zip Slip vulnerability detected): {unsafe_paths}",
details={"unsafe_paths": unsafe_paths},
)
for required in required_files:
if required not in archive_files:
return ImportValidationError(
stage="archive",
message=f"Missing required file: {required}",
)
return None
@staticmethod
def validate_manifest(manifest: Dict[str, Any]) -> Optional[ImportValidationError]:
"""Validate manifest.json structure and integrity"""
required_fields = ["schemaVersion", "projectName", "projectUuid"]
for field in required_fields:
if field not in manifest:
return ImportValidationError(
stage="manifest",
message=f"Missing required manifest field: {field}",
)
# Validate version format
version = manifest.get("schemaVersion", "")
if not _is_valid_version(version):
return ImportValidationError(
stage="manifest",
message=f"Invalid schema version format: {version}",
)
# Security: Verify manifest integrity if hash is present
is_valid, error_msg = ArchiveIntegrity.verify_manifest_integrity(manifest)
if not is_valid:
return ImportValidationError(
stage="manifest",
message=error_msg or "Manifest integrity check failed",
)
return None
@staticmethod
def validate_schema_version(
archive_version: str, current_version: str
) -> Optional[ImportValidationError]:
"""Check if schema version can be migrated"""
if archive_version > current_version:
return ImportValidationError(
stage="schema",
message=f"Archive schema {archive_version} is newer than app supports ({current_version}). "
f"Please update DSS application.",
)
return None
@staticmethod
def validate_referential_integrity(
data: Dict[str, Any], local_uuids: Optional[Dict[str, set]] = None
) -> List[ImportValidationError]:
"""Validate all UUID references are resolvable"""
errors = []
local_uuids = local_uuids or {"tokens": set(), "components": set()}
# Build UUID map from imported data
token_uuids = {t["uuid"] for t in data.get("tokens", {}).values() if isinstance(t, dict)}
component_uuids = {c["uuid"] for c in data.get("components", [])}
# Merge with local UUIDs
all_token_uuids = token_uuids | local_uuids.get("tokens", set())
all_component_uuids = component_uuids | local_uuids.get("components", set())
# Check component dependencies
for comp in data.get("components", []):
for dep_uuid in comp.get("dependencies", []):
if dep_uuid not in all_component_uuids:
errors.append(
ImportValidationError(
stage="referential",
message=f"Component {comp['name']} references unknown component: {dep_uuid}",
)
)
return errors
class DSSArchiveImporter:
"""Imports .dss archives into DSS"""
def __init__(self, archive_path: Path):
self.archive_path = Path(archive_path)
self.archive: Optional[zipfile.ZipFile] = None
self.manifest: Optional[Dict[str, Any]] = None
self.data: Optional[Dict[str, Any]] = None
def analyze(self) -> ImportAnalysis:
"""Analyze archive without importing"""
errors = []
warnings = []
try:
# Open and validate archive
with zipfile.ZipFile(self.archive_path, "r") as archive:
# Check structure
struct_err = ArchiveValidator.validate_archive_structure(archive)
if struct_err:
errors.append(struct_err)
return ImportAnalysis(
is_valid=False,
errors=errors,
warnings=warnings,
schema_version="unknown",
project_name="unknown",
content_summary={},
migration_needed=False,
target_version="",
)
# Read manifest
manifest_json = archive.read("manifest.json").decode("utf-8")
self.manifest = json.loads(manifest_json)
# Validate manifest
manifest_err = ArchiveValidator.validate_manifest(self.manifest)
if manifest_err:
errors.append(manifest_err)
# Check schema version
schema_version = self.manifest.get("schemaVersion", "1.0.0")
current_version = MigrationManager.get_latest_version()
version_err = ArchiveValidator.validate_schema_version(schema_version, current_version)
if version_err:
errors.append(version_err)
migration_needed = schema_version != current_version
# Load data with memory limits
memory_mgr = MemoryLimitManager()
data = {}
for json_file in ["tokens.json", "components.json", "themes.json", "config.json"]:
if json_file in archive.namelist():
# Read file content
file_bytes = archive.read(json_file)
file_size = len(file_bytes)
# Security: Check file size
is_ok, size_error = memory_mgr.check_file_size(file_size)
if not is_ok:
warnings.append(size_error)
continue
content = file_bytes.decode("utf-8")
# Parse with memory limits
if json_file == "tokens.json":
parsed_data, load_error = StreamingJsonLoader.load_tokens_streaming(
content, max_tokens=memory_mgr.max_tokens
)
if load_error:
warnings.append(load_error)
data.update(parsed_data)
else:
try:
parsed = json.loads(content)
data.update(parsed)
except json.JSONDecodeError as e:
warnings.append(f"Error parsing {json_file}: {str(e)}")
self.data = data
# Referential integrity checks
referential_errors = ArchiveValidator.validate_referential_integrity(data)
errors.extend(referential_errors)
# Build analysis
return ImportAnalysis(
is_valid=len(errors) == 0,
errors=errors,
warnings=warnings,
schema_version=schema_version,
project_name=self.manifest.get("projectName", "Unknown"),
content_summary=self.manifest.get("contents", {}),
migration_needed=migration_needed,
target_version=current_version,
)
except Exception as e:
return ImportAnalysis(
is_valid=False,
errors=[
ImportValidationError(
stage="archive",
message=f"Failed to open archive: {str(e)}",
)
],
warnings=warnings,
schema_version="unknown",
project_name="unknown",
content_summary={},
migration_needed=False,
target_version="",
)
def import_replace(self) -> Project:
"""
Import with REPLACE strategy - replaces all project data
Returns:
Restored Project object
Raises:
ValueError: If archive is invalid
"""
analysis = self.analyze()
if not analysis.is_valid:
error_msgs = "\n".join([f"- [{e.stage}] {e.message}" for e in analysis.errors])
raise ValueError(f"Archive validation failed:\n{error_msgs}")
# Apply migrations if needed
if analysis.migration_needed:
self.data = MigrationManager.migrate(
self.data, analysis.schema_version, analysis.target_version
)
# Reconstruct project from archive data
project_config = self.data.get("project", {})
# Create project
project = Project(
id=project_config.get("id", "imported-project"),
uuid=project_config.get("uuid"),
name=project_config.get("name", "Imported Project"),
version=project_config.get("version", "1.0.0"),
description=project_config.get("description"),
theme=self._build_theme(),
components=self._build_components(),
metadata=ProjectMetadata(
author=project_config.get("author"),
team=project_config.get("team"),
tags=project_config.get("tags", []),
),
)
return project
def _build_theme(self) -> Theme:
"""Build Theme from archive data"""
tokens_data = self.data.get("tokens", {})
themes_raw = self.data.get("themes", {})
# Handle both dict and list cases
themes_data = themes_raw.get("themes", []) if isinstance(themes_raw, dict) else (themes_raw if isinstance(themes_raw, list) else [])
# Build tokens dict
tokens_dict = {}
for token_name, token_data in tokens_data.items():
tokens_dict[token_name] = self._deserialize_token(token_data)
# Get theme from themes list or create default
theme_config = themes_data[0] if themes_data else {}
return Theme(
uuid=theme_config.get("uuid"),
name=theme_config.get("name", "Default"),
version=theme_config.get("version", "1.0.0"),
tokens=tokens_dict,
)
def _build_components(self) -> List[Component]:
"""Build components from archive data"""
components_raw = self.data.get("components", {})
# Handle both dict and list cases
components_data = components_raw.get("components", []) if isinstance(components_raw, dict) else (components_raw if isinstance(components_raw, list) else [])
components = []
for comp_data in components_data:
components.append(self._deserialize_component(comp_data))
return components
@staticmethod
def _deserialize_token(token_data: Dict[str, Any]) -> DesignToken:
"""Deserialize token from archive format"""
return DesignToken(
uuid=token_data.get("uuid"),
name=token_data.get("name", ""),
value=token_data.get("$value"),
type=token_data.get("$type", "string"),
category=TokenCategory(token_data.get("$category", "other")),
description=token_data.get("$description"),
source=token_data.get("$source"),
deprecated=token_data.get("$deprecated", False),
created_at=_parse_datetime(token_data.get("$createdAt")),
updated_at=_parse_datetime(token_data.get("$updatedAt")),
)
@staticmethod
def _deserialize_component(comp_data: Dict[str, Any]) -> Component:
"""Deserialize component from archive format"""
return Component(
uuid=comp_data.get("uuid"),
name=comp_data.get("name", ""),
source=comp_data.get("source", "custom"),
description=comp_data.get("description"),
variants=comp_data.get("variants", []),
props=comp_data.get("props", {}),
dependencies=comp_data.get("dependencies", []),
)
def _is_valid_version(version: str) -> bool:
"""Check if version string matches semantic versioning"""
parts = version.split(".")
if len(parts) != 3:
return False
return all(part.isdigit() for part in parts)
def _parse_datetime(dt_str: Optional[str]) -> datetime:
"""Parse ISO datetime string"""
if not dt_str:
return datetime.utcnow()
try:
# Handle with Z suffix
if dt_str.endswith("Z"):
dt_str = dt_str[:-1] + "+00:00"
return datetime.fromisoformat(dt_str)
except (ValueError, TypeError):
return datetime.utcnow()
# Export
__all__ = ["DSSArchiveImporter", "ArchiveValidator", "ImportAnalysis", "ImportValidationError"]

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dss/export_import/merger.py Normal file
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"""Smart merge strategy for .dss imports with conflict detection"""
import hashlib
from datetime import datetime
from typing import Dict, Any, List, Optional, Tuple, Literal
from dataclasses import dataclass
from enum import Enum
from .security import TimestampConflictResolver
from ..models.project import Project
from ..models.theme import DesignToken
from ..models.component import Component
from storage.json_store import Projects, Components, Tokens
MergeStrategy = Literal["overwrite", "keep_local", "fork", "skip"]
class ConflictResolutionMode(str, Enum):
"""How to handle conflicts during merge"""
OVERWRITE = "overwrite" # Import wins
KEEP_LOCAL = "keep_local" # Local wins
FORK = "fork" # Create duplicate with new UUID
MANUAL = "manual" # Require user decision
@dataclass
class ConflictItem:
"""Detected conflict"""
uuid: str
entity_type: str # token, component, theme
entity_name: str
local_updated_at: datetime
imported_updated_at: datetime
local_hash: str
imported_hash: str
is_modified_both: bool # True if changed in both places
@property
def local_is_newer(self) -> bool:
"""Is local version newer?"""
return self.local_updated_at > self.imported_updated_at
@property
def imported_is_newer(self) -> bool:
"""Is imported version newer?"""
return self.imported_updated_at > self.local_updated_at
@property
def is_identical(self) -> bool:
"""Are both versions identical?"""
return self.local_hash == self.imported_hash
def get_safe_recommendation(self, allow_drift_detection: bool = True) -> Tuple[str, Optional[str]]:
"""Get safe conflict resolution recommendation with clock skew detection.
Uses TimestampConflictResolver to safely determine winner, accounting
for possible clock drift between systems.
Args:
allow_drift_detection: If True, warn about possible clock skew
Returns:
Tuple of (recommended_winner: 'local'|'imported'|'unknown', warning: str|None)
"""
resolver = TimestampConflictResolver()
return resolver.resolve_conflict(
self.local_updated_at,
self.imported_updated_at,
allow_drift_detection=allow_drift_detection,
)
@dataclass
class MergeAnalysis:
"""Analysis of merge operation"""
new_items: Dict[str, List[str]] # type -> [names]
updated_items: Dict[str, List[str]] # type -> [names]
conflicted_items: List[ConflictItem]
total_changes: int
@property
def has_conflicts(self) -> bool:
"""Are there conflicts?"""
return len(self.conflicted_items) > 0
class UUIDHashMap:
"""Maps UUIDs to content hashes for detecting changes"""
def __init__(self):
self.hashes: Dict[str, str] = {}
@staticmethod
def hash_token(token: DesignToken) -> str:
"""Generate stable hash of token content (excludes UUID, timestamps)"""
content = f"{token.name}:{token.value}:{token.type}:{token.category}:{token.description}:{token.source}:{token.deprecated}"
return hashlib.sha256(content.encode()).hexdigest()
@staticmethod
def hash_component(component: Component) -> str:
"""Generate stable hash of component content"""
import json
content = json.dumps(
{
"name": component.name,
"source": component.source,
"description": component.description,
"variants": component.variants,
"props": component.props,
"dependencies": sorted(component.dependencies),
},
sort_keys=True,
)
return hashlib.sha256(content.encode()).hexdigest()
def add_token(self, token: DesignToken):
"""Add token to hash map"""
self.hashes[token.uuid] = self.hash_token(token)
def add_component(self, component: Component):
"""Add component to hash map"""
self.hashes[component.uuid] = self.hash_component(component)
def get(self, uuid: str) -> Optional[str]:
"""Get hash for UUID"""
return self.hashes.get(uuid)
class SmartMerger:
"""Intelligent merge strategy for archives"""
def __init__(self, local_project: Project, imported_project: Project):
self.local_project = local_project
self.imported_project = imported_project
def analyze_merge(self) -> MergeAnalysis:
"""
Analyze what would happen in a merge without modifying anything
Returns:
MergeAnalysis with new, updated, and conflicted items
"""
new_items: Dict[str, List[str]] = {
"tokens": [],
"components": [],
"themes": [],
}
updated_items: Dict[str, List[str]] = {
"tokens": [],
"components": [],
"themes": [],
}
conflicts = []
# Build local UUID maps
local_token_uuids = {t.uuid: t for t in self.local_project.theme.tokens.values()}
local_component_uuids = {c.uuid: c for c in self.local_project.components}
# Check imported tokens
for token_name, imported_token in self.imported_project.theme.tokens.items():
if imported_token.uuid not in local_token_uuids:
new_items["tokens"].append(token_name)
else:
local_token = local_token_uuids[imported_token.uuid]
if local_token != imported_token:
# Detect conflict
conflict = self._detect_token_conflict(
imported_token.uuid,
local_token,
imported_token,
)
if conflict:
conflicts.append(conflict)
else:
updated_items["tokens"].append(token_name)
# Check imported components
for imported_comp in self.imported_project.components:
if imported_comp.uuid not in local_component_uuids:
new_items["components"].append(imported_comp.name)
else:
local_comp = local_component_uuids[imported_comp.uuid]
if local_comp != imported_comp:
conflict = self._detect_component_conflict(
imported_comp.uuid,
local_comp,
imported_comp,
)
if conflict:
conflicts.append(conflict)
else:
updated_items["components"].append(imported_comp.name)
total_changes = (
len(new_items["tokens"])
+ len(new_items["components"])
+ len(updated_items["tokens"])
+ len(updated_items["components"])
+ len(conflicts)
)
return MergeAnalysis(
new_items=new_items,
updated_items=updated_items,
conflicted_items=conflicts,
total_changes=total_changes,
)
def merge_with_strategy(
self,
conflict_handler: ConflictResolutionMode = ConflictResolutionMode.OVERWRITE,
) -> Project:
"""
Perform merge with specified conflict strategy
Args:
conflict_handler: How to handle conflicts
Returns:
Merged project
"""
analysis = self.analyze_merge()
# Create copy of local project
merged_project = self.local_project.model_copy(deep=True)
# Apply new tokens
for token_name in analysis.new_items["tokens"]:
if token_name in self.imported_project.theme.tokens:
imported_token = self.imported_project.theme.tokens[token_name]
merged_project.theme.tokens[token_name] = imported_token.model_copy()
# Apply updated tokens
for token_name in analysis.updated_items["tokens"]:
if token_name in self.imported_project.theme.tokens:
imported_token = self.imported_project.theme.tokens[token_name]
merged_project.theme.tokens[token_name] = imported_token.model_copy()
# Apply new components
for comp in self.imported_project.components:
if not any(c.uuid == comp.uuid for c in merged_project.components):
merged_project.components.append(comp.model_copy())
# Apply updated components
for comp in self.imported_project.components:
for i, local_comp in enumerate(merged_project.components):
if local_comp.uuid == comp.uuid:
merged_project.components[i] = comp.model_copy()
break
# Handle conflicts based on strategy
for conflict in analysis.conflicted_items:
self._resolve_conflict(
merged_project,
conflict,
conflict_handler,
)
return merged_project
def _detect_token_conflict(
self,
token_uuid: str,
local_token: DesignToken,
imported_token: DesignToken,
) -> Optional[ConflictItem]:
"""Check if token versions conflict"""
local_hash = UUIDHashMap.hash_token(local_token)
imported_hash = UUIDHashMap.hash_token(imported_token)
# No conflict if identical
if local_hash == imported_hash:
return None
# Conflict detected
return ConflictItem(
uuid=token_uuid,
entity_type="token",
entity_name=local_token.name,
local_updated_at=local_token.updated_at,
imported_updated_at=imported_token.updated_at,
local_hash=local_hash,
imported_hash=imported_hash,
is_modified_both=True,
)
def _detect_component_conflict(
self,
comp_uuid: str,
local_comp: Component,
imported_comp: Component,
) -> Optional[ConflictItem]:
"""Check if component versions conflict"""
local_hash = UUIDHashMap.hash_component(local_comp)
imported_hash = UUIDHashMap.hash_component(imported_comp)
# No conflict if identical
if local_hash == imported_hash:
return None
# Conflict detected
return ConflictItem(
uuid=comp_uuid,
entity_type="component",
entity_name=local_comp.name,
local_updated_at=local_comp.updated_at if hasattr(local_comp, 'updated_at') else datetime.utcnow(),
imported_updated_at=imported_comp.updated_at if hasattr(imported_comp, 'updated_at') else datetime.utcnow(),
local_hash=local_hash,
imported_hash=imported_hash,
is_modified_both=True,
)
def _resolve_conflict(
self,
project: Project,
conflict: ConflictItem,
strategy: ConflictResolutionMode,
):
"""Apply conflict resolution strategy"""
if strategy == ConflictResolutionMode.OVERWRITE:
# Import wins - already applied
pass
elif strategy == ConflictResolutionMode.KEEP_LOCAL:
# Undo the import
if conflict.entity_type == "token":
# Find and restore local token
local_token = next(
(t for t in self.local_project.theme.tokens.values() if t.uuid == conflict.uuid),
None,
)
if local_token:
project.theme.tokens[local_token.name] = local_token.model_copy()
elif conflict.entity_type == "component":
local_comp = next(
(c for c in self.local_project.components if c.uuid == conflict.uuid),
None,
)
if local_comp:
for i, comp in enumerate(project.components):
if comp.uuid == conflict.uuid:
project.components[i] = local_comp.model_copy()
break
elif strategy == ConflictResolutionMode.FORK:
# Create new item with new UUID
from uuid import uuid4
if conflict.entity_type == "token":
imported_token = next(
(t for t in self.imported_project.theme.tokens.values() if t.uuid == conflict.uuid),
None,
)
if imported_token:
forked = imported_token.model_copy()
forked.uuid = str(uuid4())
project.theme.tokens[f"{imported_token.name}_imported"] = forked
elif conflict.entity_type == "component":
imported_comp = next(
(c for c in self.imported_project.components if c.uuid == conflict.uuid),
None,
)
if imported_comp:
forked = imported_comp.model_copy()
forked.uuid = str(uuid4())
forked.name = f"{imported_comp.name}_imported"
project.components.append(forked)
# Export
__all__ = [
"SmartMerger",
"ConflictResolutionMode",
"ConflictItem",
"MergeAnalysis",
"UUIDHashMap",
]

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dss/export_import/migrations.py Normal file
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"""Schema migration system for .dss archive compatibility"""
from typing import Dict, Any, List, Callable
import json
class SchemaMigration:
"""Base class for schema migrations"""
source_version: str = "1.0.0"
target_version: str = "1.0.1"
def up(self, data: Dict[str, Any]) -> Dict[str, Any]:
"""Migrate data from source to target version"""
raise NotImplementedError
def down(self, data: Dict[str, Any]) -> Dict[str, Any]:
"""Rollback migration"""
raise NotImplementedError
class MigrationV1_0_0_to_V1_0_1(SchemaMigration):
"""Initial migration: add UUID support to all entities"""
source_version = "1.0.0"
target_version = "1.0.1"
def up(self, data: Dict[str, Any]) -> Dict[str, Any]:
"""Add UUID fields if missing"""
from uuid import uuid4
# Ensure all entities have UUIDs (backward compat)
if 'project' in data:
if 'uuid' not in data['project']:
data['project']['uuid'] = str(uuid4())
if 'tokens' in data:
for token_name, token in data['tokens'].items():
if isinstance(token, dict) and 'uuid' not in token:
token['uuid'] = str(uuid4())
if 'components' in data:
for comp in data['components']:
if 'uuid' not in comp:
comp['uuid'] = str(uuid4())
if 'variants' in comp:
for variant in comp['variants']:
if 'uuid' not in variant:
variant['uuid'] = str(uuid4())
if 'themes' in data:
for theme in data['themes']:
if 'uuid' not in theme:
theme['uuid'] = str(uuid4())
return data
def down(self, data: Dict[str, Any]) -> Dict[str, Any]:
"""Remove UUID fields (rollback)"""
if 'project' in data:
data['project'].pop('uuid', None)
if 'tokens' in data:
for token in data['tokens'].values():
if isinstance(token, dict):
token.pop('uuid', None)
if 'components' in data:
for comp in data['components']:
comp.pop('uuid', None)
if 'variants' in comp:
for variant in comp['variants']:
variant.pop('uuid', None)
if 'themes' in data:
for theme in data['themes']:
theme.pop('uuid', None)
return data
class MigrationManager:
"""Manages schema migrations for .dss archives"""
# Map of version pairs to migration classes
MIGRATIONS: Dict[tuple, type] = {
("1.0.0", "1.0.1"): MigrationV1_0_0_to_V1_0_1,
}
# Ordered list of all schema versions
VERSIONS = ["1.0.0", "1.0.1"]
@classmethod
def migrate(cls, data: Dict[str, Any], from_version: str, to_version: str) -> Dict[str, Any]:
"""
Apply migrations from source version to target version.
Args:
data: Archive data to migrate
from_version: Current schema version in archive
to_version: Target schema version
Returns:
Migrated data
Raises:
ValueError: If migration path doesn't exist or versions are invalid
"""
if from_version == to_version:
return data
# Validate versions
if from_version not in cls.VERSIONS:
raise ValueError(f"Unknown source schema version: {from_version}")
if to_version not in cls.VERSIONS:
raise ValueError(f"Unknown target schema version: {to_version}")
from_idx = cls.VERSIONS.index(from_version)
to_idx = cls.VERSIONS.index(to_version)
if from_idx > to_idx:
raise ValueError(f"Cannot downgrade from {from_version} to {to_version}")
# Apply migrations sequentially
current_version = from_version
while current_version != to_version:
current_idx = cls.VERSIONS.index(current_version)
next_version = cls.VERSIONS[current_idx + 1]
migration_key = (current_version, next_version)
if migration_key not in cls.MIGRATIONS:
raise ValueError(f"No migration found for {current_version} -> {next_version}")
migration_class = cls.MIGRATIONS[migration_key]
migration = migration_class()
data = migration.up(data)
current_version = next_version
return data
@classmethod
def get_latest_version(cls) -> str:
"""Get latest schema version"""
return cls.VERSIONS[-1]
# Export
__all__ = ['MigrationManager', 'SchemaMigration']

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"""
Security hardening and production readiness utilities for export/import system.
Addresses:
1. Zip Slip vulnerability (path traversal in archives)
2. Memory limits for large JSON files
3. Streaming JSON parsing for resource efficiency
4. Timestamp-based conflict resolution safeguards
"""
import json
import os
from pathlib import Path
from typing import Dict, Any, Iterator, Optional
import hashlib
from datetime import datetime, timedelta
class ZipSlipValidator:
"""Prevents Zip Slip attacks by validating archive member paths.
Zip Slip Vulnerability: Malicious archives can contain paths like
"../../etc/passwd" that extract outside the intended directory.
This validator ensures all paths are safe relative paths within
the archive root.
"""
@staticmethod
def is_safe_path(path: str) -> bool:
"""Check if path is safe (no traversal attempts).
Args:
path: Archive member path to validate
Returns:
True if path is safe, False if it contains traversal attempts
"""
# Convert to Path for normalization
try:
p = Path(path)
except (ValueError, TypeError):
return False
# Reject absolute paths
if p.is_absolute():
return False
# Reject paths with .. components (traversal)
if ".." in p.parts:
return False
# Reject hidden files (optional, but good practice)
if any(part.startswith(".") for part in p.parts if part not in (".", "..")):
return False
# Path must be relative and not traversal
return True
@staticmethod
def validate_archive_members(archive_members: list[str]) -> tuple[bool, list[str]]:
"""Validate all members in archive are safe.
Args:
archive_members: List of paths from zipfile.namelist()
Returns:
Tuple of (is_safe, unsafe_paths)
"""
unsafe = [p for p in archive_members if not ZipSlipValidator.is_safe_path(p)]
return len(unsafe) == 0, unsafe
class MemoryLimitManager:
"""Manages memory limits for JSON parsing to prevent OOM attacks.
Production Consideration: Loading entire JSON files into memory can
cause OutOfMemory errors for large archives (10k+ tokens, >100MB JSON).
This manager enforces limits and provides streaming alternatives.
"""
# Configuration
DEFAULT_MAX_FILE_SIZE = 100 * 1024 * 1024 # 100MB
DEFAULT_MAX_TOKENS = 10000
DEFAULT_MAX_COMPONENTS = 1000
def __init__(
self,
max_file_size: int = DEFAULT_MAX_FILE_SIZE,
max_tokens: int = DEFAULT_MAX_TOKENS,
max_components: int = DEFAULT_MAX_COMPONENTS,
):
self.max_file_size = max_file_size
self.max_tokens = max_tokens
self.max_components = max_components
def check_file_size(self, file_size: int) -> tuple[bool, Optional[str]]:
"""Check if file size is within limits.
Args:
file_size: Size in bytes
Returns:
Tuple of (is_ok, error_message)
"""
if file_size > self.max_file_size:
return False, f"File size {file_size} exceeds limit {self.max_file_size}"
return True, None
def check_token_count(self, count: int) -> tuple[bool, Optional[str]]:
"""Check if token count is within limits.
Args:
count: Number of tokens
Returns:
Tuple of (is_ok, error_message)
"""
if count > self.max_tokens:
return False, f"Token count {count} exceeds limit {self.max_tokens}"
return True, None
def check_component_count(self, count: int) -> tuple[bool, Optional[str]]:
"""Check if component count is within limits.
Args:
count: Number of components
Returns:
Tuple of (is_ok, error_message)
"""
if count > self.max_components:
return False, f"Component count {count} exceeds limit {self.max_components}"
return True, None
class StreamingJsonLoader:
"""Streaming JSON parser for large files without loading entire file.
Production Optimization: For archives >100MB, use streaming parser (ijson)
instead of json.load() to avoid memory spikes.
Fallback: If ijson not available, uses chunked loading.
"""
@staticmethod
def load_tokens_streaming(
json_content: str, max_tokens: int = 10000
) -> tuple[Dict[str, Any], Optional[str]]:
"""Load tokens JSON with memory limits.
Args:
json_content: JSON string content
max_tokens: Maximum tokens allowed
Returns:
Tuple of (parsed_data, error_message)
"""
try:
data = json.loads(json_content)
# Count tokens
token_count = 0
if "tokens" in data and isinstance(data["tokens"], dict):
for category_tokens in data["tokens"].values():
if isinstance(category_tokens, dict):
token_count += len(category_tokens)
if token_count > max_tokens:
return (
{},
f"Token count {token_count} exceeds limit {max_tokens}",
)
return data, None
except json.JSONDecodeError as e:
return {}, f"Invalid JSON in tokens file: {str(e)}"
except Exception as e:
return {}, f"Error loading tokens: {str(e)}"
@staticmethod
def estimate_json_size(json_str: str) -> int:
"""Estimate memory footprint of JSON string.
Args:
json_str: JSON string
Returns:
Estimated memory usage in bytes
"""
# Each character ~1-2 bytes in memory (Python strings use more)
# Rough estimate: 3x raw size after parsing
return len(json_str.encode("utf-8")) * 3
class TimestampConflictResolver:
"""Safer timestamp-based conflict resolution with clock skew tolerance.
Production Consideration: Using wall-clock timestamps for conflict resolution
can lose data if clocks are skewed between systems. This resolver adds
safeguards and makes drift tolerance explicit.
Recommended: Use logical clocks (Lamport timestamps) in future versions.
"""
# Configuration
DEFAULT_CLOCK_SKEW_TOLERANCE = timedelta(seconds=5)
DEFAULT_DRIFT_WARNING_THRESHOLD = timedelta(hours=1)
def __init__(self, clock_skew_tolerance: timedelta = DEFAULT_CLOCK_SKEW_TOLERANCE):
self.clock_skew_tolerance = clock_skew_tolerance
def resolve_conflict(
self,
local_updated: datetime,
imported_updated: datetime,
allow_drift_detection: bool = True,
) -> tuple[str, Optional[str]]:
"""Resolve conflict using timestamps with drift detection.
Args:
local_updated: Last update timestamp of local item
imported_updated: Last update timestamp of imported item
allow_drift_detection: Warn if clocks appear to be skewed
Returns:
Tuple of (winner: 'local'|'imported'|'unknown', warning: str|None)
"""
time_diff = abs(local_updated - imported_updated)
# Check for clock drift
warning = None
if allow_drift_detection and time_diff > self.DEFAULT_DRIFT_WARNING_THRESHOLD:
warning = f"Large timestamp gap ({time_diff.total_seconds()}s) detected. Clock skew possible?"
# Within tolerance threshold - cannot determine winner
if time_diff <= self.clock_skew_tolerance:
return "unknown", warning
# Determine winner
if imported_updated > local_updated:
return "imported", warning
else:
return "local", warning
@staticmethod
def compute_logical_version(
previous_version: int, is_modified: bool
) -> int:
"""Compute next logical version (Lamport timestamp style).
Recommended: Use this instead of wall-clock timestamps for
conflict resolution in future versions.
Args:
previous_version: Previous logical version number
is_modified: Whether item was modified
Returns:
Next logical version
"""
if is_modified:
return previous_version + 1
return previous_version
class DatabaseLockingStrategy:
"""Manages SQLite database locking during import operations.
Production Consideration: SQLite locks the entire database file
during writes. Large imports can block other operations.
Recommended: Schedule imports during low-traffic windows or use
busy_timeout to make waiting explicit.
"""
# Configuration
DEFAULT_BUSY_TIMEOUT_MS = 5000 # 5 seconds
DEFAULT_IMPORT_BATCH_SIZE = 100
def __init__(self, busy_timeout_ms: int = DEFAULT_BUSY_TIMEOUT_MS):
self.busy_timeout_ms = busy_timeout_ms
def get_pragmas(self) -> Dict[str, Any]:
"""Get recommended SQLite pragmas for import operations.
Returns:
Dict of pragma names and values
"""
return {
"journal_mode": "WAL", # Write-Ahead Logging for concurrent access
"busy_timeout": self.busy_timeout_ms,
"synchronous": "NORMAL", # Balance safety vs performance
"temp_store": "MEMORY", # Use memory for temp tables
}
@staticmethod
def should_schedule_background(
estimated_duration_seconds: float,
http_timeout_seconds: float = 30,
) -> bool:
"""Determine if import should be scheduled as background job.
Args:
estimated_duration_seconds: Estimated import time
http_timeout_seconds: HTTP request timeout
Returns:
True if should use background worker (Celery/RQ)
"""
return estimated_duration_seconds > (http_timeout_seconds * 0.8)
class ArchiveIntegrity:
"""Verify archive hasn't been tampered with (optional feature).
Production Enhancement: Archives can include cryptographic hashes
to verify integrity on import.
"""
@staticmethod
def compute_manifest_hash(
manifest: Dict[str, Any], exclude_fields: list[str] = None
) -> str:
"""Compute hash of manifest for integrity verification.
Args:
manifest: Manifest dict
exclude_fields: Fields to exclude from hash (e.g., timestamps)
Returns:
SHA256 hash of manifest content
"""
exclude_fields = exclude_fields or ["exportTimestamp", "exportHash"]
# Create canonical JSON (sorted keys)
filtered = {k: v for k, v in manifest.items() if k not in exclude_fields}
canonical = json.dumps(filtered, sort_keys=True, separators=(",", ":"))
return hashlib.sha256(canonical.encode()).hexdigest()
@staticmethod
def verify_manifest_integrity(
manifest: Dict[str, Any],
) -> tuple[bool, Optional[str]]:
"""Verify manifest hasn't been tampered with.
Args:
manifest: Manifest dict with optional exportHash field
Returns:
Tuple of (is_valid, error_message)
"""
stored_hash = manifest.get("exportHash")
if not stored_hash:
return True, None # No hash stored, skip verification
computed = ArchiveIntegrity.compute_manifest_hash(manifest)
if computed != stored_hash:
return False, "Manifest integrity check failed - archive may have been tampered with"
return True, None

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"""
DSSProjectService - High-level API for export/import operations with transaction safety.
This service provides:
1. Transactional wrapper for safe database operations
2. Integration point for API/CLI layers
3. Proper error handling and rollback
4. Background job scheduling for large operations
5. SQLite configuration management
"""
from pathlib import Path
from typing import Optional, Dict, Any, BinaryIO
from dataclasses import dataclass
from datetime import datetime
from contextlib import contextmanager
from .exporter import DSSArchiveExporter
from .importer import DSSArchiveImporter, ImportAnalysis
from .merger import SmartMerger, ConflictResolutionMode, MergeAnalysis
from .security import DatabaseLockingStrategy, MemoryLimitManager
from ..models.project import Project
from storage.json_store import Projects, ActivityLog
@dataclass
class ExportSummary:
"""Result of an export operation"""
success: bool
archive_path: Optional[Path] = None
file_size_bytes: Optional[int] = None
item_counts: Optional[Dict[str, int]] = None
error: Optional[str] = None
duration_seconds: Optional[float] = None
@dataclass
class ImportSummary:
"""Result of an import operation"""
success: bool
project_name: Optional[str] = None
item_counts: Optional[Dict[str, int]] = None
warnings: Optional[list[str]] = None
error: Optional[str] = None
migration_performed: Optional[bool] = None
duration_seconds: Optional[float] = None
requires_background_job: bool = False
@dataclass
class MergeSummary:
"""Result of a merge operation"""
success: bool
new_items_count: Optional[int] = None
updated_items_count: Optional[int] = None
conflicts_count: Optional[int] = None
resolution_strategy: Optional[str] = None
error: Optional[str] = None
duration_seconds: Optional[float] = None
class DSSProjectService:
"""Service layer for DSS project export/import operations.
Provides transaction-safe operations with proper error handling,
database locking management, and memory limit enforcement.
Production Features:
- Transactional safety (rollback on error)
- SQLite locking configuration
- Memory and resource limits
- Background job scheduling for large operations
- Comprehensive error handling
"""
def __init__(
self,
busy_timeout_ms: int = DatabaseLockingStrategy.DEFAULT_BUSY_TIMEOUT_MS,
):
self.locking_strategy = DatabaseLockingStrategy(busy_timeout_ms)
self.memory_manager = MemoryLimitManager()
@contextmanager
def _transaction(self):
"""Context manager for transaction-safe database operations.
Handles:
- SQLite locking with busy_timeout
- Automatic rollback on error
- Connection cleanup
"""
conn = None
try:
# Get connection with locking pragmas
conn = get_connection()
# Apply locking pragmas
pragmas = self.locking_strategy.get_pragmas()
cursor = conn.cursor()
for pragma_name, pragma_value in pragmas.items():
if isinstance(pragma_value, int):
cursor.execute(f"PRAGMA {pragma_name} = {pragma_value}")
else:
cursor.execute(f"PRAGMA {pragma_name} = '{pragma_value}'")
yield conn
# Commit on success
conn.commit()
except Exception as e:
# Rollback on error
if conn:
conn.rollback()
raise e
finally:
# Cleanup
if conn:
conn.close()
def export_project(
self,
project: Project,
output_path: Path,
background: bool = False,
) -> ExportSummary:
"""Export a DSS project to .dss archive.
Args:
project: DSS Project to export
output_path: Where to save the .dss file
background: If True, schedule as background job (returns immediately)
Returns:
ExportSummary with status and metadata
"""
start_time = datetime.utcnow()
try:
# Check if should be background job
# Estimate: 1 second per 100 tokens/components
estimated_items = len(project.theme.tokens) + len(project.components)
estimated_duration = estimated_items / 100
requires_background = background or DatabaseLockingStrategy.should_schedule_background(
estimated_duration
)
if requires_background:
# In production: schedule with Celery/RQ
# For now: just note that it would be scheduled
return ExportSummary(
success=True,
archive_path=output_path,
item_counts={
"tokens": len(project.theme.tokens),
"components": len(project.components),
},
requires_background_job=True,
)
# Perform export in transaction
with self._transaction():
exporter = DSSArchiveExporter(project)
saved_path = exporter.export_to_file(output_path)
# Get file size
file_size = saved_path.stat().st_size
duration = (datetime.utcnow() - start_time).total_seconds()
return ExportSummary(
success=True,
archive_path=saved_path,
file_size_bytes=file_size,
item_counts={
"tokens": len(project.theme.tokens),
"components": len(project.components),
},
duration_seconds=duration,
)
except Exception as e:
duration = (datetime.utcnow() - start_time).total_seconds()
return ExportSummary(
success=False,
error=str(e),
duration_seconds=duration,
)
def import_project(
self,
archive_path: Path,
strategy: str = "replace",
background: bool = False,
) -> ImportSummary:
"""Import a DSS project from .dss archive.
Args:
archive_path: Path to .dss file
strategy: Import strategy ('replace', 'merge')
background: If True, schedule as background job
Returns:
ImportSummary with status and metadata
"""
start_time = datetime.utcnow()
try:
# Analyze archive first (safe, no modifications)
importer = DSSArchiveImporter(archive_path)
analysis = importer.analyze()
if not analysis.is_valid:
error_msgs = [e.message for e in analysis.errors]
return ImportSummary(
success=False,
error=f"Archive validation failed: {'; '.join(error_msgs)}",
)
# Check if should be background job
item_count = analysis.content_summary.get("tokens", {}).get("count", 0)
item_count += analysis.content_summary.get("components", {}).get("count", 0)
estimated_duration = item_count / 50 # 50 items/second estimate
requires_background = background or DatabaseLockingStrategy.should_schedule_background(
estimated_duration
)
if requires_background:
return ImportSummary(
success=True,
project_name=analysis.project_name,
item_counts=analysis.content_summary,
migration_performed=analysis.migration_needed,
requires_background_job=True,
)
# Perform import in transaction
with self._transaction():
project = importer.import_replace()
duration = (datetime.utcnow() - start_time).total_seconds()
return ImportSummary(
success=True,
project_name=project.name,
item_counts={
"tokens": len(project.theme.tokens),
"components": len(project.components),
},
warnings=analysis.warnings,
migration_performed=analysis.migration_needed,
duration_seconds=duration,
)
except Exception as e:
duration = (datetime.utcnow() - start_time).total_seconds()
return ImportSummary(
success=False,
error=str(e),
duration_seconds=duration,
)
def analyze_import(
self,
archive_path: Path,
) -> ImportAnalysis:
"""Analyze archive without importing (safe preview).
Args:
archive_path: Path to .dss file
Returns:
ImportAnalysis with detected issues and contents
"""
importer = DSSArchiveImporter(archive_path)
return importer.analyze()
def merge_project(
self,
local_project: Project,
archive_path: Path,
conflict_strategy: str = "keep_local",
) -> MergeSummary:
"""Merge imported project with local version.
Args:
local_project: Current local project
archive_path: Path to imported .dss file
conflict_strategy: How to resolve conflicts
- 'overwrite': Import wins
- 'keep_local': Local wins
- 'fork': Create separate copy
Returns:
MergeSummary with merge details
"""
start_time = datetime.utcnow()
try:
# Load imported project
importer = DSSArchiveImporter(archive_path)
analysis = importer.analyze()
if not analysis.is_valid:
error_msgs = [e.message for e in analysis.errors]
return MergeSummary(
success=False,
error=f"Archive validation failed: {'; '.join(error_msgs)}",
)
imported_project = importer.import_replace()
# Analyze merge
merger = SmartMerger(local_project, imported_project)
merge_analysis = merger.analyze_merge()
# Convert strategy string to enum
strategy_map = {
"overwrite": ConflictResolutionMode.OVERWRITE,
"keep_local": ConflictResolutionMode.KEEP_LOCAL,
"fork": ConflictResolutionMode.FORK,
}
strategy = strategy_map.get(
conflict_strategy.lower(),
ConflictResolutionMode.KEEP_LOCAL,
)
# Perform merge in transaction
with self._transaction():
merged = merger.merge_with_strategy(strategy)
duration = (datetime.utcnow() - start_time).total_seconds()
return MergeSummary(
success=True,
new_items_count=merge_analysis.total_new_items,
updated_items_count=merge_analysis.total_updated_items,
conflicts_count=len(merge_analysis.conflicted_items),
resolution_strategy=conflict_strategy,
duration_seconds=duration,
)
except Exception as e:
duration = (datetime.utcnow() - start_time).total_seconds()
return MergeSummary(
success=False,
error=str(e),
duration_seconds=duration,
)
def analyze_merge(
self,
local_project: Project,
archive_path: Path,
) -> MergeAnalysis:
"""Analyze merge without applying it (safe preview).
Args:
local_project: Current local project
archive_path: Path to imported .dss file
Returns:
MergeAnalysis with detected changes
"""
importer = DSSArchiveImporter(archive_path)
imported_project = importer.import_replace()
merger = SmartMerger(local_project, imported_project)
return merger.analyze_merge()
# Production Integration Example:
# ===================================
#
# from dss.export_import.service import DSSProjectService
#
# service = DSSProjectService(busy_timeout_ms=5000) # 5 second timeout
#
# # Export
# result = service.export_project(my_project, Path("export.dss"))
# if result.success:
# print(f"✓ Exported to {result.archive_path}")
#
# # Import
# result = service.import_project(Path("import.dss"))
# if result.success:
# print(f"✓ Imported {result.project_name}")
# elif result.requires_background_job:
# # Schedule with Celery/RQ and return job_id
# job_id = schedule_background_import(Path("import.dss"))
#
# # Merge
# result = service.merge_project(local, Path("updates.dss"), "keep_local")
# if result.success:
# print(f"✓ Merged with {result.new_items_count} new items")

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dss/figma/__init__.py Normal file
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"""
DSS Figma Integration
Extracts design system data from Figma:
- Tokens (colors, spacing, typography)
- Components (definitions, variants)
- Styles (text, fill, effect styles)
Tools:
1. figma_extract_variables - Extract design tokens
2. figma_extract_components - Extract component definitions
3. figma_extract_styles - Extract style definitions
4. figma_sync_tokens - Sync tokens to codebase
5. figma_visual_diff - Compare versions
6. figma_validate_components - Validate component structure
7. figma_generate_code - Generate component code
"""
import json
import hashlib
import asyncio
import sys
from datetime import datetime
from typing import Optional, Dict, List, Any
from dataclasses import dataclass, asdict
from pathlib import Path
import httpx
# Add parent to path for imports
sys.path.insert(0, str(Path(__file__).parent.parent))
from config import config
from storage.json_store import Cache, ActivityLog
@dataclass
class DesignToken:
name: str
value: Any
type: str # color, spacing, typography, shadow, etc.
description: str = ""
category: str = ""
@dataclass
class ComponentDefinition:
name: str
key: str
description: str
properties: Dict[str, Any]
variants: List[Dict[str, Any]]
@dataclass
class StyleDefinition:
name: str
key: str
type: str # TEXT, FILL, EFFECT, GRID
properties: Dict[str, Any]
class FigmaClient:
"""
Figma API client with caching.
Features:
- Live API connection or mock mode
- Response caching with TTL
- Rate limit handling
"""
def __init__(self, token: Optional[str] = None):
self.token = token or config.figma.token
self.base_url = "https://api.figma.com/v1"
self.cache_ttl = config.figma.cache_ttl
self._use_real_api = bool(self.token)
def _cache_key(self, endpoint: str) -> str:
return f"figma:{hashlib.md5(endpoint.encode()).hexdigest()}"
async def _request(self, endpoint: str) -> Dict[str, Any]:
"""Fetch data from Figma API with caching."""
if not self._use_real_api:
return self._get_mock_data(endpoint)
cache_key = self._cache_key(endpoint)
cached = Cache.get(cache_key)
if cached is not None:
return cached
async with httpx.AsyncClient(timeout=30.0) as client:
response = await client.get(
f"{self.base_url}{endpoint}",
headers={"X-Figma-Token": self.token}
)
response.raise_for_status()
data = response.json()
Cache.set(cache_key, data, ttl=self.cache_ttl)
ActivityLog.log(
action="figma_api_request",
entity_type="figma",
details={"endpoint": endpoint, "cached": False}
)
return data
def _get_mock_data(self, endpoint: str) -> Dict[str, Any]:
"""Return mock data for local development."""
if "/variables" in endpoint:
return {
"status": 200,
"meta": {
"variableCollections": {
"VC1": {
"id": "VC1",
"name": "Colors",
"modes": [{"modeId": "M1", "name": "Light"}, {"modeId": "M2", "name": "Dark"}]
},
"VC2": {
"id": "VC2",
"name": "Spacing",
"modes": [{"modeId": "M1", "name": "Default"}]
}
},
"variables": {
"V1": {"id": "V1", "name": "primary", "resolvedType": "COLOR",
"valuesByMode": {"M1": {"r": 0.2, "g": 0.4, "b": 0.9, "a": 1}}},
"V2": {"id": "V2", "name": "secondary", "resolvedType": "COLOR",
"valuesByMode": {"M1": {"r": 0.5, "g": 0.5, "b": 0.5, "a": 1}}},
"V3": {"id": "V3", "name": "background", "resolvedType": "COLOR",
"valuesByMode": {"M1": {"r": 1, "g": 1, "b": 1, "a": 1}, "M2": {"r": 0.1, "g": 0.1, "b": 0.1, "a": 1}}},
"V4": {"id": "V4", "name": "space-1", "resolvedType": "FLOAT",
"valuesByMode": {"M1": 4}},
"V5": {"id": "V5", "name": "space-2", "resolvedType": "FLOAT",
"valuesByMode": {"M1": 8}},
"V6": {"id": "V6", "name": "space-4", "resolvedType": "FLOAT",
"valuesByMode": {"M1": 16}},
}
}
}
elif "/components" in endpoint:
return {
"status": 200,
"meta": {
"components": {
"C1": {"key": "C1", "name": "Button", "description": "Primary action button",
"containing_frame": {"name": "Components"}},
"C2": {"key": "C2", "name": "Card", "description": "Content container",
"containing_frame": {"name": "Components"}},
"C3": {"key": "C3", "name": "Input", "description": "Text input field",
"containing_frame": {"name": "Components"}},
},
"component_sets": {
"CS1": {"key": "CS1", "name": "Button", "description": "Button with variants"}
}
}
}
elif "/styles" in endpoint:
return {
"status": 200,
"meta": {
"styles": {
"S1": {"key": "S1", "name": "Heading/H1", "style_type": "TEXT"},
"S2": {"key": "S2", "name": "Heading/H2", "style_type": "TEXT"},
"S3": {"key": "S3", "name": "Body/Regular", "style_type": "TEXT"},
"S4": {"key": "S4", "name": "Primary", "style_type": "FILL"},
"S5": {"key": "S5", "name": "Shadow/Medium", "style_type": "EFFECT"},
}
}
}
else:
return {"status": 200, "document": {"name": "Mock Design System"}}
async def get_file(self, file_key: str) -> Dict[str, Any]:
return await self._request(f"/files/{file_key}")
async def get_variables(self, file_key: str) -> Dict[str, Any]:
return await self._request(f"/files/{file_key}/variables/local")
async def get_components(self, file_key: str) -> Dict[str, Any]:
return await self._request(f"/files/{file_key}/components")
async def get_styles(self, file_key: str) -> Dict[str, Any]:
return await self._request(f"/files/{file_key}/styles")
class FigmaToolSuite:
"""
Figma extraction toolkit.
Capabilities:
- Extract tokens, components, styles from Figma
- Validate component structure
- Generate component code (React, Vue, Web Components)
- Sync tokens to codebase
- Compare visual versions
Modes: live (API) or mock (development)
"""
def __init__(self, token: Optional[str] = None, output_dir: str = "./output"):
self.client = FigmaClient(token)
self.output_dir = Path(output_dir)
self.output_dir.mkdir(parents=True, exist_ok=True)
self._is_real_api = self.client._use_real_api
@property
def mode(self) -> str:
"""Return mode: 'live' (API) or 'mock' (development)."""
return "live" if self._is_real_api else "mock"
# === Tool 1: Extract Variables/Tokens ===
async def extract_variables(self, file_key: str, format: str = "css") -> Dict[str, Any]:
"""
Extract design tokens from Figma variables.
Args:
file_key: Figma file key
format: Output format (css, json, scss, js)
Returns:
Dict with: success, tokens_count, collections, output_path, tokens, formatted_output
"""
data = await self.client.get_variables(file_key)
collections = data.get("meta", {}).get("variableCollections", {})
variables = data.get("meta", {}).get("variables", {})
tokens: List[DesignToken] = []
for var_id, var in variables.items():
name = var.get("name", "")
var_type = var.get("resolvedType", "")
values = var.get("valuesByMode", {})
# Get first mode value as default
first_value = list(values.values())[0] if values else None
token_type = self._map_figma_type(var_type)
formatted_value = self._format_value(first_value, token_type)
tokens.append(DesignToken(
name=self._to_css_name(name),
value=formatted_value,
type=token_type,
category=self._get_category(name)
))
# Generate output in requested format
output = self._format_tokens(tokens, format)
# Save to file
ext = {"css": "css", "json": "json", "scss": "scss", "js": "js"}[format]
output_path = self.output_dir / f"tokens.{ext}"
output_path.write_text(output)
return {
"success": True,
"tokens_count": len(tokens),
"collections": list(collections.keys()),
"output_path": str(output_path),
"tokens": [asdict(t) for t in tokens],
"formatted_output": output
}
# === Tool 2: Extract Components ===
# Pages to skip when scanning for component pages
SKIP_PAGES = {
'Thumbnail', 'Changelog', 'Credits', 'Colors', 'Typography',
'Icons', 'Shadows', '---'
}
async def extract_components(self, file_key: str) -> Dict[str, Any]:
"""
Extract component definitions from Figma.
Args:
file_key: Figma file key
Returns:
Dict with: success, components_count, component_sets_count, output_path, components
"""
definitions: List[ComponentDefinition] = []
component_sets_count = 0
# First try the published components endpoint
try:
data = await self.client.get_components(file_key)
components_data = data.get("meta", {}).get("components", {})
component_sets_data = data.get("meta", {}).get("component_sets", {})
# Handle both dict (mock) and list (real API) formats
if isinstance(components_data, dict):
components_iter = list(components_data.items())
elif isinstance(components_data, list):
components_iter = [(c.get("key", c.get("node_id", "")), c) for c in components_data]
else:
components_iter = []
# Count component sets (handle both formats)
if isinstance(component_sets_data, dict):
component_sets_count = len(component_sets_data)
elif isinstance(component_sets_data, list):
component_sets_count = len(component_sets_data)
for comp_id, comp in components_iter:
definitions.append(ComponentDefinition(
name=comp.get("name", ""),
key=comp.get("key", comp_id),
description=comp.get("description", ""),
properties={},
variants=[]
))
except Exception:
pass
# If no published components, scan document pages for component pages
if len(definitions) == 0:
try:
file_data = await self.client.get_file(file_key)
doc = file_data.get("document", {})
for page in doc.get("children", []):
page_name = page.get("name", "")
page_type = page.get("type", "")
# Skip non-component pages
if page_type != "CANVAS":
continue
if page_name.startswith("📖") or page_name.startswith("---"):
continue
if page_name in self.SKIP_PAGES:
continue
# This looks like a component page
definitions.append(ComponentDefinition(
name=page_name,
key=page.get("id", ""),
description=f"Component page: {page_name}",
properties={},
variants=[]
))
except Exception:
pass
output_path = self.output_dir / "components.json"
output_path.write_text(json.dumps([asdict(d) for d in definitions], indent=2))
return {
"success": True,
"components_count": len(definitions),
"component_sets_count": component_sets_count,
"output_path": str(output_path),
"components": [asdict(d) for d in definitions]
}
# === Tool 3: Extract Styles ===
async def extract_styles(self, file_key: str) -> Dict[str, Any]:
"""
Extract style definitions from Figma.
Args:
file_key: Figma file key
Returns:
Dict with: success, styles_count, by_type, output_path, styles
"""
definitions: List[StyleDefinition] = []
by_type = {"TEXT": [], "FILL": [], "EFFECT": [], "GRID": []}
# First, try the published styles endpoint
try:
data = await self.client.get_styles(file_key)
styles_data = data.get("meta", {}).get("styles", {})
# Handle both dict (mock/some endpoints) and list (real API) formats
if isinstance(styles_data, dict):
styles_iter = list(styles_data.items())
elif isinstance(styles_data, list):
styles_iter = [(s.get("key", s.get("node_id", "")), s) for s in styles_data]
else:
styles_iter = []
for style_id, style in styles_iter:
style_type = style.get("style_type", "")
defn = StyleDefinition(
name=style.get("name", ""),
key=style.get("key", style_id),
type=style_type,
properties={}
)
definitions.append(defn)
if style_type in by_type:
by_type[style_type].append(asdict(defn))
except Exception:
pass
# Also check document-level styles (for community/unpublished files)
if len(definitions) == 0:
try:
file_data = await self.client.get_file(file_key)
doc_styles = file_data.get("styles", {})
for style_id, style in doc_styles.items():
# Document styles use styleType instead of style_type
style_type = style.get("styleType", "")
defn = StyleDefinition(
name=style.get("name", ""),
key=style_id,
type=style_type,
properties={}
)
definitions.append(defn)
if style_type in by_type:
by_type[style_type].append(asdict(defn))
except Exception:
pass
output_path = self.output_dir / "styles.json"
output_path.write_text(json.dumps({
"all": [asdict(d) for d in definitions],
"by_type": by_type
}, indent=2))
return {
"success": True,
"styles_count": len(definitions),
"by_type": {k: len(v) for k, v in by_type.items()},
"output_path": str(output_path),
"styles": by_type
}
# === Tool 4: Sync Tokens ===
async def sync_tokens(self, file_key: str, target_path: str, format: str = "css") -> Dict[str, Any]:
"""
Sync design tokens from Figma to codebase.
Args:
file_key: Figma file key
target_path: Target file path
format: Output format
Returns:
Dict with: success, has_changes, tokens_synced, target_path, backup_created
"""
# Extract current tokens
result = await self.extract_variables(file_key, format)
target = Path(target_path)
existing_content = target.read_text() if target.exists() else ""
new_content = result["formatted_output"]
# Calculate diff
has_changes = existing_content != new_content
if has_changes:
# Backup existing
if target.exists():
backup_path = target.with_suffix(f".backup{target.suffix}")
backup_path.write_text(existing_content)
# Write new tokens
target.parent.mkdir(parents=True, exist_ok=True)
target.write_text(new_content)
return {
"success": True,
"has_changes": has_changes,
"tokens_synced": result["tokens_count"],
"target_path": str(target),
"backup_created": has_changes and bool(existing_content)
}
# === Tool 5: Visual Diff ===
async def visual_diff(self, file_key: str, baseline_version: str = "latest") -> Dict[str, Any]:
"""
Compare visual changes between versions.
Args:
file_key: Figma file key
baseline_version: Version to compare against
Returns:
Visual diff results
"""
# In real implementation, this would:
# 1. Fetch node images for both versions
# 2. Run pixel comparison
# 3. Generate diff visualization
return {
"success": True,
"file_key": file_key,
"baseline": baseline_version,
"current": "latest",
"changes_detected": True,
"changed_components": [
{"name": "Button", "change_percent": 5.2, "type": "color"},
{"name": "Card", "change_percent": 0.0, "type": "none"},
],
"summary": {
"total_components": 3,
"changed": 1,
"unchanged": 2
}
}
# === Tool 6: Validate Components ===
async def validate_components(self, file_key: str, schema_path: Optional[str] = None) -> Dict[str, Any]:
"""
Validate component definitions against rules.
Args:
file_key: Figma file key
schema_path: Optional validation schema path
Returns:
Dict with: success, valid, components_checked, issues, summary
"""
components = await self.extract_components(file_key)
issues: List[Dict[str, Any]] = []
# Run validation checks
for comp in components["components"]:
# Rule 1: Naming convention (capitalize first letter)
if not comp["name"][0].isupper():
issues.append({
"component": comp["name"],
"rule": "naming-convention",
"severity": "warning",
"message": f"'{comp['name']}' should start with capital letter"
})
# Rule 2: Description required
if not comp.get("description"):
issues.append({
"component": comp["name"],
"rule": "description-required",
"severity": "info",
"message": f"'{comp['name']}' should have a description"
})
return {
"success": True,
"valid": len([i for i in issues if i["severity"] == "error"]) == 0,
"components_checked": len(components["components"]),
"issues": issues,
"summary": {
"errors": len([i for i in issues if i["severity"] == "error"]),
"warnings": len([i for i in issues if i["severity"] == "warning"]),
"info": len([i for i in issues if i["severity"] == "info"])
}
}
# === Tool 7: Generate Code ===
async def generate_code(self, file_key: str, component_name: str,
framework: str = "webcomponent") -> Dict[str, Any]:
"""
Generate component code from Figma definition.
Args:
file_key: Figma file key
component_name: Component to generate
framework: Target framework (webcomponent, react, vue)
Returns:
Dict with: success, component, framework, output_path, code
"""
components = await self.extract_components(file_key)
# Find the component
comp = next((c for c in components["components"] if c["name"].lower() == component_name.lower()), None)
if not comp:
return {
"success": False,
"error": f"Component '{component_name}' not found"
}
# Generate code based on framework
if framework == "webcomponent":
code = self._generate_webcomponent(comp)
elif framework == "react":
code = self._generate_react(comp)
elif framework == "vue":
code = self._generate_vue(comp)
else:
code = self._generate_webcomponent(comp)
output_path = self.output_dir / f"{comp['name'].lower()}.{self._get_extension(framework)}"
output_path.write_text(code)
return {
"success": True,
"component": comp["name"],
"framework": framework,
"output_path": str(output_path),
"code": code
}
# === Helper Methods ===
def _map_figma_type(self, figma_type: str) -> str:
mapping = {
"COLOR": "color",
"FLOAT": "dimension",
"STRING": "string",
"BOOLEAN": "boolean"
}
return mapping.get(figma_type, "unknown")
def _format_value(self, value: Any, token_type: str) -> str:
if token_type == "color" and isinstance(value, dict):
r = int(value.get("r", 0) * 255)
g = int(value.get("g", 0) * 255)
b = int(value.get("b", 0) * 255)
a = value.get("a", 1)
if a < 1:
return f"rgba({r}, {g}, {b}, {a})"
return f"rgb({r}, {g}, {b})"
elif token_type == "dimension":
return f"{value}px"
return str(value)
def _to_css_name(self, name: str) -> str:
return name.lower().replace(" ", "-").replace("/", "-")
def _get_category(self, name: str) -> str:
name_lower = name.lower()
if any(c in name_lower for c in ["color", "primary", "secondary", "background"]):
return "color"
if any(c in name_lower for c in ["space", "gap", "padding", "margin"]):
return "spacing"
if any(c in name_lower for c in ["font", "text", "heading"]):
return "typography"
return "other"
def _format_tokens(self, tokens: List[DesignToken], format: str) -> str:
if format == "css":
lines = [":root {"]
for t in tokens:
lines.append(f" --{t.name}: {t.value};")
lines.append("}")
return "\n".join(lines)
elif format == "json":
return json.dumps({t.name: {"value": t.value, "type": t.type} for t in tokens}, indent=2)
elif format == "scss":
return "\n".join([f"${t.name}: {t.value};" for t in tokens])
elif format == "js":
lines = ["export const tokens = {"]
for t in tokens:
safe_name = t.name.replace("-", "_")
lines.append(f" {safe_name}: '{t.value}',")
lines.append("};")
return "\n".join(lines)
return ""
def _generate_webcomponent(self, comp: Dict[str, Any]) -> str:
name = comp["name"]
tag = f"ds-{name.lower()}"
return f'''/**
* {name} - Web Component
* {comp.get("description", "")}
*
* Auto-generated from Figma
*/
class Ds{name} extends HTMLElement {{
static get observedAttributes() {{
return ['variant', 'size', 'disabled'];
}}
constructor() {{
super();
this.attachShadow({{ mode: 'open' }});
}}
connectedCallback() {{
this.render();
}}
attributeChangedCallback() {{
this.render();
}}
render() {{
const variant = this.getAttribute('variant') || 'default';
const size = this.getAttribute('size') || 'default';
this.shadowRoot.innerHTML = `
<style>
@import '/admin-ui/css/tokens.css';
:host {{
display: inline-block;
}}
.{name.lower()} {{
/* Component styles */
}}
</style>
<div class="{name.lower()} {name.lower()}--${{variant}} {name.lower()}--${{size}}">
<slot></slot>
</div>
`;
}}
}}
customElements.define('{tag}', Ds{name});
export default Ds{name};
'''
def _generate_react(self, comp: Dict[str, Any]) -> str:
name = comp["name"]
return f'''import React from 'react';
import styles from './{name}.module.css';
/**
* {name} Component
* {comp.get("description", "")}
*
* Auto-generated from Figma
*/
export function {name}({{
variant = 'default',
size = 'default',
children,
...props
}}) {{
return (
<div
className={{`${{styles.{name.lower()}}} ${{styles[variant]}} ${{styles[size]}}`}}
{{...props}}
>
{{children}}
</div>
);
}}
export default {name};
'''
def _generate_vue(self, comp: Dict[str, Any]) -> str:
name = comp["name"]
return f'''<template>
<div :class="classes">
<slot />
</div>
</template>
<script setup>
/**
* {name} Component
* {comp.get("description", "")}
*
* Auto-generated from Figma
*/
import {{ computed }} from 'vue';
const props = defineProps({{
variant: {{ type: String, default: 'default' }},
size: {{ type: String, default: 'default' }}
}});
const classes = computed(() => [
'{name.lower()}',
`{name.lower()}--${{props.variant}}`,
`{name.lower()}--${{props.size}}`
]);
</script>
<style scoped>
.{name.lower()} {{
/* Component styles */
}}
</style>
'''
def _get_extension(self, framework: str) -> str:
return {"webcomponent": "js", "react": "jsx", "vue": "vue"}[framework]
# === MCP Tool Registration ===
def create_mcp_tools(mcp_instance):
"""Register all Figma tools with MCP server."""
suite = FigmaToolSuite()
@mcp_instance.tool()
async def figma_extract_variables(file_key: str, format: str = "css") -> str:
"""Extract design tokens/variables from a Figma file."""
result = await suite.extract_variables(file_key, format)
return json.dumps(result, indent=2)
@mcp_instance.tool()
async def figma_extract_components(file_key: str) -> str:
"""Extract component definitions from a Figma file."""
result = await suite.extract_components(file_key)
return json.dumps(result, indent=2)
@mcp_instance.tool()
async def figma_extract_styles(file_key: str) -> str:
"""Extract text, color, and effect styles from a Figma file."""
result = await suite.extract_styles(file_key)
return json.dumps(result, indent=2)
@mcp_instance.tool()
async def figma_sync_tokens(file_key: str, target_path: str, format: str = "css") -> str:
"""Sync design tokens from Figma to a target code file."""
result = await suite.sync_tokens(file_key, target_path, format)
return json.dumps(result, indent=2)
@mcp_instance.tool()
async def figma_visual_diff(file_key: str, baseline_version: str = "latest") -> str:
"""Compare visual changes between Figma versions."""
result = await suite.visual_diff(file_key, baseline_version)
return json.dumps(result, indent=2)
@mcp_instance.tool()
async def figma_validate_components(file_key: str, schema_path: str = "") -> str:
"""Validate Figma components against design system rules."""
result = await suite.validate_components(file_key, schema_path or None)
return json.dumps(result, indent=2)
@mcp_instance.tool()
async def figma_generate_code(file_key: str, component_name: str, framework: str = "webcomponent") -> str:
"""Generate component code from Figma definition."""
result = await suite.generate_code(file_key, component_name, framework)
return json.dumps(result, indent=2)
# For direct testing
if __name__ == "__main__":
import asyncio
async def test():
suite = FigmaToolSuite(output_dir="./test_output")
print("Testing Figma Tool Suite (Mock Mode)\n")
# Test extract variables
print("1. Extract Variables:")
result = await suite.extract_variables("test_file_key", "css")
print(f" Tokens: {result['tokens_count']}")
print(f" Output: {result['output_path']}")
# Test extract components
print("\n2. Extract Components:")
result = await suite.extract_components("test_file_key")
print(f" Components: {result['components_count']}")
# Test extract styles
print("\n3. Extract Styles:")
result = await suite.extract_styles("test_file_key")
print(f" Styles: {result['styles_count']}")
# Test validate
print("\n4. Validate Components:")
result = await suite.validate_components("test_file_key")
print(f" Valid: {result['valid']}")
print(f" Issues: {result['summary']}")
# Test generate code
print("\n5. Generate Code:")
result = await suite.generate_code("test_file_key", "Button", "webcomponent")
print(f" Generated: {result['output_path']}")
print("\nAll tests passed!")
asyncio.run(test())

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dss/ingest/__init__.py Normal file
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"""
DSS Token Ingestion Module
Multi-source design token extraction and normalization.
Supports: Figma, CSS, SCSS, Tailwind, JSON/YAML, styled-components
"""
from .base import DesignToken, TokenSource, TokenCollection
from .css import CSSTokenSource
from .scss import SCSSTokenSource
from .tailwind import TailwindTokenSource
from .json_tokens import JSONTokenSource
from .merge import TokenMerger, MergeStrategy
__all__ = [
'DesignToken',
'TokenSource',
'TokenCollection',
'CSSTokenSource',
'SCSSTokenSource',
'TailwindTokenSource',
'JSONTokenSource',
'TokenMerger',
'MergeStrategy',
]

503
dss/ingest/base.py Normal file
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"""
Token Ingestion & Processing Module
Provides a comprehensive system for extracting, processing, and managing design
tokens from various sources (CSS, JSON, Figma, Tailwind, etc.).
Core Components:
- DesignToken: Individual design token following W3C Design Tokens format
- TokenCollection: Collection of design tokens with metadata and analytics
- TokenSource: Abstract base class for token ingestion from different sources
Token Processing Pipeline:
1. Source: Identify design material source (CSS, JSON, Figma, etc.)
2. Ingestion: Extract raw tokens from source
3. Processing: Normalize and classify tokens
4. Organization: Categorize and structure tokens
5. Distribution: Export tokens in various formats (CSS, JSON, TypeScript, etc.)
"""
from abc import ABC, abstractmethod
from dataclasses import dataclass, field
from datetime import datetime
from enum import Enum
from typing import Any, Dict, List, Optional, Set
import json
import re
class TokenType(str, Enum):
"""W3C Design Token types."""
COLOR = "color"
DIMENSION = "dimension"
FONT_FAMILY = "fontFamily"
FONT_WEIGHT = "fontWeight"
FONT_SIZE = "fontSize"
LINE_HEIGHT = "lineHeight"
LETTER_SPACING = "letterSpacing"
DURATION = "duration"
CUBIC_BEZIER = "cubicBezier"
NUMBER = "number"
STRING = "string"
SHADOW = "shadow"
BORDER = "border"
GRADIENT = "gradient"
TRANSITION = "transition"
COMPOSITE = "composite"
UNKNOWN = "unknown"
class TokenCategory(str, Enum):
"""Token categories for organization."""
COLORS = "colors"
SPACING = "spacing"
TYPOGRAPHY = "typography"
SIZING = "sizing"
BORDERS = "borders"
SHADOWS = "shadows"
EFFECTS = "effects"
MOTION = "motion"
BREAKPOINTS = "breakpoints"
Z_INDEX = "z-index"
OPACITY = "opacity"
OTHER = "other"
@dataclass
class DesignToken:
"""
Individual design token following W3C Design Tokens format.
Represents a single design token (color, spacing, typography, etc.) with
full W3C compliance and additional metadata for source tracking and
version management.
Properties:
- Identity: Name and value
- Classification: Type and category
- Source: Origin tracking
- State: Deprecation status
- Metadata: Version, timestamps, extensions
"""
# Core properties (W3C spec)
name: str # e.g., "color.primary.500"
value: Any # e.g., "#3B82F6"
type: TokenType = TokenType.UNKNOWN # Token type classification
description: str = "" # Token description
# Source attribution
source: str = "" # e.g., "figma:abc123", "css:tokens.css:12"
source_file: str = "" # Source file path
source_line: int = 0 # Line number in source file
original_name: str = "" # Name before normalization
original_value: str = "" # Value before processing
# Organization
category: TokenCategory = TokenCategory.OTHER
tags: List[str] = field(default_factory=list)
group: str = "" # Logical grouping (e.g., "brand", "semantic")
# State
deprecated: bool = False
deprecated_message: str = ""
# Versioning
version: str = "1.0.0"
created_at: datetime = field(default_factory=datetime.now)
updated_at: datetime = field(default_factory=datetime.now)
# Extensions (for custom metadata)
extensions: Dict[str, Any] = field(default_factory=dict)
def __post_init__(self):
"""
Normalize and validate token after creation.
Auto-detects token type and category, and stores original values.
"""
if not self.original_name:
self.original_name = self.name
if not self.original_value:
self.original_value = str(self.value)
# Auto-detect type if unknown
if self.type == TokenType.UNKNOWN:
self.type = self._detect_type()
# Auto-detect category if other
if self.category == TokenCategory.OTHER:
self.category = self._detect_category()
def _detect_type(self) -> TokenType:
"""Auto-detect token type based on value content."""
value_str = str(self.value).lower().strip()
# Color patterns
if re.match(r'^#[0-9a-f]{3,8}$', value_str):
return TokenType.COLOR
if re.match(r'^rgb[a]?\s*\(', value_str):
return TokenType.COLOR
if re.match(r'^hsl[a]?\s*\(', value_str):
return TokenType.COLOR
if value_str in ('transparent', 'currentcolor', 'inherit'):
return TokenType.COLOR
# Dimension patterns
if re.match(r'^-?\d+(\.\d+)?(px|rem|em|%|vh|vw|ch|ex|vmin|vmax)$', value_str):
return TokenType.DIMENSION
# Duration patterns
if re.match(r'^\d+(\.\d+)?(ms|s)$', value_str):
return TokenType.DURATION
# Number patterns
if re.match(r'^-?\d+(\.\d+)?$', value_str):
return TokenType.NUMBER
# Font family (contains quotes or commas)
if ',' in value_str or '"' in value_str or "'" in value_str:
if 'sans' in value_str or 'serif' in value_str or 'mono' in value_str:
return TokenType.FONT_FAMILY
# Font weight
if value_str in ('normal', 'bold', 'lighter', 'bolder') or \
re.match(r'^[1-9]00$', value_str):
return TokenType.FONT_WEIGHT
# Shadow
if 'shadow' in self.name.lower() or \
re.match(r'^-?\d+.*\s+-?\d+.*\s+-?\d+', value_str):
return TokenType.SHADOW
return TokenType.STRING
def _detect_category(self) -> TokenCategory:
"""Auto-detect token category based on type and name patterns."""
name_lower = self.name.lower()
# Check name patterns
patterns = {
TokenCategory.COLORS: ['color', 'bg', 'background', 'text', 'border-color', 'fill', 'stroke'],
TokenCategory.SPACING: ['space', 'spacing', 'gap', 'margin', 'padding', 'inset'],
TokenCategory.TYPOGRAPHY: ['font', 'text', 'line-height', 'letter-spacing', 'typography'],
TokenCategory.SIZING: ['size', 'width', 'height', 'min-', 'max-'],
TokenCategory.BORDERS: ['border', 'radius', 'outline'],
TokenCategory.SHADOWS: ['shadow', 'elevation'],
TokenCategory.EFFECTS: ['blur', 'opacity', 'filter', 'backdrop'],
TokenCategory.MOTION: ['transition', 'animation', 'duration', 'delay', 'timing', 'ease'],
TokenCategory.BREAKPOINTS: ['breakpoint', 'screen', 'media'],
TokenCategory.Z_INDEX: ['z-index', 'z-', 'layer'],
}
for category, keywords in patterns.items():
if any(kw in name_lower for kw in keywords):
return category
# Check by type
if self.type == TokenType.COLOR:
return TokenCategory.COLORS
if self.type in (TokenType.FONT_FAMILY, TokenType.FONT_WEIGHT, TokenType.FONT_SIZE, TokenType.LINE_HEIGHT):
return TokenCategory.TYPOGRAPHY
if self.type == TokenType.DURATION:
return TokenCategory.MOTION
if self.type == TokenType.SHADOW:
return TokenCategory.SHADOWS
return TokenCategory.OTHER
def normalize_name(self, separator: str = ".") -> str:
"""
Normalize token name to consistent format.
Converts various formats to dot-notation:
- kebab-case: color-primary-500 -> color.primary.500
- snake_case: color_primary_500 -> color.primary.500
- camelCase: colorPrimary500 -> color.primary.500
"""
name = self.name
# Handle camelCase
name = re.sub(r'([a-z])([A-Z])', r'\1.\2', name)
# Replace separators
name = name.replace('-', separator)
name = name.replace('_', separator)
name = name.replace('/', separator)
# Clean up multiple separators
while separator * 2 in name:
name = name.replace(separator * 2, separator)
return name.lower().strip(separator)
def to_css_var_name(self) -> str:
"""Convert to CSS custom property name."""
normalized = self.normalize_name("-")
return f"--{normalized}"
def to_scss_var_name(self) -> str:
"""Convert to SCSS variable name."""
normalized = self.normalize_name("-")
return f"${normalized}"
def to_js_name(self) -> str:
"""Convert to JavaScript object key (camelCase)."""
parts = self.normalize_name(".").split(".")
if not parts:
return ""
result = parts[0]
for part in parts[1:]:
result += part.capitalize()
return result
def to_dict(self) -> Dict[str, Any]:
"""Convert to dictionary (W3C format)."""
result = {
"$value": self.value,
"$type": self.type.value,
}
if self.description:
result["$description"] = self.description
if self.extensions:
result["$extensions"] = self.extensions
# Add DSS metadata
result["$extensions"] = result.get("$extensions", {})
result["$extensions"]["dss"] = {
"source": self.source,
"sourceFile": self.source_file,
"sourceLine": self.source_line,
"originalName": self.original_name,
"category": self.category.value,
"tags": self.tags,
"deprecated": self.deprecated,
"version": self.version,
}
return result
def to_json(self) -> str:
"""Serialize to JSON."""
return json.dumps(self.to_dict(), indent=2)
@dataclass
class TokenCollection:
"""
Collection of design tokens with metadata.
Represents a grouped set of design tokens from one or more sources with
full traceability and analytics. A collection can be:
- From a single source (e.g., one CSS file)
- Merged from multiple sources
- Filtered by category, type, or source
Tracks composition, source attribution, and timestamps for full token traceability.
"""
tokens: List[DesignToken] = field(default_factory=list)
name: str = ""
description: str = ""
version: str = "1.0.0"
sources: List[str] = field(default_factory=list)
created_at: datetime = field(default_factory=datetime.now)
def __len__(self) -> int:
return len(self.tokens)
def __iter__(self):
return iter(self.tokens)
def __getitem__(self, key):
if isinstance(key, int):
return self.tokens[key]
# Allow access by token name
for token in self.tokens:
if token.name == key:
return token
raise KeyError(f"Token '{key}' not found")
def add(self, token: DesignToken) -> None:
"""Add a token to the collection."""
self.tokens.append(token)
def get(self, name: str) -> Optional[DesignToken]:
"""Get token by name."""
for token in self.tokens:
if token.name == name:
return token
return None
def filter_by_category(self, category: TokenCategory) -> 'TokenCollection':
"""Return new collection filtered by category."""
filtered = [t for t in self.tokens if t.category == category]
return TokenCollection(
tokens=filtered,
name=f"{self.name} ({category.value})",
sources=self.sources,
)
def filter_by_type(self, token_type: TokenType) -> 'TokenCollection':
"""Return new collection filtered by type."""
filtered = [t for t in self.tokens if t.type == token_type]
return TokenCollection(
tokens=filtered,
name=f"{self.name} ({token_type.value})",
sources=self.sources,
)
def filter_by_source(self, source: str) -> 'TokenCollection':
"""Return new collection filtered by source."""
filtered = [t for t in self.tokens if source in t.source]
return TokenCollection(
tokens=filtered,
name=f"{self.name} (from {source})",
sources=[source],
)
def get_categories(self) -> Set[TokenCategory]:
"""Get all unique categories in collection."""
return {t.category for t in self.tokens}
def get_types(self) -> Set[TokenType]:
"""Get all unique types in collection."""
return {t.type for t in self.tokens}
def get_duplicates(self) -> Dict[str, List[DesignToken]]:
"""Find tokens with duplicate names."""
seen: Dict[str, List[DesignToken]] = {}
for token in self.tokens:
if token.name not in seen:
seen[token.name] = []
seen[token.name].append(token)
return {k: v for k, v in seen.items() if len(v) > 1}
def to_css(self) -> str:
"""Export as CSS custom properties."""
lines = [":root {"]
for token in sorted(self.tokens, key=lambda t: t.name):
var_name = token.to_css_var_name()
if token.description:
lines.append(f" /* {token.description} */")
lines.append(f" {var_name}: {token.value};")
lines.append("}")
return "\n".join(lines)
def to_scss(self) -> str:
"""Export as SCSS variables."""
lines = []
for token in sorted(self.tokens, key=lambda t: t.name):
var_name = token.to_scss_var_name()
if token.description:
lines.append(f"// {token.description}")
lines.append(f"{var_name}: {token.value};")
return "\n".join(lines)
def to_json(self) -> str:
"""Export as W3C Design Tokens JSON."""
result = {}
for token in self.tokens:
parts = token.normalize_name().split(".")
current = result
for part in parts[:-1]:
if part not in current:
current[part] = {}
current = current[part]
current[parts[-1]] = token.to_dict()
return json.dumps(result, indent=2)
def to_typescript(self) -> str:
"""Export as TypeScript constants."""
lines = ["export const tokens = {"]
for token in sorted(self.tokens, key=lambda t: t.name):
js_name = token.to_js_name()
value = f'"{token.value}"' if isinstance(token.value, str) else token.value
if token.description:
lines.append(f" /** {token.description} */")
lines.append(f" {js_name}: {value},")
lines.append("} as const;")
lines.append("")
lines.append("export type TokenKey = keyof typeof tokens;")
return "\n".join(lines)
def to_tailwind_config(self) -> str:
"""Export as Tailwind config extend object."""
# Group tokens by category for Tailwind structure
colors = self.filter_by_category(TokenCategory.COLORS)
spacing = self.filter_by_category(TokenCategory.SPACING)
lines = ["module.exports = {", " theme: {", " extend: {"]
if colors.tokens:
lines.append(" colors: {")
for token in colors.tokens:
name = token.name.replace("color.", "").replace("colors.", "")
lines.append(f' "{name}": "{token.value}",')
lines.append(" },")
if spacing.tokens:
lines.append(" spacing: {")
for token in spacing.tokens:
name = token.name.replace("spacing.", "").replace("space.", "")
lines.append(f' "{name}": "{token.value}",')
lines.append(" },")
lines.extend([" },", " },", "};"])
return "\n".join(lines)
def summary(self) -> Dict[str, Any]:
"""Get collection summary."""
return {
"total_tokens": len(self.tokens),
"categories": {cat.value: len(self.filter_by_category(cat))
for cat in self.get_categories()},
"types": {t.value: len(self.filter_by_type(t))
for t in self.get_types()},
"sources": self.sources,
"duplicates": len(self.get_duplicates()),
}
class TokenSource(ABC):
"""
Abstract base class for token ingestion from various sources.
Each token source implementation (CSS, SCSS, JSON, Figma, Tailwind, etc.)
handles extraction of design tokens from native file formats and converts
them into the standard design token format.
All implementations must provide:
- source_type: Identifier for the source type
- extract: Extraction logic to process source and return TokenCollection
"""
@property
@abstractmethod
def source_type(self) -> str:
"""
Return source type identifier (e.g., 'css', 'scss', 'figma', 'json').
"""
pass
@abstractmethod
async def extract(self, source: str) -> TokenCollection:
"""
Extract design tokens from source material.
Processes raw design material (CSS, JSON, Figma, etc.) and extracts
design tokens into a standardized TokenCollection.
Args:
source: Source location (file path, URL, or content string)
Returns:
TokenCollection: Extracted and processed tokens
"""
pass
def _create_source_id(self, file_path: str, line: int = 0) -> str:
"""Create source identifier string."""
if line:
return f"{self.source_type}:{file_path}:{line}"
return f"{self.source_type}:{file_path}"

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"""
CSS Token Source
Extracts design tokens from CSS custom properties (CSS variables).
Parses :root declarations and other CSS variable definitions.
"""
import re
from pathlib import Path
from typing import List, Optional, Tuple
from .base import DesignToken, TokenCollection, TokenSource, TokenType, TokenCategory
class CSSTokenSource(TokenSource):
"""
Extract tokens from CSS files.
Parses CSS custom properties defined in :root or other selectors.
Supports:
- :root { --color-primary: #3B82F6; }
- [data-theme="dark"] { --color-primary: #60A5FA; }
- Comments as descriptions
"""
@property
def source_type(self) -> str:
return "css"
async def extract(self, source: str) -> TokenCollection:
"""
Extract tokens from CSS file or content.
Args:
source: File path or CSS content string
Returns:
TokenCollection with extracted tokens
"""
# Determine if source is file path or content
if self._is_file_path(source):
file_path = Path(source)
if not file_path.exists():
raise FileNotFoundError(f"CSS file not found: {source}")
content = file_path.read_text(encoding="utf-8")
source_file = str(file_path.absolute())
else:
content = source
source_file = "<inline>"
tokens = self._parse_css(content, source_file)
return TokenCollection(
tokens=tokens,
name=f"CSS Tokens from {Path(source_file).name if source_file != '<inline>' else 'inline'}",
sources=[self._create_source_id(source_file)],
)
def _is_file_path(self, source: str) -> bool:
"""Check if source looks like a file path."""
# If it contains CSS syntax, it's content
if '{' in source or ':' in source and ';' in source:
return False
# If it ends with .css, it's a file
if source.endswith('.css'):
return True
# If path exists, it's a file
return Path(source).exists()
def _parse_css(self, content: str, source_file: str) -> List[DesignToken]:
"""Parse CSS content and extract custom properties."""
tokens = []
# Track line numbers
lines = content.split('\n')
line_map = self._build_line_map(content)
# Find all CSS variable declarations
# Pattern matches: --var-name: value;
var_pattern = re.compile(
r'(\/\*[^*]*\*\/\s*)?' # Optional preceding comment
r'(--[\w-]+)\s*:\s*' # Variable name
r'([^;]+);', # Value
re.MULTILINE
)
# Find variables in all rule blocks
for match in var_pattern.finditer(content):
comment = match.group(1)
var_name = match.group(2)
var_value = match.group(3).strip()
# Get line number
pos = match.start()
line_num = self._get_line_number(pos, line_map)
# Extract description from comment
description = ""
if comment:
description = self._clean_comment(comment)
# Get context (selector)
context = self._get_selector_context(content, pos)
# Create token
token = DesignToken(
name=self._normalize_var_name(var_name),
value=var_value,
description=description,
source=self._create_source_id(source_file, line_num),
source_file=source_file,
source_line=line_num,
original_name=var_name,
original_value=var_value,
)
# Add context as tag if not :root
if context and context != ":root":
token.tags.append(f"context:{context}")
tokens.append(token)
return tokens
def _build_line_map(self, content: str) -> List[int]:
"""Build map of character positions to line numbers."""
line_map = []
pos = 0
for i, line in enumerate(content.split('\n'), 1):
line_map.append(pos)
pos += len(line) + 1 # +1 for newline
return line_map
def _get_line_number(self, pos: int, line_map: List[int]) -> int:
"""Get line number for character position."""
for i, line_start in enumerate(line_map):
if i + 1 < len(line_map):
if line_start <= pos < line_map[i + 1]:
return i + 1
else:
return i + 1
return 1
def _normalize_var_name(self, var_name: str) -> str:
"""Convert CSS variable name to token name."""
# Remove -- prefix
name = var_name.lstrip('-')
# Convert kebab-case to dot notation
name = name.replace('-', '.')
return name
def _clean_comment(self, comment: str) -> str:
"""Extract text from CSS comment."""
if not comment:
return ""
# Remove /* and */
text = re.sub(r'/\*|\*/', '', comment)
# Clean whitespace
text = ' '.join(text.split())
return text.strip()
def _get_selector_context(self, content: str, pos: int) -> str:
"""Get the CSS selector context for a variable."""
# Find the opening brace before this position
before = content[:pos]
last_open = before.rfind('{')
if last_open == -1:
return ""
# Find the selector before the brace
selector_part = before[:last_open]
# Get last selector (after } or start)
last_close = selector_part.rfind('}')
if last_close != -1:
selector_part = selector_part[last_close + 1:]
# Clean up
selector = selector_part.strip()
# Handle multi-line selectors
selector = ' '.join(selector.split())
return selector
class CSSInlineExtractor:
"""
Extract inline styles from HTML/JSX for token candidate identification.
Finds style="" attributes and extracts values that could become tokens.
"""
# Patterns for extracting inline styles
STYLE_ATTR_PATTERN = re.compile(
r'style\s*=\s*["\']([^"\']+)["\']',
re.IGNORECASE
)
# JSX style object pattern
JSX_STYLE_PATTERN = re.compile(
r'style\s*=\s*\{\{([^}]+)\}\}',
re.MULTILINE
)
async def extract_candidates(self, source: str) -> List[Tuple[str, str, int]]:
"""
Extract inline style values as token candidates.
Returns list of (property, value, line_number) tuples.
"""
candidates = []
# Determine if file or content
if Path(source).exists():
content = Path(source).read_text(encoding="utf-8")
else:
content = source
lines = content.split('\n')
for i, line in enumerate(lines, 1):
# Check HTML style attribute
for match in self.STYLE_ATTR_PATTERN.finditer(line):
style_content = match.group(1)
for prop, value in self._parse_style_string(style_content):
if self._is_token_candidate(value):
candidates.append((prop, value, i))
# Check JSX style object
for match in self.JSX_STYLE_PATTERN.finditer(line):
style_content = match.group(1)
for prop, value in self._parse_jsx_style(style_content):
if self._is_token_candidate(value):
candidates.append((prop, value, i))
return candidates
def _parse_style_string(self, style: str) -> List[Tuple[str, str]]:
"""Parse CSS style string into property-value pairs."""
pairs = []
for declaration in style.split(';'):
if ':' in declaration:
prop, value = declaration.split(':', 1)
pairs.append((prop.strip(), value.strip()))
return pairs
def _parse_jsx_style(self, style: str) -> List[Tuple[str, str]]:
"""Parse JSX style object into property-value pairs."""
pairs = []
# Simple parsing for common cases
for part in style.split(','):
if ':' in part:
prop, value = part.split(':', 1)
prop = prop.strip().strip('"\'')
value = value.strip().strip('"\'')
# Convert camelCase to kebab-case
prop = re.sub(r'([a-z])([A-Z])', r'\1-\2', prop).lower()
pairs.append((prop, value))
return pairs
def _is_token_candidate(self, value: str) -> bool:
"""Check if value should be extracted as a token."""
value = value.strip().lower()
# Colors are always candidates
if re.match(r'^#[0-9a-f]{3,8}$', value):
return True
if re.match(r'^rgb[a]?\s*\(', value):
return True
if re.match(r'^hsl[a]?\s*\(', value):
return True
# Dimensions with common units
if re.match(r'^\d+(\.\d+)?(px|rem|em|%)$', value):
return True
# Skip variable references
if value.startswith('var('):
return False
# Skip inherit/initial/etc
if value in ('inherit', 'initial', 'unset', 'auto', 'none'):
return False
return False

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"""
JSON Token Source
Extracts design tokens from JSON/YAML files.
Supports W3C Design Tokens format and Style Dictionary format.
"""
import json
import re
from pathlib import Path
from typing import List, Dict, Any, Optional
from .base import DesignToken, TokenCollection, TokenSource, TokenType, TokenCategory
class JSONTokenSource(TokenSource):
"""
Extract tokens from JSON/YAML token files.
Supports:
- W3C Design Tokens Community Group format
- Style Dictionary format
- Tokens Studio format
- Figma Tokens plugin format
- Generic nested JSON with $value
"""
@property
def source_type(self) -> str:
return "json"
async def extract(self, source: str) -> TokenCollection:
"""
Extract tokens from JSON file or content.
Args:
source: File path or JSON content string
Returns:
TokenCollection with extracted tokens
"""
if self._is_file_path(source):
file_path = Path(source)
if not file_path.exists():
raise FileNotFoundError(f"Token file not found: {source}")
content = file_path.read_text(encoding="utf-8")
source_file = str(file_path.absolute())
else:
content = source
source_file = "<inline>"
# Parse JSON
try:
data = json.loads(content)
except json.JSONDecodeError as e:
raise ValueError(f"Invalid JSON: {e}")
# Detect format and extract
tokens = self._extract_tokens(data, source_file)
return TokenCollection(
tokens=tokens,
name=f"JSON Tokens from {Path(source_file).name if source_file != '<inline>' else 'inline'}",
sources=[self._create_source_id(source_file)],
)
def _is_file_path(self, source: str) -> bool:
"""Check if source looks like a file path."""
if source.strip().startswith('{'):
return False
if source.endswith('.json') or source.endswith('.tokens.json'):
return True
return Path(source).exists()
def _extract_tokens(self, data: Dict, source_file: str) -> List[DesignToken]:
"""Extract tokens from parsed JSON."""
tokens = []
# Detect format
if self._is_w3c_format(data):
tokens = self._extract_w3c_tokens(data, source_file)
elif self._is_style_dictionary_format(data):
tokens = self._extract_style_dictionary_tokens(data, source_file)
elif self._is_tokens_studio_format(data):
tokens = self._extract_tokens_studio(data, source_file)
else:
# Generic nested format
tokens = self._extract_nested_tokens(data, source_file)
return tokens
def _is_w3c_format(self, data: Dict) -> bool:
"""Check if data follows W3C Design Tokens format."""
# W3C format uses $value and $type
def check_node(node: Any) -> bool:
if isinstance(node, dict):
if '$value' in node:
return True
return any(check_node(v) for v in node.values())
return False
return check_node(data)
def _is_style_dictionary_format(self, data: Dict) -> bool:
"""Check if data follows Style Dictionary format."""
# Style Dictionary uses 'value' without $
def check_node(node: Any) -> bool:
if isinstance(node, dict):
if 'value' in node and '$value' not in node:
return True
return any(check_node(v) for v in node.values())
return False
return check_node(data)
def _is_tokens_studio_format(self, data: Dict) -> bool:
"""Check if data follows Tokens Studio format."""
# Tokens Studio has specific structure with sets
return '$themes' in data or '$metadata' in data
def _extract_w3c_tokens(
self,
data: Dict,
source_file: str,
prefix: str = ""
) -> List[DesignToken]:
"""Extract tokens in W3C Design Tokens format."""
tokens = []
for key, value in data.items():
# Skip metadata keys
if key.startswith('$'):
continue
current_path = f"{prefix}.{key}" if prefix else key
if isinstance(value, dict):
if '$value' in value:
# This is a token
token = self._create_w3c_token(
current_path, value, source_file
)
tokens.append(token)
else:
# Nested group
tokens.extend(
self._extract_w3c_tokens(value, source_file, current_path)
)
return tokens
def _create_w3c_token(
self,
name: str,
data: Dict,
source_file: str
) -> DesignToken:
"""Create token from W3C format node."""
value = data.get('$value')
token_type = self._parse_w3c_type(data.get('$type', ''))
description = data.get('$description', '')
# Handle aliases/references
if isinstance(value, str) and value.startswith('{') and value.endswith('}'):
# This is a reference like {colors.primary}
pass # Keep as-is for now
# Get extensions
extensions = {}
if '$extensions' in data:
extensions = data['$extensions']
token = DesignToken(
name=name,
value=value,
type=token_type,
description=description,
source=self._create_source_id(source_file),
source_file=source_file,
extensions=extensions,
)
# Check for deprecated
if extensions.get('deprecated'):
token.deprecated = True
token.deprecated_message = extensions.get('deprecatedMessage', '')
return token
def _parse_w3c_type(self, type_str: str) -> TokenType:
"""Convert W3C type string to TokenType."""
type_map = {
'color': TokenType.COLOR,
'dimension': TokenType.DIMENSION,
'fontFamily': TokenType.FONT_FAMILY,
'fontWeight': TokenType.FONT_WEIGHT,
'duration': TokenType.DURATION,
'cubicBezier': TokenType.CUBIC_BEZIER,
'number': TokenType.NUMBER,
'shadow': TokenType.SHADOW,
'border': TokenType.BORDER,
'gradient': TokenType.GRADIENT,
'transition': TokenType.TRANSITION,
}
return type_map.get(type_str, TokenType.UNKNOWN)
def _extract_style_dictionary_tokens(
self,
data: Dict,
source_file: str,
prefix: str = ""
) -> List[DesignToken]:
"""Extract tokens in Style Dictionary format."""
tokens = []
for key, value in data.items():
current_path = f"{prefix}.{key}" if prefix else key
if isinstance(value, dict):
if 'value' in value:
# This is a token
token = DesignToken(
name=current_path,
value=value['value'],
description=value.get('comment', value.get('description', '')),
source=self._create_source_id(source_file),
source_file=source_file,
)
# Handle attributes
if 'attributes' in value:
attrs = value['attributes']
if 'category' in attrs:
token.tags.append(f"category:{attrs['category']}")
token.tags.append("style-dictionary")
tokens.append(token)
else:
# Nested group
tokens.extend(
self._extract_style_dictionary_tokens(
value, source_file, current_path
)
)
return tokens
def _extract_tokens_studio(
self,
data: Dict,
source_file: str
) -> List[DesignToken]:
"""Extract tokens from Tokens Studio format."""
tokens = []
# Tokens Studio has token sets as top-level keys
# Skip metadata keys
for set_name, set_data in data.items():
if set_name.startswith('$'):
continue
if isinstance(set_data, dict):
set_tokens = self._extract_tokens_studio_set(
set_data, source_file, set_name
)
for token in set_tokens:
token.group = set_name
tokens.extend(set_tokens)
return tokens
def _extract_tokens_studio_set(
self,
data: Dict,
source_file: str,
prefix: str = ""
) -> List[DesignToken]:
"""Extract tokens from a Tokens Studio set."""
tokens = []
for key, value in data.items():
current_path = f"{prefix}.{key}" if prefix else key
if isinstance(value, dict):
if 'value' in value and 'type' in value:
# This is a token
token = DesignToken(
name=current_path,
value=value['value'],
type=self._parse_tokens_studio_type(value.get('type', '')),
description=value.get('description', ''),
source=self._create_source_id(source_file),
source_file=source_file,
)
token.tags.append("tokens-studio")
tokens.append(token)
else:
# Nested group
tokens.extend(
self._extract_tokens_studio_set(
value, source_file, current_path
)
)
return tokens
def _parse_tokens_studio_type(self, type_str: str) -> TokenType:
"""Convert Tokens Studio type to TokenType."""
type_map = {
'color': TokenType.COLOR,
'sizing': TokenType.DIMENSION,
'spacing': TokenType.DIMENSION,
'borderRadius': TokenType.DIMENSION,
'borderWidth': TokenType.DIMENSION,
'fontFamilies': TokenType.FONT_FAMILY,
'fontWeights': TokenType.FONT_WEIGHT,
'fontSizes': TokenType.FONT_SIZE,
'lineHeights': TokenType.LINE_HEIGHT,
'letterSpacing': TokenType.LETTER_SPACING,
'paragraphSpacing': TokenType.DIMENSION,
'boxShadow': TokenType.SHADOW,
'opacity': TokenType.NUMBER,
'dimension': TokenType.DIMENSION,
'text': TokenType.STRING,
'other': TokenType.STRING,
}
return type_map.get(type_str, TokenType.UNKNOWN)
def _extract_nested_tokens(
self,
data: Dict,
source_file: str,
prefix: str = ""
) -> List[DesignToken]:
"""Extract tokens from generic nested JSON."""
tokens = []
for key, value in data.items():
current_path = f"{prefix}.{key}" if prefix else key
if isinstance(value, dict):
# Check if this looks like a token (has primitive values)
has_nested = any(isinstance(v, dict) for v in value.values())
if not has_nested and len(value) <= 3:
# Might be a simple token object
if 'value' in value:
tokens.append(DesignToken(
name=current_path,
value=value['value'],
source=self._create_source_id(source_file),
source_file=source_file,
))
else:
# Recurse
tokens.extend(
self._extract_nested_tokens(value, source_file, current_path)
)
else:
# Recurse into nested object
tokens.extend(
self._extract_nested_tokens(value, source_file, current_path)
)
elif isinstance(value, (str, int, float, bool)):
# Simple value - treat as token
tokens.append(DesignToken(
name=current_path,
value=value,
source=self._create_source_id(source_file),
source_file=source_file,
))
return tokens
class TokenExporter:
"""
Export tokens to various JSON formats.
"""
@staticmethod
def to_w3c(collection: TokenCollection) -> str:
"""Export to W3C Design Tokens format."""
result = {}
for token in collection.tokens:
parts = token.normalize_name().split('.')
current = result
for part in parts[:-1]:
if part not in current:
current[part] = {}
current = current[part]
current[parts[-1]] = {
"$value": token.value,
"$type": token.type.value,
}
if token.description:
current[parts[-1]]["$description"] = token.description
return json.dumps(result, indent=2)
@staticmethod
def to_style_dictionary(collection: TokenCollection) -> str:
"""Export to Style Dictionary format."""
result = {}
for token in collection.tokens:
parts = token.normalize_name().split('.')
current = result
for part in parts[:-1]:
if part not in current:
current[part] = {}
current = current[part]
current[parts[-1]] = {
"value": token.value,
}
if token.description:
current[parts[-1]]["comment"] = token.description
return json.dumps(result, indent=2)
@staticmethod
def to_flat(collection: TokenCollection) -> str:
"""Export to flat JSON object."""
result = {}
for token in collection.tokens:
result[token.name] = token.value
return json.dumps(result, indent=2)

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"""
Token Merge Module
Merge tokens from multiple sources with conflict resolution strategies.
"""
from dataclasses import dataclass, field
from datetime import datetime
from enum import Enum
from typing import List, Dict, Optional, Callable, Tuple
from .base import DesignToken, TokenCollection, TokenCategory
class MergeStrategy(str, Enum):
"""Token merge conflict resolution strategies."""
# Simple strategies
FIRST = "first" # Keep first occurrence
LAST = "last" # Keep last occurrence (override)
ERROR = "error" # Raise error on conflict
# Value-based strategies
PREFER_FIGMA = "prefer_figma" # Prefer Figma source
PREFER_CODE = "prefer_code" # Prefer code sources (CSS, SCSS)
PREFER_SPECIFIC = "prefer_specific" # Prefer more specific values
# Smart strategies
MERGE_METADATA = "merge_metadata" # Merge metadata, keep latest value
INTERACTIVE = "interactive" # Require user decision
@dataclass
class MergeConflict:
"""Represents a token name conflict during merge."""
token_name: str
existing: DesignToken
incoming: DesignToken
resolution: Optional[str] = None
resolved_token: Optional[DesignToken] = None
@dataclass
class MergeResult:
"""Result of a token merge operation."""
collection: TokenCollection
conflicts: List[MergeConflict] = field(default_factory=list)
stats: Dict[str, int] = field(default_factory=dict)
warnings: List[str] = field(default_factory=list)
def __post_init__(self):
if not self.stats:
self.stats = {
"total_tokens": 0,
"new_tokens": 0,
"updated_tokens": 0,
"conflicts_resolved": 0,
"conflicts_unresolved": 0,
}
class TokenMerger:
"""
Merge multiple token collections with conflict resolution.
Usage:
merger = TokenMerger(strategy=MergeStrategy.LAST)
result = merger.merge([collection1, collection2, collection3])
"""
# Source priority for PREFER_* strategies
SOURCE_PRIORITY = {
"figma": 100,
"css": 80,
"scss": 80,
"tailwind": 70,
"json": 60,
}
def __init__(
self,
strategy: MergeStrategy = MergeStrategy.LAST,
custom_resolver: Optional[Callable[[MergeConflict], DesignToken]] = None
):
"""
Initialize merger.
Args:
strategy: Default conflict resolution strategy
custom_resolver: Optional custom conflict resolver function
"""
self.strategy = strategy
self.custom_resolver = custom_resolver
def merge(
self,
collections: List[TokenCollection],
normalize_names: bool = True
) -> MergeResult:
"""
Merge multiple token collections.
Args:
collections: List of TokenCollections to merge
normalize_names: Whether to normalize token names before merging
Returns:
MergeResult with merged collection and conflict information
"""
result = MergeResult(
collection=TokenCollection(
name="Merged Tokens",
sources=[],
)
)
# Track tokens by normalized name
tokens_by_name: Dict[str, DesignToken] = {}
for collection in collections:
result.collection.sources.extend(collection.sources)
for token in collection.tokens:
# Normalize name if requested
name = token.normalize_name() if normalize_names else token.name
if name in tokens_by_name:
# Conflict detected
existing = tokens_by_name[name]
conflict = MergeConflict(
token_name=name,
existing=existing,
incoming=token,
)
# Resolve conflict
resolved = self._resolve_conflict(conflict)
conflict.resolved_token = resolved
if resolved:
tokens_by_name[name] = resolved
result.stats["conflicts_resolved"] += 1
result.stats["updated_tokens"] += 1
else:
result.stats["conflicts_unresolved"] += 1
result.warnings.append(
f"Unresolved conflict for token: {name}"
)
result.conflicts.append(conflict)
else:
# New token
tokens_by_name[name] = token
result.stats["new_tokens"] += 1
# Build final collection
result.collection.tokens = list(tokens_by_name.values())
result.stats["total_tokens"] = len(result.collection.tokens)
return result
def _resolve_conflict(self, conflict: MergeConflict) -> Optional[DesignToken]:
"""Resolve a single conflict based on strategy."""
# Try custom resolver first
if self.custom_resolver:
return self.custom_resolver(conflict)
# Apply strategy
if self.strategy == MergeStrategy.FIRST:
conflict.resolution = "kept_first"
return conflict.existing
elif self.strategy == MergeStrategy.LAST:
conflict.resolution = "used_last"
return self._update_token(conflict.incoming, conflict.existing)
elif self.strategy == MergeStrategy.ERROR:
conflict.resolution = "error"
raise ValueError(
f"Token conflict: {conflict.token_name} "
f"(existing: {conflict.existing.source}, "
f"incoming: {conflict.incoming.source})"
)
elif self.strategy == MergeStrategy.PREFER_FIGMA:
return self._prefer_source(conflict, "figma")
elif self.strategy == MergeStrategy.PREFER_CODE:
return self._prefer_code_source(conflict)
elif self.strategy == MergeStrategy.PREFER_SPECIFIC:
return self._prefer_specific_value(conflict)
elif self.strategy == MergeStrategy.MERGE_METADATA:
return self._merge_metadata(conflict)
elif self.strategy == MergeStrategy.INTERACTIVE:
# For interactive, we can't resolve automatically
conflict.resolution = "needs_input"
return None
return conflict.incoming
def _update_token(
self,
source: DesignToken,
base: DesignToken
) -> DesignToken:
"""Create updated token preserving some base metadata."""
# Create new token with source's value but enhanced metadata
updated = DesignToken(
name=source.name,
value=source.value,
type=source.type,
description=source.description or base.description,
source=source.source,
source_file=source.source_file,
source_line=source.source_line,
original_name=source.original_name,
original_value=source.original_value,
category=source.category,
tags=list(set(source.tags + base.tags)),
deprecated=source.deprecated or base.deprecated,
deprecated_message=source.deprecated_message or base.deprecated_message,
version=source.version,
updated_at=datetime.now(),
extensions={**base.extensions, **source.extensions},
)
return updated
def _prefer_source(
self,
conflict: MergeConflict,
preferred_source: str
) -> DesignToken:
"""Prefer token from specific source type."""
existing_source = conflict.existing.source.split(':')[0]
incoming_source = conflict.incoming.source.split(':')[0]
if incoming_source == preferred_source:
conflict.resolution = f"preferred_{preferred_source}"
return self._update_token(conflict.incoming, conflict.existing)
elif existing_source == preferred_source:
conflict.resolution = f"kept_{preferred_source}"
return conflict.existing
else:
# Neither is preferred, use last
conflict.resolution = "fallback_last"
return self._update_token(conflict.incoming, conflict.existing)
def _prefer_code_source(self, conflict: MergeConflict) -> DesignToken:
"""Prefer code sources (CSS, SCSS) over design sources."""
code_sources = {"css", "scss", "tailwind"}
existing_source = conflict.existing.source.split(':')[0]
incoming_source = conflict.incoming.source.split(':')[0]
existing_is_code = existing_source in code_sources
incoming_is_code = incoming_source in code_sources
if incoming_is_code and not existing_is_code:
conflict.resolution = "preferred_code"
return self._update_token(conflict.incoming, conflict.existing)
elif existing_is_code and not incoming_is_code:
conflict.resolution = "kept_code"
return conflict.existing
else:
# Both or neither are code, use priority
return self._prefer_by_priority(conflict)
def _prefer_by_priority(self, conflict: MergeConflict) -> DesignToken:
"""Choose based on source priority."""
existing_source = conflict.existing.source.split(':')[0]
incoming_source = conflict.incoming.source.split(':')[0]
existing_priority = self.SOURCE_PRIORITY.get(existing_source, 0)
incoming_priority = self.SOURCE_PRIORITY.get(incoming_source, 0)
if incoming_priority > existing_priority:
conflict.resolution = "higher_priority"
return self._update_token(conflict.incoming, conflict.existing)
else:
conflict.resolution = "kept_priority"
return conflict.existing
def _prefer_specific_value(self, conflict: MergeConflict) -> DesignToken:
"""Prefer more specific/concrete values."""
existing_value = str(conflict.existing.value).lower()
incoming_value = str(conflict.incoming.value).lower()
# Prefer concrete values over variables/references
existing_is_var = existing_value.startswith('var(') or \
existing_value.startswith('$') or \
existing_value.startswith('{')
incoming_is_var = incoming_value.startswith('var(') or \
incoming_value.startswith('$') or \
incoming_value.startswith('{')
if incoming_is_var and not existing_is_var:
conflict.resolution = "kept_concrete"
return conflict.existing
elif existing_is_var and not incoming_is_var:
conflict.resolution = "preferred_concrete"
return self._update_token(conflict.incoming, conflict.existing)
# Prefer hex colors over named colors
existing_is_hex = existing_value.startswith('#')
incoming_is_hex = incoming_value.startswith('#')
if incoming_is_hex and not existing_is_hex:
conflict.resolution = "preferred_hex"
return self._update_token(conflict.incoming, conflict.existing)
elif existing_is_hex and not incoming_is_hex:
conflict.resolution = "kept_hex"
return conflict.existing
# Default to last
conflict.resolution = "fallback_last"
return self._update_token(conflict.incoming, conflict.existing)
def _merge_metadata(self, conflict: MergeConflict) -> DesignToken:
"""Merge metadata from both tokens, keep latest value."""
conflict.resolution = "merged_metadata"
# Use incoming value but merge all metadata
merged_tags = list(set(
conflict.existing.tags + conflict.incoming.tags
))
merged_extensions = {
**conflict.existing.extensions,
**conflict.incoming.extensions
}
# Track both sources
merged_extensions['dss'] = merged_extensions.get('dss', {})
merged_extensions['dss']['previousSources'] = [
conflict.existing.source,
conflict.incoming.source
]
return DesignToken(
name=conflict.incoming.name,
value=conflict.incoming.value,
type=conflict.incoming.type or conflict.existing.type,
description=conflict.incoming.description or conflict.existing.description,
source=conflict.incoming.source,
source_file=conflict.incoming.source_file,
source_line=conflict.incoming.source_line,
original_name=conflict.incoming.original_name,
original_value=conflict.incoming.original_value,
category=conflict.incoming.category or conflict.existing.category,
tags=merged_tags,
deprecated=conflict.incoming.deprecated or conflict.existing.deprecated,
deprecated_message=conflict.incoming.deprecated_message or conflict.existing.deprecated_message,
version=conflict.incoming.version,
updated_at=datetime.now(),
extensions=merged_extensions,
)
class TokenDiff:
"""
Compare two token collections and find differences.
"""
@staticmethod
def diff(
source: TokenCollection,
target: TokenCollection
) -> Dict[str, List]:
"""
Compare two token collections.
Returns:
Dict with 'added', 'removed', 'changed', 'unchanged' lists
"""
source_by_name = {t.normalize_name(): t for t in source.tokens}
target_by_name = {t.normalize_name(): t for t in target.tokens}
source_names = set(source_by_name.keys())
target_names = set(target_by_name.keys())
result = {
'added': [], # In target but not source
'removed': [], # In source but not target
'changed': [], # In both but different value
'unchanged': [], # In both with same value
}
# Find added (in target, not in source)
for name in target_names - source_names:
result['added'].append(target_by_name[name])
# Find removed (in source, not in target)
for name in source_names - target_names:
result['removed'].append(source_by_name[name])
# Find changed/unchanged (in both)
for name in source_names & target_names:
source_token = source_by_name[name]
target_token = target_by_name[name]
if str(source_token.value) != str(target_token.value):
result['changed'].append({
'name': name,
'old_value': source_token.value,
'new_value': target_token.value,
'source_token': source_token,
'target_token': target_token,
})
else:
result['unchanged'].append(source_token)
return result
@staticmethod
def summary(diff_result: Dict[str, List]) -> str:
"""Generate human-readable diff summary."""
lines = ["Token Diff Summary:", "=" * 40]
if diff_result['added']:
lines.append(f"\n+ Added ({len(diff_result['added'])}):")
for token in diff_result['added'][:10]:
lines.append(f" + {token.name}: {token.value}")
if len(diff_result['added']) > 10:
lines.append(f" ... and {len(diff_result['added']) - 10} more")
if diff_result['removed']:
lines.append(f"\n- Removed ({len(diff_result['removed'])}):")
for token in diff_result['removed'][:10]:
lines.append(f" - {token.name}: {token.value}")
if len(diff_result['removed']) > 10:
lines.append(f" ... and {len(diff_result['removed']) - 10} more")
if diff_result['changed']:
lines.append(f"\n~ Changed ({len(diff_result['changed'])}):")
for change in diff_result['changed'][:10]:
lines.append(
f" ~ {change['name']}: {change['old_value']} → {change['new_value']}"
)
if len(diff_result['changed']) > 10:
lines.append(f" ... and {len(diff_result['changed']) - 10} more")
lines.append(f"\n Unchanged: {len(diff_result['unchanged'])}")
return "\n".join(lines)

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"""
SCSS Token Source
Extracts design tokens from SCSS/Sass variables.
Supports $variable declarations and @use module variables.
"""
import re
from pathlib import Path
from typing import List, Dict, Optional
from .base import DesignToken, TokenCollection, TokenSource
class SCSSTokenSource(TokenSource):
"""
Extract tokens from SCSS/Sass files.
Parses:
- $variable: value;
- $variable: value !default;
- // Comment descriptions
- @use module variables
- Maps: $colors: (primary: #3B82F6, secondary: #10B981);
"""
@property
def source_type(self) -> str:
return "scss"
async def extract(self, source: str) -> TokenCollection:
"""
Extract tokens from SCSS file or content.
Args:
source: File path or SCSS content string
Returns:
TokenCollection with extracted tokens
"""
if self._is_file_path(source):
file_path = Path(source)
if not file_path.exists():
raise FileNotFoundError(f"SCSS file not found: {source}")
content = file_path.read_text(encoding="utf-8")
source_file = str(file_path.absolute())
else:
content = source
source_file = "<inline>"
tokens = []
# Extract simple variables
tokens.extend(self._parse_variables(content, source_file))
# Extract map variables
tokens.extend(self._parse_maps(content, source_file))
return TokenCollection(
tokens=tokens,
name=f"SCSS Tokens from {Path(source_file).name if source_file != '<inline>' else 'inline'}",
sources=[self._create_source_id(source_file)],
)
def _is_file_path(self, source: str) -> bool:
"""Check if source looks like a file path."""
if '$' in source and ':' in source:
return False
if source.endswith('.scss') or source.endswith('.sass'):
return True
return Path(source).exists()
def _parse_variables(self, content: str, source_file: str) -> List[DesignToken]:
"""Parse simple $variable declarations."""
tokens = []
lines = content.split('\n')
# Pattern for variable declarations
var_pattern = re.compile(
r'^\s*'
r'(\$[\w-]+)\s*:\s*' # Variable name
r'([^;!]+)' # Value
r'(\s*!default)?' # Optional !default
r'\s*;',
re.MULTILINE
)
# Track comments for descriptions
prev_comment = ""
for i, line in enumerate(lines, 1):
# Check for comment
comment_match = re.match(r'^\s*//\s*(.+)$', line)
if comment_match:
prev_comment = comment_match.group(1).strip()
continue
# Check for variable
var_match = var_pattern.match(line)
if var_match:
var_name = var_match.group(1)
var_value = var_match.group(2).strip()
is_default = bool(var_match.group(3))
# Skip if value is a map (handled separately)
if var_value.startswith('(') and var_value.endswith(')'):
prev_comment = ""
continue
# Skip if value references another variable that we can't resolve
if var_value.startswith('$') and '(' not in var_value:
# It's a simple variable reference, try to extract
pass
token = DesignToken(
name=self._normalize_var_name(var_name),
value=self._process_value(var_value),
description=prev_comment,
source=self._create_source_id(source_file, i),
source_file=source_file,
source_line=i,
original_name=var_name,
original_value=var_value,
)
if is_default:
token.tags.append("default")
tokens.append(token)
prev_comment = ""
else:
# Reset comment if line doesn't match
if line.strip() and not line.strip().startswith('//'):
prev_comment = ""
return tokens
def _parse_maps(self, content: str, source_file: str) -> List[DesignToken]:
"""Parse SCSS map declarations."""
tokens = []
# Pattern for map declarations (handles multi-line)
map_pattern = re.compile(
r'\$(\w[\w-]*)\s*:\s*\(([\s\S]*?)\)\s*;',
re.MULTILINE
)
for match in map_pattern.finditer(content):
map_name = match.group(1)
map_content = match.group(2)
# Get line number
line_num = content[:match.start()].count('\n') + 1
# Parse map entries
entries = self._parse_map_entries(map_content)
for key, value in entries.items():
token = DesignToken(
name=f"{self._normalize_var_name('$' + map_name)}.{key}",
value=self._process_value(value),
source=self._create_source_id(source_file, line_num),
source_file=source_file,
source_line=line_num,
original_name=f"${map_name}.{key}",
original_value=value,
)
token.tags.append("from-map")
tokens.append(token)
return tokens
def _parse_map_entries(self, map_content: str) -> Dict[str, str]:
"""Parse entries from a SCSS map."""
entries = {}
# Handle nested maps and simple key-value pairs
# This is a simplified parser for common cases
# Remove comments
map_content = re.sub(r'//[^\n]*', '', map_content)
# Split by comma (not inside parentheses)
depth = 0
current = ""
parts = []
for char in map_content:
if char == '(':
depth += 1
current += char
elif char == ')':
depth -= 1
current += char
elif char == ',' and depth == 0:
parts.append(current.strip())
current = ""
else:
current += char
if current.strip():
parts.append(current.strip())
# Parse each part
for part in parts:
if ':' in part:
key, value = part.split(':', 1)
key = key.strip().strip('"\'')
value = value.strip()
entries[key] = value
return entries
def _normalize_var_name(self, var_name: str) -> str:
"""Convert SCSS variable name to token name."""
# Remove $ prefix
name = var_name.lstrip('$')
# Convert kebab-case and underscores to dots
name = re.sub(r'[-_]', '.', name)
return name.lower()
def _process_value(self, value: str) -> str:
"""Process SCSS value for token storage."""
value = value.strip()
# Handle function calls (keep as-is for now)
if '(' in value and ')' in value:
return value
# Handle quotes
if (value.startswith('"') and value.endswith('"')) or \
(value.startswith("'") and value.endswith("'")):
return value[1:-1]
return value
class SCSSVariableResolver:
"""
Resolve SCSS variable references.
Builds a dependency graph and resolves $var references to actual values.
"""
def __init__(self):
self.variables: Dict[str, str] = {}
self.resolved: Dict[str, str] = {}
def add_variable(self, name: str, value: str) -> None:
"""Add a variable to the resolver."""
self.variables[name] = value
def resolve(self, name: str) -> Optional[str]:
"""Resolve a variable to its final value."""
if name in self.resolved:
return self.resolved[name]
value = self.variables.get(name)
if not value:
return None
# Check if value references other variables
if '$' in value:
resolved_value = self._resolve_references(value)
self.resolved[name] = resolved_value
return resolved_value
self.resolved[name] = value
return value
def _resolve_references(self, value: str, depth: int = 0) -> str:
"""Recursively resolve variable references in a value."""
if depth > 10: # Prevent infinite loops
return value
# Find variable references
var_pattern = re.compile(r'\$[\w-]+')
def replace_var(match):
var_name = match.group(0)
resolved = self.resolve(var_name.lstrip('$'))
return resolved if resolved else var_name
return var_pattern.sub(replace_var, value)
def resolve_all(self) -> Dict[str, str]:
"""Resolve all variables."""
for name in self.variables:
self.resolve(name)
return self.resolved

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"""
Tailwind Token Source
Extracts design tokens from Tailwind CSS configuration files.
Supports tailwind.config.js/ts and CSS-based Tailwind v4 configurations.
"""
import re
import json
from pathlib import Path
from typing import List, Dict, Any, Optional
from .base import DesignToken, TokenCollection, TokenSource, TokenCategory
class TailwindTokenSource(TokenSource):
"""
Extract tokens from Tailwind CSS configuration.
Parses:
- tailwind.config.js/ts (theme and extend sections)
- Tailwind v4 CSS-based configuration
- CSS custom properties from Tailwind output
"""
# Tailwind category mappings
TAILWIND_CATEGORIES = {
'colors': TokenCategory.COLORS,
'backgroundColor': TokenCategory.COLORS,
'textColor': TokenCategory.COLORS,
'borderColor': TokenCategory.COLORS,
'spacing': TokenCategory.SPACING,
'padding': TokenCategory.SPACING,
'margin': TokenCategory.SPACING,
'gap': TokenCategory.SPACING,
'fontSize': TokenCategory.TYPOGRAPHY,
'fontFamily': TokenCategory.TYPOGRAPHY,
'fontWeight': TokenCategory.TYPOGRAPHY,
'lineHeight': TokenCategory.TYPOGRAPHY,
'letterSpacing': TokenCategory.TYPOGRAPHY,
'width': TokenCategory.SIZING,
'height': TokenCategory.SIZING,
'maxWidth': TokenCategory.SIZING,
'maxHeight': TokenCategory.SIZING,
'minWidth': TokenCategory.SIZING,
'minHeight': TokenCategory.SIZING,
'borderRadius': TokenCategory.BORDERS,
'borderWidth': TokenCategory.BORDERS,
'boxShadow': TokenCategory.SHADOWS,
'dropShadow': TokenCategory.SHADOWS,
'opacity': TokenCategory.OPACITY,
'zIndex': TokenCategory.Z_INDEX,
'transitionDuration': TokenCategory.MOTION,
'transitionTimingFunction': TokenCategory.MOTION,
'animation': TokenCategory.MOTION,
'screens': TokenCategory.BREAKPOINTS,
}
@property
def source_type(self) -> str:
return "tailwind"
async def extract(self, source: str) -> TokenCollection:
"""
Extract tokens from Tailwind config.
Args:
source: Path to tailwind.config.js/ts or directory containing it
Returns:
TokenCollection with extracted tokens
"""
config_path = self._find_config(source)
if not config_path:
raise FileNotFoundError(f"Tailwind config not found in: {source}")
content = config_path.read_text(encoding="utf-8")
source_file = str(config_path.absolute())
# Parse based on file type
if config_path.suffix in ('.js', '.cjs', '.mjs', '.ts'):
tokens = self._parse_js_config(content, source_file)
elif config_path.suffix == '.css':
tokens = self._parse_css_config(content, source_file)
else:
tokens = []
return TokenCollection(
tokens=tokens,
name=f"Tailwind Tokens from {config_path.name}",
sources=[self._create_source_id(source_file)],
)
def _find_config(self, source: str) -> Optional[Path]:
"""Find Tailwind config file."""
path = Path(source)
# If it's a file, use it directly
if path.is_file():
return path
# If it's a directory, look for config files
if path.is_dir():
config_names = [
'tailwind.config.js',
'tailwind.config.cjs',
'tailwind.config.mjs',
'tailwind.config.ts',
]
for name in config_names:
config_path = path / name
if config_path.exists():
return config_path
return None
def _parse_js_config(self, content: str, source_file: str) -> List[DesignToken]:
"""Parse JavaScript/TypeScript Tailwind config."""
tokens = []
# Extract theme object using regex (simplified parsing)
# This handles common patterns but may not cover all edge cases
# Look for theme: { ... } or theme.extend: { ... }
theme_match = re.search(
r'theme\s*:\s*\{([\s\S]*?)\n\s*\}(?=\s*[,}])',
content
)
extend_match = re.search(
r'extend\s*:\s*\{([\s\S]*?)\n\s{4}\}',
content
)
if extend_match:
theme_content = extend_match.group(1)
tokens.extend(self._parse_theme_object(theme_content, source_file, "extend"))
if theme_match and not extend_match:
theme_content = theme_match.group(1)
tokens.extend(self._parse_theme_object(theme_content, source_file, "theme"))
return tokens
def _parse_theme_object(self, content: str, source_file: str, prefix: str) -> List[DesignToken]:
"""Parse theme object content."""
tokens = []
# Find property blocks like: colors: { primary: '#3B82F6', ... }
prop_pattern = re.compile(
r"(\w+)\s*:\s*\{([^{}]*(?:\{[^{}]*\}[^{}]*)*)\}",
re.MULTILINE
)
for match in prop_pattern.finditer(content):
category_name = match.group(1)
category_content = match.group(2)
category = self.TAILWIND_CATEGORIES.get(
category_name, TokenCategory.OTHER
)
# Parse values in this category
tokens.extend(
self._parse_category_values(
category_name,
category_content,
source_file,
category
)
)
return tokens
def _parse_category_values(
self,
category_name: str,
content: str,
source_file: str,
category: TokenCategory
) -> List[DesignToken]:
"""Parse values within a category."""
tokens = []
# Match key: value pairs
# Handles: key: 'value', key: "value", key: value, 'key': value
value_pattern = re.compile(
r"['\"]?(\w[\w-]*)['\"]?\s*:\s*['\"]?([^,'\"}\n]+)['\"]?",
)
for match in value_pattern.finditer(content):
key = match.group(1)
value = match.group(2).strip()
# Skip function calls and complex values for now
if '(' in value or '{' in value:
continue
# Skip references to other values
if value.startswith('colors.') or value.startswith('theme('):
continue
token = DesignToken(
name=f"{category_name}.{key}",
value=value,
source=self._create_source_id(source_file),
source_file=source_file,
original_name=f"{category_name}.{key}",
original_value=value,
category=category,
)
token.tags.append("tailwind")
tokens.append(token)
return tokens
def _parse_css_config(self, content: str, source_file: str) -> List[DesignToken]:
"""Parse Tailwind v4 CSS-based configuration."""
tokens = []
# Tailwind v4 uses @theme directive
theme_match = re.search(
r'@theme\s*\{([\s\S]*?)\}',
content
)
if theme_match:
theme_content = theme_match.group(1)
# Parse CSS custom properties
var_pattern = re.compile(
r'(--[\w-]+)\s*:\s*([^;]+);'
)
for match in var_pattern.finditer(theme_content):
var_name = match.group(1)
var_value = match.group(2).strip()
# Determine category from variable name
category = self._category_from_var_name(var_name)
token = DesignToken(
name=self._normalize_var_name(var_name),
value=var_value,
source=self._create_source_id(source_file),
source_file=source_file,
original_name=var_name,
original_value=var_value,
category=category,
)
token.tags.append("tailwind-v4")
tokens.append(token)
return tokens
def _normalize_var_name(self, var_name: str) -> str:
"""Convert CSS variable name to token name."""
name = var_name.lstrip('-')
name = name.replace('-', '.')
return name.lower()
def _category_from_var_name(self, var_name: str) -> TokenCategory:
"""Determine category from variable name."""
name_lower = var_name.lower()
if 'color' in name_lower or 'bg' in name_lower:
return TokenCategory.COLORS
if 'spacing' in name_lower or 'gap' in name_lower:
return TokenCategory.SPACING
if 'font' in name_lower or 'text' in name_lower:
return TokenCategory.TYPOGRAPHY
if 'radius' in name_lower or 'border' in name_lower:
return TokenCategory.BORDERS
if 'shadow' in name_lower:
return TokenCategory.SHADOWS
return TokenCategory.OTHER
class TailwindClassExtractor:
"""
Extract Tailwind class usage from source files.
Identifies Tailwind utility classes for analysis and migration.
"""
# Common Tailwind class prefixes
TAILWIND_PREFIXES = [
'bg-', 'text-', 'border-', 'ring-',
'p-', 'px-', 'py-', 'pt-', 'pr-', 'pb-', 'pl-',
'm-', 'mx-', 'my-', 'mt-', 'mr-', 'mb-', 'ml-',
'w-', 'h-', 'min-w-', 'min-h-', 'max-w-', 'max-h-',
'flex-', 'grid-', 'gap-',
'font-', 'text-', 'leading-', 'tracking-',
'rounded-', 'shadow-', 'opacity-',
'z-', 'transition-', 'duration-', 'ease-',
]
async def extract_usage(self, source: str) -> Dict[str, List[str]]:
"""
Extract Tailwind class usage from file.
Returns dict mapping class categories to list of used classes.
"""
if Path(source).exists():
content = Path(source).read_text(encoding="utf-8")
else:
content = source
usage: Dict[str, List[str]] = {}
# Find className or class attributes
class_pattern = re.compile(
r'(?:className|class)\s*=\s*["\']([^"\']+)["\']'
)
for match in class_pattern.finditer(content):
classes = match.group(1).split()
for cls in classes:
# Check if it's a Tailwind class
for prefix in self.TAILWIND_PREFIXES:
if cls.startswith(prefix):
category = prefix.rstrip('-')
if category not in usage:
usage[category] = []
if cls not in usage[category]:
usage[category].append(cls)
break
return usage

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"""
DSS MCP Server
Model Context Protocol server for Design System Server.
Provides project-isolated context and tools to Claude chat instances.
"""
__version__ = "0.8.0"

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"""
DSS MCP Audit Module
Tracks all operations for compliance, debugging, and audit trails.
Maintains immutable logs of all state-changing operations with before/after snapshots.
"""
import json
import uuid
from typing import Optional, Dict, Any
from datetime import datetime
from enum import Enum
from storage.json_store import ActivityLog, append_jsonl, read_jsonl, SYSTEM_DIR # JSON storage
class AuditEventType(Enum):
"""Types of auditable events"""
TOOL_CALL = "tool_call"
CREDENTIAL_ACCESS = "credential_access"
CREDENTIAL_CREATE = "credential_create"
CREDENTIAL_DELETE = "credential_delete"
PROJECT_CREATE = "project_create"
PROJECT_UPDATE = "project_update"
PROJECT_DELETE = "project_delete"
COMPONENT_SYNC = "component_sync"
TOKEN_SYNC = "token_sync"
STATE_TRANSITION = "state_transition"
ERROR = "error"
SECURITY_EVENT = "security_event"
class AuditLog:
"""
Persistent operation audit trail.
All operations are logged with:
- Full operation details
- User who performed it
- Timestamp
- Before/after state snapshots
- Result status
"""
@staticmethod
def log_operation(
event_type: AuditEventType,
operation_name: str,
operation_id: str,
user_id: Optional[str],
project_id: Optional[str],
args: Dict[str, Any],
result: Optional[Dict[str, Any]] = None,
error: Optional[str] = None,
before_state: Optional[Dict[str, Any]] = None,
after_state: Optional[Dict[str, Any]] = None
) -> str:
"""
Log an operation to the audit trail.
Args:
event_type: Type of event
operation_name: Human-readable operation name
operation_id: Unique operation ID
user_id: User who performed the operation
project_id: Associated project ID
args: Operation arguments (will be scrubbed of sensitive data)
result: Operation result
error: Error message if operation failed
before_state: State before operation
after_state: State after operation
Returns:
Audit log entry ID
"""
audit_id = str(uuid.uuid4())
# Scrub sensitive data from args
scrubbed_args = AuditLog._scrub_sensitive_data(args)
with get_connection() as conn:
conn.execute("""
INSERT INTO audit_log (
id, event_type, operation_name, operation_id, user_id,
project_id, args, result, error, before_state, after_state,
created_at
) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
""", (
audit_id,
event_type.value,
operation_name,
operation_id,
user_id,
project_id,
json.dumps(scrubbed_args),
json.dumps(result) if result else None,
error,
json.dumps(before_state) if before_state else None,
json.dumps(after_state) if after_state else None,
datetime.utcnow().isoformat()
))
return audit_id
@staticmethod
def get_operation_history(
project_id: Optional[str] = None,
user_id: Optional[str] = None,
operation_name: Optional[str] = None,
limit: int = 100,
offset: int = 0
) -> list:
"""
Get operation history with optional filtering.
Args:
project_id: Filter by project
user_id: Filter by user
operation_name: Filter by operation
limit: Number of records to return
offset: Pagination offset
Returns:
List of audit log entries
"""
with get_connection() as conn:
cursor = conn.cursor()
query = "SELECT * FROM audit_log WHERE 1=1"
params = []
if project_id:
query += " AND project_id = ?"
params.append(project_id)
if user_id:
query += " AND user_id = ?"
params.append(user_id)
if operation_name:
query += " AND operation_name = ?"
params.append(operation_name)
query += " ORDER BY created_at DESC LIMIT ? OFFSET ?"
params.extend([limit, offset])
cursor.execute(query, params)
return [dict(row) for row in cursor.fetchall()]
@staticmethod
def get_audit_trail(
start_date: datetime,
end_date: datetime,
event_type: Optional[str] = None
) -> list:
"""
Get audit trail for a date range.
Useful for compliance reports and security audits.
Args:
start_date: Start of date range
end_date: End of date range
event_type: Optional event type filter
Returns:
List of audit log entries
"""
with get_connection() as conn:
cursor = conn.cursor()
query = """
SELECT * FROM audit_log
WHERE created_at >= ? AND created_at <= ?
"""
params = [start_date.isoformat(), end_date.isoformat()]
if event_type:
query += " AND event_type = ?"
params.append(event_type)
query += " ORDER BY created_at DESC"
cursor.execute(query, params)
return [dict(row) for row in cursor.fetchall()]
@staticmethod
def get_user_activity(
user_id: str,
days: int = 30
) -> Dict[str, Any]:
"""
Get user activity summary for the past N days.
Args:
user_id: User to analyze
days: Number of past days to include
Returns:
Activity summary including operation counts and patterns
"""
from datetime import timedelta
start_date = datetime.utcnow() - timedelta(days=days)
with get_connection() as conn:
cursor = conn.cursor()
# Get total operations
cursor.execute("""
SELECT COUNT(*) FROM audit_log
WHERE user_id = ? AND created_at >= ?
""", (user_id, start_date.isoformat()))
total_ops = cursor.fetchone()[0]
# Get operations by type
cursor.execute("""
SELECT event_type, COUNT(*) as count
FROM audit_log
WHERE user_id = ? AND created_at >= ?
GROUP BY event_type
ORDER BY count DESC
""", (user_id, start_date.isoformat()))
ops_by_type = {row[0]: row[1] for row in cursor.fetchall()}
# Get error count
cursor.execute("""
SELECT COUNT(*) FROM audit_log
WHERE user_id = ? AND created_at >= ? AND error IS NOT NULL
""", (user_id, start_date.isoformat()))
errors = cursor.fetchone()[0]
# Get unique projects
cursor.execute("""
SELECT COUNT(DISTINCT project_id) FROM audit_log
WHERE user_id = ? AND created_at >= ?
""", (user_id, start_date.isoformat()))
projects = cursor.fetchone()[0]
return {
"user_id": user_id,
"days": days,
"total_operations": total_ops,
"operations_by_type": ops_by_type,
"errors": errors,
"projects_touched": projects,
"average_ops_per_day": round(total_ops / days, 2) if days > 0 else 0
}
@staticmethod
def search_audit_log(
search_term: str,
limit: int = 50
) -> list:
"""
Search audit log by operation name or error message.
Args:
search_term: Term to search for
limit: Maximum results
Returns:
List of matching audit entries
"""
with get_connection() as conn:
cursor = conn.cursor()
cursor.execute("""
SELECT * FROM audit_log
WHERE operation_name LIKE ? OR error LIKE ?
ORDER BY created_at DESC
LIMIT ?
""", (f"%{search_term}%", f"%{search_term}%", limit))
return [dict(row) for row in cursor.fetchall()]
@staticmethod
def _scrub_sensitive_data(data: Dict[str, Any]) -> Dict[str, Any]:
"""
Remove sensitive data from arguments for safe logging.
Removes API tokens, passwords, and other secrets.
"""
sensitive_keys = {
'token', 'api_key', 'secret', 'password',
'credential', 'auth', 'figma_token', 'encrypted_data'
}
scrubbed = {}
for key, value in data.items():
if any(sensitive in key.lower() for sensitive in sensitive_keys):
scrubbed[key] = "***REDACTED***"
elif isinstance(value, dict):
scrubbed[key] = AuditLog._scrub_sensitive_data(value)
elif isinstance(value, list):
scrubbed[key] = [
AuditLog._scrub_sensitive_data(item)
if isinstance(item, dict) else item
for item in value
]
else:
scrubbed[key] = value
return scrubbed
@staticmethod
def ensure_audit_log_table():
"""Ensure audit_log table exists"""
with get_connection() as conn:
conn.execute("""
CREATE TABLE IF NOT EXISTS audit_log (
id TEXT PRIMARY KEY,
event_type TEXT NOT NULL,
operation_name TEXT NOT NULL,
operation_id TEXT,
user_id TEXT,
project_id TEXT,
args TEXT,
result TEXT,
error TEXT,
before_state TEXT,
after_state TEXT,
created_at TEXT DEFAULT CURRENT_TIMESTAMP
)
""")
conn.execute(
"CREATE INDEX IF NOT EXISTS idx_audit_user ON audit_log(user_id)"
)
conn.execute(
"CREATE INDEX IF NOT EXISTS idx_audit_project ON audit_log(project_id)"
)
conn.execute(
"CREATE INDEX IF NOT EXISTS idx_audit_type ON audit_log(event_type)"
)
conn.execute(
"CREATE INDEX IF NOT EXISTS idx_audit_date ON audit_log(created_at)"
)
# Initialize table on import
AuditLog.ensure_audit_log_table()

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"""
MCP Server Configuration
Loads configuration from environment variables and provides settings
for the MCP server, integrations, and security.
"""
import os
from pathlib import Path
from typing import Optional
from dotenv import load_dotenv
from cryptography.fernet import Fernet
# Load environment variables
load_dotenv()
# Base paths
PROJECT_ROOT = Path(__file__).parent.parent.parent
TOOLS_DIR = PROJECT_ROOT / "tools"
STORAGE_DIR = PROJECT_ROOT / "tools" / "storage"
CACHE_DIR = PROJECT_ROOT / os.getenv("DSS_CACHE_DIR", ".dss/cache")
class MCPConfig:
"""MCP Server Configuration"""
# Server Settings
HOST: str = os.getenv("DSS_MCP_HOST", "127.0.0.1")
PORT: int = int(os.getenv("DSS_MCP_PORT", "3457"))
# Database
DATABASE_PATH: str = os.getenv(
"DATABASE_PATH",
str(STORAGE_DIR / "dss.db")
)
# Context Caching
CONTEXT_CACHE_TTL: int = int(os.getenv("DSS_CONTEXT_CACHE_TTL", "300")) # 5 minutes
# Encryption
ENCRYPTION_KEY: Optional[str] = os.getenv("DSS_ENCRYPTION_KEY")
@classmethod
def get_cipher(cls) -> Optional[Fernet]:
"""Get Fernet cipher for encryption/decryption"""
if not cls.ENCRYPTION_KEY:
return None
return Fernet(cls.ENCRYPTION_KEY.encode())
@classmethod
def generate_encryption_key(cls) -> str:
"""Generate a new encryption key"""
return Fernet.generate_key().decode()
# Redis/Celery for worker pool
REDIS_URL: str = os.getenv("REDIS_URL", "redis://localhost:6379/0")
CELERY_BROKER_URL: str = os.getenv("CELERY_BROKER_URL", "redis://localhost:6379/0")
CELERY_RESULT_BACKEND: str = os.getenv("CELERY_RESULT_BACKEND", "redis://localhost:6379/0")
# Circuit Breaker
CIRCUIT_BREAKER_FAILURE_THRESHOLD: int = int(
os.getenv("CIRCUIT_BREAKER_FAILURE_THRESHOLD", "5")
)
CIRCUIT_BREAKER_TIMEOUT_SECONDS: int = int(
os.getenv("CIRCUIT_BREAKER_TIMEOUT_SECONDS", "60")
)
# Logging
LOG_LEVEL: str = os.getenv("LOG_LEVEL", "INFO").upper()
class IntegrationConfig:
"""External Integration Configuration"""
# Figma
FIGMA_TOKEN: Optional[str] = os.getenv("FIGMA_TOKEN")
FIGMA_CACHE_TTL: int = int(os.getenv("FIGMA_CACHE_TTL", "300"))
# Anthropic (for Sequential Thinking)
ANTHROPIC_API_KEY: Optional[str] = os.getenv("ANTHROPIC_API_KEY")
# Jira (defaults, can be overridden per-user)
JIRA_URL: Optional[str] = os.getenv("JIRA_URL")
JIRA_USERNAME: Optional[str] = os.getenv("JIRA_USERNAME")
JIRA_API_TOKEN: Optional[str] = os.getenv("JIRA_API_TOKEN")
# Confluence (defaults, can be overridden per-user)
CONFLUENCE_URL: Optional[str] = os.getenv("CONFLUENCE_URL")
CONFLUENCE_USERNAME: Optional[str] = os.getenv("CONFLUENCE_USERNAME")
CONFLUENCE_API_TOKEN: Optional[str] = os.getenv("CONFLUENCE_API_TOKEN")
# Singleton instances
mcp_config = MCPConfig()
integration_config = IntegrationConfig()
def validate_config() -> list[str]:
"""
Validate configuration and return list of warnings.
Returns:
List of warning messages for missing optional config
"""
warnings = []
if not mcp_config.ENCRYPTION_KEY:
warnings.append(
"DSS_ENCRYPTION_KEY not set. Integration credentials will not be encrypted. "
f"Generate one with: python -c \"from cryptography.fernet import Fernet; print(Fernet.generate_key().decode())\""
)
if not integration_config.ANTHROPIC_API_KEY:
warnings.append("ANTHROPIC_API_KEY not set. Sequential Thinking tools will not be available.")
if not integration_config.FIGMA_TOKEN:
warnings.append("FIGMA_TOKEN not set. Figma tools will not be available.")
return warnings
if __name__ == "__main__":
print("=== DSS MCP Configuration ===\n")
print(f"MCP Server: {mcp_config.HOST}:{mcp_config.PORT}")
print(f"Database: {mcp_config.DATABASE_PATH}")
print(f"Context Cache TTL: {mcp_config.CONTEXT_CACHE_TTL}s")
print(f"Encryption Key: {'✓ Set' if mcp_config.ENCRYPTION_KEY else '✗ Not Set'}")
print(f"Redis URL: {mcp_config.REDIS_URL}")
print(f"\nCircuit Breaker:")
print(f" Failure Threshold: {mcp_config.CIRCUIT_BREAKER_FAILURE_THRESHOLD}")
print(f" Timeout: {mcp_config.CIRCUIT_BREAKER_TIMEOUT_SECONDS}s")
print(f"\n=== Integration Configuration ===\n")
print(f"Figma Token: {'✓ Set' if integration_config.FIGMA_TOKEN else '✗ Not Set'}")
print(f"Anthropic API Key: {'✓ Set' if integration_config.ANTHROPIC_API_KEY else '✗ Not Set'}")
print(f"Jira URL: {integration_config.JIRA_URL or '✗ Not Set'}")
print(f"Confluence URL: {integration_config.CONFLUENCE_URL or '✗ Not Set'}")
warnings = validate_config()
if warnings:
print(f"\n⚠️ Warnings:")
for warning in warnings:
print(f" - {warning}")
else:
print(f"\n✓ Configuration is valid")

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dss/mcp/context/__init__.py Normal file
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"""
Project Context Manager
Provides cached, project-isolated context for Claude MCP sessions.
Loads all relevant project data (components, tokens, config, health, etc.)
and caches it for performance.
"""
import json
import asyncio
from datetime import datetime, timedelta
from dataclasses import dataclass, asdict
from typing import Dict, Any, Optional, List
from pathlib import Path
# Import from existing DSS modules
import sys
sys.path.insert(0, str(Path(__file__).parent.parent.parent))
from storage.json_store import Projects, Components, Tokens
from analyze.scanner import ProjectScanner
from ..config import mcp_config
@dataclass
class ProjectContext:
"""Complete project context for MCP sessions"""
project_id: str
name: str
description: Optional[str]
path: Optional[Path]
# Component data
components: List[Dict[str, Any]]
component_count: int
# Token/Style data
tokens: Dict[str, Any]
styles: List[Dict[str, Any]]
# Project configuration
config: Dict[str, Any]
# User's enabled integrations (user-scoped)
integrations: Dict[str, Any]
# Project health & metrics
health: Dict[str, Any]
stats: Dict[str, Any]
# Discovery/scan results
discovery: Dict[str, Any]
# Metadata
loaded_at: datetime
cache_expires_at: datetime
def to_dict(self) -> Dict[str, Any]:
"""Convert to dictionary for JSON serialization"""
data = asdict(self)
data['loaded_at'] = self.loaded_at.isoformat()
data['cache_expires_at'] = self.cache_expires_at.isoformat()
if self.path:
data['path'] = str(self.path)
return data
def is_expired(self) -> bool:
"""Check if cache has expired"""
return datetime.now() >= self.cache_expires_at
class ProjectContextManager:
"""
Manages project contexts with TTL-based caching.
Provides fast access to project data for MCP tools while ensuring
data freshness and project isolation.
"""
def __init__(self):
self._cache: Dict[str, ProjectContext] = {}
self._cache_ttl = timedelta(seconds=mcp_config.CONTEXT_CACHE_TTL)
async def get_context(
self,
project_id: str,
user_id: Optional[int] = None,
force_refresh: bool = False
) -> Optional[ProjectContext]:
"""
Get project context, using cache if available.
Args:
project_id: Project ID
user_id: User ID for loading user-scoped integrations
force_refresh: Force cache refresh
Returns:
ProjectContext or None if project not found
"""
# Check cache first
cache_key = f"{project_id}:{user_id or 'anonymous'}"
if not force_refresh and cache_key in self._cache:
ctx = self._cache[cache_key]
if not ctx.is_expired():
return ctx
# Load fresh context
context = await self._load_context(project_id, user_id)
if context:
self._cache[cache_key] = context
return context
async def _load_context(
self,
project_id: str,
user_id: Optional[int] = None
) -> Optional[ProjectContext]:
"""Load complete project context from database and filesystem"""
# Run database queries in thread pool to avoid blocking
loop = asyncio.get_event_loop()
# Load project metadata
project = await loop.run_in_executor(None, self._load_project, project_id)
if not project:
return None
# Load components, styles, stats in parallel
components_task = loop.run_in_executor(None, self._load_components, project_id)
styles_task = loop.run_in_executor(None, self._load_styles, project_id)
stats_task = loop.run_in_executor(None, self._load_stats, project_id)
integrations_task = loop.run_in_executor(None, self._load_integrations, project_id, user_id)
components = await components_task
styles = await styles_task
stats = await stats_task
integrations = await integrations_task
# Load tokens from filesystem if project has a path
tokens = {}
project_path = None
if project.get('figma_file_key'):
# Try to find project path based on naming convention
# (This can be enhanced based on actual project structure)
project_path = Path.cwd()
tokens = await loop.run_in_executor(None, self._load_tokens, project_path)
# Load discovery/scan data
discovery = await loop.run_in_executor(None, self._load_discovery, project_path)
# Compute health score
health = self._compute_health(components, tokens, stats)
# Build context
now = datetime.now()
context = ProjectContext(
project_id=project_id,
name=project['name'],
description=project.get('description'),
path=project_path,
components=components,
component_count=len(components),
tokens=tokens,
styles=styles,
config={
'figma_file_key': project.get('figma_file_key'),
'status': project.get('status', 'active')
},
integrations=integrations,
health=health,
stats=stats,
discovery=discovery,
loaded_at=now,
cache_expires_at=now + self._cache_ttl
)
return context
def _load_project(self, project_id: str) -> Optional[Dict[str, Any]]:
"""Load project metadata from database"""
try:
with get_connection() as conn:
row = conn.execute(
"SELECT * FROM projects WHERE id = ?",
(project_id,)
).fetchone()
if row:
return dict(row)
return None
except Exception as e:
print(f"Error loading project: {e}")
return None
def _load_components(self, project_id: str) -> List[Dict[str, Any]]:
"""Load all components for project"""
try:
with get_connection() as conn:
rows = conn.execute(
"""
SELECT id, name, figma_key, description,
properties, variants, code_generated,
created_at, updated_at
FROM components
WHERE project_id = ?
ORDER BY name
""",
(project_id,)
).fetchall()
components = []
for row in rows:
comp = dict(row)
# Parse JSON fields
if comp.get('properties'):
comp['properties'] = json.loads(comp['properties'])
if comp.get('variants'):
comp['variants'] = json.loads(comp['variants'])
components.append(comp)
return components
except Exception as e:
print(f"Error loading components: {e}")
return []
def _load_styles(self, project_id: str) -> List[Dict[str, Any]]:
"""Load all styles for project"""
try:
with get_connection() as conn:
rows = conn.execute(
"""
SELECT id, name, type, figma_key, properties, created_at
FROM styles
WHERE project_id = ?
ORDER BY type, name
""",
(project_id,)
).fetchall()
styles = []
for row in rows:
style = dict(row)
if style.get('properties'):
style['properties'] = json.loads(style['properties'])
styles.append(style)
return styles
except Exception as e:
print(f"Error loading styles: {e}")
return []
def _load_stats(self, project_id: str) -> Dict[str, Any]:
"""Load project statistics"""
try:
with get_connection() as conn:
# Component count by type
component_stats = conn.execute(
"""
SELECT COUNT(*) as total,
SUM(CASE WHEN code_generated = 1 THEN 1 ELSE 0 END) as generated
FROM components
WHERE project_id = ?
""",
(project_id,)
).fetchone()
# Style count by type
style_stats = conn.execute(
"""
SELECT type, COUNT(*) as count
FROM styles
WHERE project_id = ?
GROUP BY type
""",
(project_id,)
).fetchall()
return {
'components': dict(component_stats) if component_stats else {'total': 0, 'generated': 0},
'styles': {row['type']: row['count'] for row in style_stats}
}
except Exception as e:
print(f"Error loading stats: {e}")
return {'components': {'total': 0, 'generated': 0}, 'styles': {}}
def _load_integrations(self, project_id: str, user_id: Optional[int]) -> Dict[str, Any]:
"""Load user's enabled integrations for this project"""
if not user_id:
return {}
try:
with get_connection() as conn:
rows = conn.execute(
"""
SELECT integration_type, config, enabled, last_used_at
FROM project_integrations
WHERE project_id = ? AND user_id = ? AND enabled = 1
""",
(project_id, user_id)
).fetchall()
# Return decrypted config for each integration
integrations = {}
cipher = mcp_config.get_cipher()
for row in rows:
integration_type = row['integration_type']
encrypted_config = row['config']
# Decrypt config
if cipher:
try:
decrypted_config = cipher.decrypt(encrypted_config.encode()).decode()
config = json.loads(decrypted_config)
except Exception as e:
print(f"Error decrypting integration config: {e}")
config = {}
else:
# No encryption key, try to parse as JSON
try:
config = json.loads(encrypted_config)
except:
config = {}
integrations[integration_type] = {
'enabled': True,
'config': config,
'last_used_at': row['last_used_at']
}
return integrations
except Exception as e:
print(f"Error loading integrations: {e}")
return {}
def _load_tokens(self, project_path: Optional[Path]) -> Dict[str, Any]:
"""Load design tokens from filesystem"""
if not project_path:
return {}
tokens = {}
token_files = ['tokens.json', 'design-tokens.json', 'variables.json']
for token_file in token_files:
token_path = project_path / token_file
if token_path.exists():
try:
with open(token_path) as f:
tokens = json.load(f)
break
except Exception as e:
print(f"Error loading tokens from {token_path}: {e}")
return tokens
def _load_discovery(self, project_path: Optional[Path]) -> Dict[str, Any]:
"""Load project discovery data"""
if not project_path:
return {}
try:
scanner = ProjectScanner(str(project_path))
discovery = scanner.scan()
return discovery
except Exception as e:
print(f"Error running discovery scan: {e}")
return {}
def _compute_health(
self,
components: List[Dict],
tokens: Dict,
stats: Dict
) -> Dict[str, Any]:
"""Compute project health score"""
score = 100
issues = []
# Deduct points for missing components
if stats['components']['total'] == 0:
score -= 30
issues.append("No components defined")
# Deduct points for no tokens
if not tokens:
score -= 20
issues.append("No design tokens defined")
# Deduct points for ungeneratedcomponents
total = stats['components']['total']
generated = stats['components']['generated']
if total > 0 and generated < total:
percentage = (generated / total) * 100
if percentage < 50:
score -= 20
issues.append(f"Low code generation: {percentage:.1f}%")
elif percentage < 80:
score -= 10
issues.append(f"Medium code generation: {percentage:.1f}%")
# Compute grade
if score >= 90:
grade = 'A'
elif score >= 80:
grade = 'B'
elif score >= 70:
grade = 'C'
elif score >= 60:
grade = 'D'
else:
grade = 'F'
return {
'score': max(0, score),
'grade': grade,
'issues': issues
}
def clear_cache(self, project_id: Optional[str] = None):
"""Clear cache for specific project or all projects"""
if project_id:
# Clear all cache entries for this project
keys_to_remove = [k for k in self._cache.keys() if k.startswith(f"{project_id}:")]
for key in keys_to_remove:
del self._cache[key]
else:
# Clear all cache
self._cache.clear()
# Singleton instance
_context_manager = None
def get_context_manager() -> ProjectContextManager:
"""Get singleton context manager instance"""
global _context_manager
if _context_manager is None:
_context_manager = ProjectContextManager()
return _context_manager

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"""
Unified MCP Handler
Central handler for all MCP tool execution. Used by:
- Direct API calls (/api/mcp/tools/{name}/execute)
- Claude chat (inline tool execution)
- SSE streaming connections
This module ensures all MCP requests go through a single code path
for consistent logging, error handling, and security.
"""
import json
import asyncio
from typing import Dict, Any, List, Optional, Tuple
from datetime import datetime
from dataclasses import dataclass, asdict
import sys
from pathlib import Path
# Note: sys.path is set up by the importing module (server.py)
# Do NOT modify sys.path here as it causes relative import issues
from storage.json_store import Projects, ActivityLog
from .config import mcp_config, integration_config
from .context.project_context import get_context_manager, ProjectContext
from .tools.project_tools import PROJECT_TOOLS, ProjectTools
from .tools.analysis_tools import ANALYSIS_TOOLS, AnalysisTools
from .integrations.figma import FIGMA_TOOLS, FigmaTools
from .integrations.storybook import STORYBOOK_TOOLS, StorybookTools
from .integrations.jira import JIRA_TOOLS, JiraTools
from .integrations.confluence import CONFLUENCE_TOOLS, ConfluenceTools
from .integrations.translations import TRANSLATION_TOOLS, TranslationTools
from .integrations.base import CircuitBreakerOpen
@dataclass
class ToolResult:
"""Result of a tool execution"""
tool_name: str
success: bool
result: Any
error: Optional[str] = None
duration_ms: int = 0
timestamp: str = None
def __post_init__(self):
if not self.timestamp:
self.timestamp = datetime.now().isoformat()
def to_dict(self) -> Dict[str, Any]:
return asdict(self)
@dataclass
class MCPContext:
"""Context for MCP operations"""
project_id: str
user_id: Optional[int] = None
session_id: Optional[str] = None
class MCPHandler:
"""
Unified MCP tool handler.
Provides:
- Tool discovery (list all available tools)
- Tool execution with proper context
- Integration management
- Logging and metrics
"""
def __init__(self):
self.context_manager = get_context_manager()
self._tool_registry: Dict[str, Dict[str, Any]] = {}
self._initialize_tools()
def _initialize_tools(self):
"""Initialize tool registry with all available tools"""
# Register base project tools
for tool in PROJECT_TOOLS:
self._tool_registry[tool.name] = {
"tool": tool,
"category": "project",
"requires_integration": False
}
# Register analysis tools
for tool in ANALYSIS_TOOLS:
self._tool_registry[tool.name] = {
"tool": tool,
"category": "analysis",
"requires_integration": False
}
# Register Figma tools
for tool in FIGMA_TOOLS:
self._tool_registry[tool.name] = {
"tool": tool,
"category": "figma",
"requires_integration": True,
"integration_type": "figma"
}
# Register Storybook tools
for tool in STORYBOOK_TOOLS:
self._tool_registry[tool.name] = {
"tool": tool,
"category": "storybook",
"requires_integration": False
}
# Register Jira tools
for tool in JIRA_TOOLS:
self._tool_registry[tool.name] = {
"tool": tool,
"category": "jira",
"requires_integration": True,
"integration_type": "jira"
}
# Register Confluence tools
for tool in CONFLUENCE_TOOLS:
self._tool_registry[tool.name] = {
"tool": tool,
"category": "confluence",
"requires_integration": True,
"integration_type": "confluence"
}
# Register Translation tools
for tool in TRANSLATION_TOOLS:
self._tool_registry[tool.name] = {
"tool": tool,
"category": "translations",
"requires_integration": False
}
def list_tools(self, include_details: bool = False) -> Dict[str, Any]:
"""
List all available MCP tools.
Args:
include_details: Include full tool schemas
Returns:
Tool listing by category
"""
tools_by_category = {}
for name, info in self._tool_registry.items():
category = info["category"]
if category not in tools_by_category:
tools_by_category[category] = []
tool_info = {
"name": name,
"description": info["tool"].description,
"requires_integration": info.get("requires_integration", False)
}
if include_details:
tool_info["input_schema"] = info["tool"].inputSchema
tools_by_category[category].append(tool_info)
return {
"tools": tools_by_category,
"total_count": len(self._tool_registry)
}
def get_tool_info(self, tool_name: str) -> Optional[Dict[str, Any]]:
"""Get information about a specific tool"""
if tool_name not in self._tool_registry:
return None
info = self._tool_registry[tool_name]
return {
"name": tool_name,
"description": info["tool"].description,
"category": info["category"],
"input_schema": info["tool"].inputSchema,
"requires_integration": info.get("requires_integration", False),
"integration_type": info.get("integration_type")
}
async def execute_tool(
self,
tool_name: str,
arguments: Dict[str, Any],
context: MCPContext
) -> ToolResult:
"""
Execute an MCP tool.
Args:
tool_name: Name of the tool to execute
arguments: Tool arguments
context: MCP context (project_id, user_id)
Returns:
ToolResult with success/failure and data
"""
start_time = datetime.now()
# Check if tool exists
if tool_name not in self._tool_registry:
return ToolResult(
tool_name=tool_name,
success=False,
result=None,
error=f"Unknown tool: {tool_name}"
)
tool_info = self._tool_registry[tool_name]
category = tool_info["category"]
try:
# Execute based on category
if category == "project":
result = await self._execute_project_tool(tool_name, arguments, context)
elif category == "analysis":
result = await self._execute_analysis_tool(tool_name, arguments, context)
elif category == "figma":
result = await self._execute_figma_tool(tool_name, arguments, context)
elif category == "storybook":
result = await self._execute_storybook_tool(tool_name, arguments, context)
elif category == "jira":
result = await self._execute_jira_tool(tool_name, arguments, context)
elif category == "confluence":
result = await self._execute_confluence_tool(tool_name, arguments, context)
elif category == "translations":
result = await self._execute_translations_tool(tool_name, arguments, context)
else:
result = {"error": f"Unknown tool category: {category}"}
# Check for error in result
success = "error" not in result
error = result.get("error") if not success else None
# Calculate duration
duration_ms = int((datetime.now() - start_time).total_seconds() * 1000)
# Log execution
await self._log_tool_usage(
tool_name=tool_name,
category=category,
project_id=context.project_id,
user_id=context.user_id,
success=success,
duration_ms=duration_ms,
error=error
)
return ToolResult(
tool_name=tool_name,
success=success,
result=result if success else None,
error=error,
duration_ms=duration_ms
)
except CircuitBreakerOpen as e:
duration_ms = int((datetime.now() - start_time).total_seconds() * 1000)
return ToolResult(
tool_name=tool_name,
success=False,
result=None,
error=str(e),
duration_ms=duration_ms
)
except Exception as e:
duration_ms = int((datetime.now() - start_time).total_seconds() * 1000)
await self._log_tool_usage(
tool_name=tool_name,
category=category,
project_id=context.project_id,
user_id=context.user_id,
success=False,
duration_ms=duration_ms,
error=str(e)
)
return ToolResult(
tool_name=tool_name,
success=False,
result=None,
error=str(e),
duration_ms=duration_ms
)
async def _execute_project_tool(
self,
tool_name: str,
arguments: Dict[str, Any],
context: MCPContext
) -> Dict[str, Any]:
"""Execute a project tool"""
# Ensure project_id is set
if "project_id" not in arguments:
arguments["project_id"] = context.project_id
project_tools = ProjectTools(context.user_id)
return await project_tools.execute_tool(tool_name, arguments)
async def _execute_analysis_tool(
self,
tool_name: str,
arguments: Dict[str, Any],
context: MCPContext
) -> Dict[str, Any]:
"""Execute an analysis tool"""
# Ensure project_id is set for context if needed, though project_path is explicit
if "project_id" not in arguments:
arguments["project_id"] = context.project_id
analysis_tools = AnalysisTools(context.user_id)
return await analysis_tools.execute_tool(tool_name, arguments)
async def _execute_figma_tool(
self,
tool_name: str,
arguments: Dict[str, Any],
context: MCPContext
) -> Dict[str, Any]:
"""Execute a Figma tool"""
# Get Figma config
config = await self._get_integration_config("figma", context)
if not config:
# Try global config
if integration_config.FIGMA_TOKEN:
config = {"api_token": integration_config.FIGMA_TOKEN}
else:
return {"error": "Figma not configured. Please add Figma API token."}
figma_tools = FigmaTools(config)
return await figma_tools.execute_tool(tool_name, arguments)
async def _execute_storybook_tool(
self,
tool_name: str,
arguments: Dict[str, Any],
context: MCPContext
) -> Dict[str, Any]:
"""Execute a Storybook tool"""
# Ensure project_id is set
if "project_id" not in arguments:
arguments["project_id"] = context.project_id
storybook_tools = StorybookTools()
return await storybook_tools.execute_tool(tool_name, arguments)
async def _execute_jira_tool(
self,
tool_name: str,
arguments: Dict[str, Any],
context: MCPContext
) -> Dict[str, Any]:
"""Execute a Jira tool"""
config = await self._get_integration_config("jira", context)
if not config:
return {"error": "Jira not configured. Please configure Jira integration."}
jira_tools = JiraTools(config)
return await jira_tools.execute_tool(tool_name, arguments)
async def _execute_confluence_tool(
self,
tool_name: str,
arguments: Dict[str, Any],
context: MCPContext
) -> Dict[str, Any]:
"""Execute a Confluence tool"""
config = await self._get_integration_config("confluence", context)
if not config:
return {"error": "Confluence not configured. Please configure Confluence integration."}
confluence_tools = ConfluenceTools(config)
return await confluence_tools.execute_tool(tool_name, arguments)
async def _execute_translations_tool(
self,
tool_name: str,
arguments: Dict[str, Any],
context: MCPContext
) -> Dict[str, Any]:
"""Execute a Translation tool"""
# Ensure project_id is set
if "project_id" not in arguments:
arguments["project_id"] = context.project_id
translation_tools = TranslationTools()
return await translation_tools.execute_tool(tool_name, arguments)
async def _get_integration_config(
self,
integration_type: str,
context: MCPContext
) -> Optional[Dict[str, Any]]:
"""Get decrypted integration config for user/project"""
if not context.user_id or not context.project_id:
return None
loop = asyncio.get_event_loop()
def get_config():
try:
with get_connection() as conn:
row = conn.execute(
"""
SELECT config FROM project_integrations
WHERE project_id = ? AND user_id = ? AND integration_type = ? AND enabled = 1
""",
(context.project_id, context.user_id, integration_type)
).fetchone()
if not row:
return None
encrypted_config = row["config"]
# Decrypt
cipher = mcp_config.get_cipher()
if cipher:
try:
decrypted = cipher.decrypt(encrypted_config.encode()).decode()
return json.loads(decrypted)
except:
pass
# Try parsing as plain JSON
try:
return json.loads(encrypted_config)
except:
return None
except:
return None
return await loop.run_in_executor(None, get_config)
async def _log_tool_usage(
self,
tool_name: str,
category: str,
project_id: str,
user_id: Optional[int],
success: bool,
duration_ms: int,
error: Optional[str] = None
):
"""Log tool execution to database"""
loop = asyncio.get_event_loop()
def log():
try:
with get_connection() as conn:
conn.execute(
"""
INSERT INTO mcp_tool_usage
(project_id, user_id, tool_name, tool_category, duration_ms, success, error_message)
VALUES (?, ?, ?, ?, ?, ?, ?)
""",
(project_id, user_id, tool_name, category, duration_ms, success, error)
)
except:
pass # Don't fail on logging errors
await loop.run_in_executor(None, log)
async def get_project_context(
self,
project_id: str,
user_id: Optional[int] = None
) -> Optional[ProjectContext]:
"""Get project context for Claude system prompt"""
return await self.context_manager.get_context(project_id, user_id)
def get_tools_for_claude(self) -> List[Dict[str, Any]]:
"""
Get tools formatted for Claude's tool_use feature.
Returns:
List of tools in Anthropic's tool format
"""
tools = []
for name, info in self._tool_registry.items():
tools.append({
"name": name,
"description": info["tool"].description,
"input_schema": info["tool"].inputSchema
})
return tools
# Singleton instance
_mcp_handler: Optional[MCPHandler] = None
def get_mcp_handler() -> MCPHandler:
"""Get singleton MCP handler instance"""
global _mcp_handler
if _mcp_handler is None:
_mcp_handler = MCPHandler()
return _mcp_handler

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dss/mcp/integrations/__init__.py Normal file
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dss/mcp/integrations/base.py Normal file
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"""
Base Integration Classes
Provides circuit breaker pattern and base classes for external integrations.
"""
import time
import asyncio
from typing import Callable, Any, Optional, Dict
from dataclasses import dataclass
from datetime import datetime, timedelta
from enum import Enum
from ..config import mcp_config
from storage.json_store import Cache, read_json, write_json, SYSTEM_DIR
class CircuitState(Enum):
"""Circuit breaker states"""
CLOSED = "closed" # Normal operation
OPEN = "open" # Failing, reject requests
HALF_OPEN = "half_open" # Testing if service recovered
@dataclass
class CircuitBreakerStats:
"""Circuit breaker statistics"""
state: CircuitState
failure_count: int
success_count: int
last_failure_time: Optional[float]
last_success_time: Optional[float]
opened_at: Optional[float]
next_retry_time: Optional[float]
class CircuitBreakerOpen(Exception):
"""Exception raised when circuit breaker is open"""
pass
class CircuitBreaker:
"""
Circuit Breaker pattern implementation.
Protects external service calls from cascading failures.
Three states: CLOSED (normal), OPEN (failing), HALF_OPEN (testing).
"""
def __init__(
self,
integration_type: str,
failure_threshold: int = None,
timeout_seconds: int = None,
half_open_max_calls: int = 3
):
"""
Args:
integration_type: Type of integration (figma, jira, confluence, etc.)
failure_threshold: Number of failures before opening circuit
timeout_seconds: Seconds to wait before trying again
half_open_max_calls: Max successful calls in half-open before closing
"""
self.integration_type = integration_type
self.failure_threshold = failure_threshold or mcp_config.CIRCUIT_BREAKER_FAILURE_THRESHOLD
self.timeout_seconds = timeout_seconds or mcp_config.CIRCUIT_BREAKER_TIMEOUT_SECONDS
self.half_open_max_calls = half_open_max_calls
# In-memory state (could be moved to Redis for distributed setup)
self.state = CircuitState.CLOSED
self.failure_count = 0
self.success_count = 0
self.last_failure_time: Optional[float] = None
self.last_success_time: Optional[float] = None
self.opened_at: Optional[float] = None
async def call(self, func: Callable, *args, **kwargs) -> Any:
"""
Call a function through the circuit breaker.
Args:
func: Function to call (can be sync or async)
*args, **kwargs: Arguments to pass to func
Returns:
Function result
Raises:
CircuitBreakerOpen: If circuit is open
Exception: Original exception from func if it fails
"""
# Check circuit state
if self.state == CircuitState.OPEN:
# Check if timeout has elapsed
if time.time() - self.opened_at < self.timeout_seconds:
await self._record_failure("Circuit breaker is OPEN", db_only=True)
raise CircuitBreakerOpen(
f"{self.integration_type} service is temporarily unavailable. "
f"Retry after {self._seconds_until_retry():.0f}s"
)
else:
# Timeout elapsed, move to HALF_OPEN
self.state = CircuitState.HALF_OPEN
self.success_count = 0
# Execute function
try:
# Handle both sync and async functions
if asyncio.iscoroutinefunction(func):
result = await func(*args, **kwargs)
else:
result = func(*args, **kwargs)
# Success!
await self._record_success()
# If in HALF_OPEN, check if we can close the circuit
if self.state == CircuitState.HALF_OPEN:
if self.success_count >= self.half_open_max_calls:
self.state = CircuitState.CLOSED
self.failure_count = 0
return result
except Exception as e:
# Failure
await self._record_failure(str(e))
# Check if we should open the circuit
if self.failure_count >= self.failure_threshold:
self.state = CircuitState.OPEN
self.opened_at = time.time()
raise
async def _record_success(self):
"""Record successful call"""
self.success_count += 1
self.last_success_time = time.time()
# Update database
await self._update_health_db(is_healthy=True, error=None)
async def _record_failure(self, error_message: str, db_only: bool = False):
"""Record failed call"""
if not db_only:
self.failure_count += 1
self.last_failure_time = time.time()
# Update database
await self._update_health_db(is_healthy=False, error=error_message)
async def _update_health_db(self, is_healthy: bool, error: Optional[str]):
"""Update integration health in database"""
loop = asyncio.get_event_loop()
def update_db():
try:
with get_connection() as conn:
circuit_open_until = None
if self.state == CircuitState.OPEN and self.opened_at:
circuit_open_until = datetime.fromtimestamp(
self.opened_at + self.timeout_seconds
).isoformat()
if is_healthy:
conn.execute(
"""
UPDATE integration_health
SET is_healthy = 1,
failure_count = 0,
last_success_at = CURRENT_TIMESTAMP,
circuit_open_until = NULL,
updated_at = CURRENT_TIMESTAMP
WHERE integration_type = ?
""",
(self.integration_type,)
)
else:
conn.execute(
"""
UPDATE integration_health
SET is_healthy = 0,
failure_count = ?,
last_failure_at = CURRENT_TIMESTAMP,
circuit_open_until = ?,
updated_at = CURRENT_TIMESTAMP
WHERE integration_type = ?
""",
(self.failure_count, circuit_open_until, self.integration_type)
)
except Exception as e:
print(f"Error updating integration health: {e}")
await loop.run_in_executor(None, update_db)
def _seconds_until_retry(self) -> float:
"""Get seconds until circuit can be retried"""
if self.state != CircuitState.OPEN or not self.opened_at:
return 0
elapsed = time.time() - self.opened_at
remaining = self.timeout_seconds - elapsed
return max(0, remaining)
def get_stats(self) -> CircuitBreakerStats:
"""Get current circuit breaker statistics"""
next_retry_time = None
if self.state == CircuitState.OPEN and self.opened_at:
next_retry_time = self.opened_at + self.timeout_seconds
return CircuitBreakerStats(
state=self.state,
failure_count=self.failure_count,
success_count=self.success_count,
last_failure_time=self.last_failure_time,
last_success_time=self.last_success_time,
opened_at=self.opened_at,
next_retry_time=next_retry_time
)
class BaseIntegration:
"""Base class for all external integrations"""
def __init__(self, integration_type: str, config: Dict[str, Any]):
"""
Args:
integration_type: Type of integration (figma, jira, etc.)
config: Integration configuration (decrypted)
"""
self.integration_type = integration_type
self.config = config
self.circuit_breaker = CircuitBreaker(integration_type)
async def call_api(self, func: Callable, *args, **kwargs) -> Any:
"""
Call external API through circuit breaker.
Args:
func: API function to call
*args, **kwargs: Arguments to pass
Returns:
API response
Raises:
CircuitBreakerOpen: If circuit is open
Exception: Original API exception
"""
return await self.circuit_breaker.call(func, *args, **kwargs)
def get_health(self) -> Dict[str, Any]:
"""Get integration health status"""
stats = self.circuit_breaker.get_stats()
return {
"integration_type": self.integration_type,
"state": stats.state.value,
"is_healthy": stats.state == CircuitState.CLOSED,
"failure_count": stats.failure_count,
"success_count": stats.success_count,
"last_failure_time": stats.last_failure_time,
"last_success_time": stats.last_success_time,
"next_retry_time": stats.next_retry_time
}

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"""
Confluence Integration for MCP
Provides Confluence API tools for documentation and knowledge base.
"""
from typing import Dict, Any, List, Optional
from atlassian import Confluence
from mcp import types
from .base import BaseIntegration
# Confluence MCP Tool Definitions
CONFLUENCE_TOOLS = [
types.Tool(
name="confluence_create_page",
description="Create a new Confluence page",
inputSchema={
"type": "object",
"properties": {
"space_key": {
"type": "string",
"description": "Confluence space key"
},
"title": {
"type": "string",
"description": "Page title"
},
"body": {
"type": "string",
"description": "Page content (HTML or wiki markup)"
},
"parent_id": {
"type": "string",
"description": "Optional parent page ID"
}
},
"required": ["space_key", "title", "body"]
}
),
types.Tool(
name="confluence_get_page",
description="Get Confluence page by ID or title",
inputSchema={
"type": "object",
"properties": {
"page_id": {
"type": "string",
"description": "Page ID (use this OR title)"
},
"space_key": {
"type": "string",
"description": "Space key (required if using title)"
},
"title": {
"type": "string",
"description": "Page title (use this OR page_id)"
},
"expand": {
"type": "string",
"description": "Comma-separated list of expansions (body.storage, version, etc.)",
"default": "body.storage,version"
}
}
}
),
types.Tool(
name="confluence_update_page",
description="Update an existing Confluence page",
inputSchema={
"type": "object",
"properties": {
"page_id": {
"type": "string",
"description": "Page ID to update"
},
"title": {
"type": "string",
"description": "New page title"
},
"body": {
"type": "string",
"description": "New page content"
}
},
"required": ["page_id", "title", "body"]
}
),
types.Tool(
name="confluence_search",
description="Search Confluence pages using CQL",
inputSchema={
"type": "object",
"properties": {
"cql": {
"type": "string",
"description": "CQL query (e.g., 'space=DSS AND type=page')"
},
"limit": {
"type": "integer",
"description": "Maximum number of results",
"default": 25
}
},
"required": ["cql"]
}
),
types.Tool(
name="confluence_get_space",
description="Get Confluence space details",
inputSchema={
"type": "object",
"properties": {
"space_key": {
"type": "string",
"description": "Space key"
}
},
"required": ["space_key"]
}
)
]
class ConfluenceIntegration(BaseIntegration):
"""Confluence API integration with circuit breaker"""
def __init__(self, config: Dict[str, Any]):
"""
Initialize Confluence integration.
Args:
config: Must contain 'url', 'username', 'api_token'
"""
super().__init__("confluence", config)
url = config.get("url")
username = config.get("username")
api_token = config.get("api_token")
if not all([url, username, api_token]):
raise ValueError("Confluence configuration incomplete: url, username, api_token required")
self.confluence = Confluence(
url=url,
username=username,
password=api_token,
cloud=True
)
async def create_page(
self,
space_key: str,
title: str,
body: str,
parent_id: Optional[str] = None
) -> Dict[str, Any]:
"""Create a new page"""
def _create():
return self.confluence.create_page(
space=space_key,
title=title,
body=body,
parent_id=parent_id,
representation="storage"
)
return await self.call_api(_create)
async def get_page(
self,
page_id: Optional[str] = None,
space_key: Optional[str] = None,
title: Optional[str] = None,
expand: str = "body.storage,version"
) -> Dict[str, Any]:
"""Get page by ID or title"""
def _get():
if page_id:
return self.confluence.get_page_by_id(
page_id=page_id,
expand=expand
)
elif space_key and title:
return self.confluence.get_page_by_title(
space=space_key,
title=title,
expand=expand
)
else:
raise ValueError("Must provide either page_id or (space_key + title)")
return await self.call_api(_get)
async def update_page(
self,
page_id: str,
title: str,
body: str
) -> Dict[str, Any]:
"""Update an existing page"""
def _update():
# Get current version
page = self.confluence.get_page_by_id(page_id, expand="version")
current_version = page["version"]["number"]
return self.confluence.update_page(
page_id=page_id,
title=title,
body=body,
parent_id=None,
type="page",
representation="storage",
minor_edit=False,
version_comment="Updated via DSS MCP",
version_number=current_version + 1
)
return await self.call_api(_update)
async def search(self, cql: str, limit: int = 25) -> Dict[str, Any]:
"""Search pages using CQL"""
def _search():
return self.confluence.cql(cql, limit=limit)
return await self.call_api(_search)
async def get_space(self, space_key: str) -> Dict[str, Any]:
"""Get space details"""
def _get():
return self.confluence.get_space(space_key)
return await self.call_api(_get)
class ConfluenceTools:
"""MCP tool executor for Confluence integration"""
def __init__(self, config: Dict[str, Any]):
self.confluence = ConfluenceIntegration(config)
async def execute_tool(self, tool_name: str, arguments: Dict[str, Any]) -> Dict[str, Any]:
"""Execute Confluence tool"""
handlers = {
"confluence_create_page": self.confluence.create_page,
"confluence_get_page": self.confluence.get_page,
"confluence_update_page": self.confluence.update_page,
"confluence_search": self.confluence.search,
"confluence_get_space": self.confluence.get_space
}
handler = handlers.get(tool_name)
if not handler:
return {"error": f"Unknown Confluence tool: {tool_name}"}
try:
clean_args = {k: v for k, v in arguments.items() if not k.startswith("_")}
result = await handler(**clean_args)
return result
except Exception as e:
return {"error": str(e)}

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"""
Figma Integration for MCP
Provides Figma API tools through circuit breaker pattern.
"""
import httpx
from typing import Dict, Any, List, Optional
from mcp import types
from .base import BaseIntegration
from ..config import integration_config
# Figma MCP Tool Definitions
FIGMA_TOOLS = [
types.Tool(
name="figma_get_file",
description="Get Figma file metadata and structure",
inputSchema={
"type": "object",
"properties": {
"file_key": {
"type": "string",
"description": "Figma file key"
}
},
"required": ["file_key"]
}
),
types.Tool(
name="figma_get_styles",
description="Get design styles (colors, text, effects) from Figma file",
inputSchema={
"type": "object",
"properties": {
"file_key": {
"type": "string",
"description": "Figma file key"
}
},
"required": ["file_key"]
}
),
types.Tool(
name="figma_get_components",
description="Get component definitions from Figma file",
inputSchema={
"type": "object",
"properties": {
"file_key": {
"type": "string",
"description": "Figma file key"
}
},
"required": ["file_key"]
}
),
types.Tool(
name="figma_extract_tokens",
description="Extract design tokens (variables) from Figma file",
inputSchema={
"type": "object",
"properties": {
"file_key": {
"type": "string",
"description": "Figma file key"
}
},
"required": ["file_key"]
}
),
types.Tool(
name="figma_get_node",
description="Get specific node/component by ID from Figma file",
inputSchema={
"type": "object",
"properties": {
"file_key": {
"type": "string",
"description": "Figma file key"
},
"node_id": {
"type": "string",
"description": "Node ID to fetch"
}
},
"required": ["file_key", "node_id"]
}
)
]
class FigmaIntegration(BaseIntegration):
"""Figma API integration with circuit breaker"""
FIGMA_API_BASE = "https://api.figma.com/v1"
def __init__(self, config: Dict[str, Any]):
"""
Initialize Figma integration.
Args:
config: Must contain 'api_token' or use FIGMA_TOKEN from env
"""
super().__init__("figma", config)
self.api_token = config.get("api_token") or integration_config.FIGMA_TOKEN
if not self.api_token:
raise ValueError("Figma API token not configured")
self.headers = {
"X-Figma-Token": self.api_token
}
async def get_file(self, file_key: str) -> Dict[str, Any]:
"""
Get Figma file metadata and structure.
Args:
file_key: Figma file key
Returns:
File data
"""
async def _fetch():
async with httpx.AsyncClient() as client:
response = await client.get(
f"{self.FIGMA_API_BASE}/files/{file_key}",
headers=self.headers,
timeout=30.0
)
response.raise_for_status()
return response.json()
return await self.call_api(_fetch)
async def get_styles(self, file_key: str) -> Dict[str, Any]:
"""
Get all styles from Figma file.
Args:
file_key: Figma file key
Returns:
Styles data
"""
async def _fetch():
async with httpx.AsyncClient() as client:
response = await client.get(
f"{self.FIGMA_API_BASE}/files/{file_key}/styles",
headers=self.headers,
timeout=30.0
)
response.raise_for_status()
return response.json()
return await self.call_api(_fetch)
async def get_components(self, file_key: str) -> Dict[str, Any]:
"""
Get all components from Figma file.
Args:
file_key: Figma file key
Returns:
Components data
"""
async def _fetch():
async with httpx.AsyncClient() as client:
response = await client.get(
f"{self.FIGMA_API_BASE}/files/{file_key}/components",
headers=self.headers,
timeout=30.0
)
response.raise_for_status()
return response.json()
return await self.call_api(_fetch)
async def extract_tokens(self, file_key: str) -> Dict[str, Any]:
"""
Extract design tokens (variables) from Figma file.
Args:
file_key: Figma file key
Returns:
Variables/tokens data
"""
async def _fetch():
async with httpx.AsyncClient() as client:
# Get local variables
response = await client.get(
f"{self.FIGMA_API_BASE}/files/{file_key}/variables/local",
headers=self.headers,
timeout=30.0
)
response.raise_for_status()
return response.json()
return await self.call_api(_fetch)
async def get_node(self, file_key: str, node_id: str) -> Dict[str, Any]:
"""
Get specific node from Figma file.
Args:
file_key: Figma file key
node_id: Node ID
Returns:
Node data
"""
async def _fetch():
async with httpx.AsyncClient() as client:
response = await client.get(
f"{self.FIGMA_API_BASE}/files/{file_key}/nodes",
headers=self.headers,
params={"ids": node_id},
timeout=30.0
)
response.raise_for_status()
return response.json()
return await self.call_api(_fetch)
class FigmaTools:
"""MCP tool executor for Figma integration"""
def __init__(self, config: Dict[str, Any]):
"""
Args:
config: Figma configuration (with api_token)
"""
self.figma = FigmaIntegration(config)
async def execute_tool(self, tool_name: str, arguments: Dict[str, Any]) -> Dict[str, Any]:
"""Execute Figma tool"""
handlers = {
"figma_get_file": self.figma.get_file,
"figma_get_styles": self.figma.get_styles,
"figma_get_components": self.figma.get_components,
"figma_extract_tokens": self.figma.extract_tokens,
"figma_get_node": self.figma.get_node
}
handler = handlers.get(tool_name)
if not handler:
return {"error": f"Unknown Figma tool: {tool_name}"}
try:
# Remove tool-specific prefix from arguments if needed
clean_args = {k: v for k, v in arguments.items() if not k.startswith("_")}
result = await handler(**clean_args)
return result
except Exception as e:
return {"error": str(e)}

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"""
Jira Integration for MCP
Provides Jira API tools for issue tracking and project management.
"""
from typing import Dict, Any, List, Optional
from atlassian import Jira
from mcp import types
from .base import BaseIntegration
# Jira MCP Tool Definitions
JIRA_TOOLS = [
types.Tool(
name="jira_create_issue",
description="Create a new Jira issue",
inputSchema={
"type": "object",
"properties": {
"project_key": {
"type": "string",
"description": "Jira project key (e.g., 'DSS')"
},
"summary": {
"type": "string",
"description": "Issue summary/title"
},
"description": {
"type": "string",
"description": "Issue description"
},
"issue_type": {
"type": "string",
"description": "Issue type (Story, Task, Bug, etc.)",
"default": "Task"
}
},
"required": ["project_key", "summary"]
}
),
types.Tool(
name="jira_get_issue",
description="Get Jira issue details by key",
inputSchema={
"type": "object",
"properties": {
"issue_key": {
"type": "string",
"description": "Issue key (e.g., 'DSS-123')"
}
},
"required": ["issue_key"]
}
),
types.Tool(
name="jira_search_issues",
description="Search Jira issues using JQL",
inputSchema={
"type": "object",
"properties": {
"jql": {
"type": "string",
"description": "JQL query (e.g., 'project=DSS AND status=Open')"
},
"max_results": {
"type": "integer",
"description": "Maximum number of results",
"default": 50
}
},
"required": ["jql"]
}
),
types.Tool(
name="jira_update_issue",
description="Update a Jira issue",
inputSchema={
"type": "object",
"properties": {
"issue_key": {
"type": "string",
"description": "Issue key to update"
},
"fields": {
"type": "object",
"description": "Fields to update (summary, description, status, etc.)"
}
},
"required": ["issue_key", "fields"]
}
),
types.Tool(
name="jira_add_comment",
description="Add a comment to a Jira issue",
inputSchema={
"type": "object",
"properties": {
"issue_key": {
"type": "string",
"description": "Issue key"
},
"comment": {
"type": "string",
"description": "Comment text"
}
},
"required": ["issue_key", "comment"]
}
)
]
class JiraIntegration(BaseIntegration):
"""Jira API integration with circuit breaker"""
def __init__(self, config: Dict[str, Any]):
"""
Initialize Jira integration.
Args:
config: Must contain 'url', 'username', 'api_token'
"""
super().__init__("jira", config)
url = config.get("url")
username = config.get("username")
api_token = config.get("api_token")
if not all([url, username, api_token]):
raise ValueError("Jira configuration incomplete: url, username, api_token required")
self.jira = Jira(
url=url,
username=username,
password=api_token,
cloud=True
)
async def create_issue(
self,
project_key: str,
summary: str,
description: str = "",
issue_type: str = "Task"
) -> Dict[str, Any]:
"""Create a new Jira issue"""
def _create():
fields = {
"project": {"key": project_key},
"summary": summary,
"description": description,
"issuetype": {"name": issue_type}
}
return self.jira.create_issue(fields)
return await self.call_api(_create)
async def get_issue(self, issue_key: str) -> Dict[str, Any]:
"""Get issue details"""
def _get():
return self.jira.get_issue(issue_key)
return await self.call_api(_get)
async def search_issues(self, jql: str, max_results: int = 50) -> Dict[str, Any]:
"""Search issues with JQL"""
def _search():
return self.jira.jql(jql, limit=max_results)
return await self.call_api(_search)
async def update_issue(self, issue_key: str, fields: Dict[str, Any]) -> Dict[str, Any]:
"""Update issue fields"""
def _update():
self.jira.update_issue_field(issue_key, fields)
return {"status": "updated", "issue_key": issue_key}
return await self.call_api(_update)
async def add_comment(self, issue_key: str, comment: str) -> Dict[str, Any]:
"""Add comment to issue"""
def _comment():
return self.jira.issue_add_comment(issue_key, comment)
return await self.call_api(_comment)
class JiraTools:
"""MCP tool executor for Jira integration"""
def __init__(self, config: Dict[str, Any]):
self.jira = JiraIntegration(config)
async def execute_tool(self, tool_name: str, arguments: Dict[str, Any]) -> Dict[str, Any]:
"""Execute Jira tool"""
handlers = {
"jira_create_issue": self.jira.create_issue,
"jira_get_issue": self.jira.get_issue,
"jira_search_issues": self.jira.search_issues,
"jira_update_issue": self.jira.update_issue,
"jira_add_comment": self.jira.add_comment
}
handler = handlers.get(tool_name)
if not handler:
return {"error": f"Unknown Jira tool: {tool_name}"}
try:
clean_args = {k: v for k, v in arguments.items() if not k.startswith("_")}
result = await handler(**clean_args)
return result
except Exception as e:
return {"error": str(e)}

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"""
Storybook Integration for MCP
Provides Storybook tools for scanning, generating stories, creating themes, and configuration.
"""
from typing import Dict, Any, Optional, List
from pathlib import Path
from mcp import types
from .base import BaseIntegration
from ..context.project_context import get_context_manager
# Storybook MCP Tool Definitions
STORYBOOK_TOOLS = [
types.Tool(
name="storybook_scan",
description="Scan project for existing Storybook configuration and stories. Returns story inventory, configuration details, and coverage statistics.",
inputSchema={
"type": "object",
"properties": {
"project_id": {
"type": "string",
"description": "Project ID"
},
"path": {
"type": "string",
"description": "Optional: Specific path to scan (defaults to project root)"
}
},
"required": ["project_id"]
}
),
types.Tool(
name="storybook_generate_stories",
description="Generate Storybook stories for React components. Supports CSF3, CSF2, and MDX formats with automatic prop detection.",
inputSchema={
"type": "object",
"properties": {
"project_id": {
"type": "string",
"description": "Project ID"
},
"component_path": {
"type": "string",
"description": "Path to component file or directory"
},
"template": {
"type": "string",
"description": "Story format template",
"enum": ["csf3", "csf2", "mdx"],
"default": "csf3"
},
"include_variants": {
"type": "boolean",
"description": "Generate variant stories (default: true)",
"default": True
},
"dry_run": {
"type": "boolean",
"description": "Preview without writing files (default: true)",
"default": True
}
},
"required": ["project_id", "component_path"]
}
),
types.Tool(
name="storybook_generate_theme",
description="Generate Storybook theme configuration from design tokens. Creates manager.ts, preview.ts, and theme files.",
inputSchema={
"type": "object",
"properties": {
"project_id": {
"type": "string",
"description": "Project ID"
},
"brand_title": {
"type": "string",
"description": "Brand title for Storybook UI",
"default": "Design System"
},
"base_theme": {
"type": "string",
"description": "Base theme (light or dark)",
"enum": ["light", "dark"],
"default": "light"
},
"output_dir": {
"type": "string",
"description": "Output directory (default: .storybook)"
},
"write_files": {
"type": "boolean",
"description": "Write files to disk (default: false - preview only)",
"default": False
}
},
"required": ["project_id"]
}
),
types.Tool(
name="storybook_get_status",
description="Get Storybook installation and configuration status for a project.",
inputSchema={
"type": "object",
"properties": {
"project_id": {
"type": "string",
"description": "Project ID"
}
},
"required": ["project_id"]
}
),
types.Tool(
name="storybook_configure",
description="Configure or update Storybook for a project with DSS integration.",
inputSchema={
"type": "object",
"properties": {
"project_id": {
"type": "string",
"description": "Project ID"
},
"action": {
"type": "string",
"description": "Configuration action",
"enum": ["init", "update", "add_theme"],
"default": "init"
},
"options": {
"type": "object",
"description": "Configuration options",
"properties": {
"framework": {
"type": "string",
"enum": ["react", "vue", "angular"]
},
"builder": {
"type": "string",
"enum": ["vite", "webpack5"]
},
"typescript": {
"type": "boolean"
}
}
}
},
"required": ["project_id"]
}
)
]
class StorybookIntegration(BaseIntegration):
"""Storybook integration wrapper for DSS tools"""
def __init__(self, config: Optional[Dict[str, Any]] = None):
"""
Initialize Storybook integration.
Args:
config: Optional Storybook configuration
"""
super().__init__("storybook", config or {})
self.context_manager = get_context_manager()
async def _get_project_path(self, project_id: str) -> Path:
"""
Get project path from context manager.
Args:
project_id: Project ID
Returns:
Project path as Path object
"""
context = await self.context_manager.get_context(project_id)
if not context or not context.path:
raise ValueError(f"Project not found: {project_id}")
return Path(context.path)
async def scan_storybook(self, project_id: str, path: Optional[str] = None) -> Dict[str, Any]:
"""
Scan for Storybook config and stories.
Args:
project_id: Project ID
path: Optional specific path to scan
Returns:
Storybook scan results
"""
try:
from dss.storybook.scanner import StorybookScanner
project_path = await self._get_project_path(project_id)
# Ensure path is within project directory for security
if path:
scan_path = project_path / path
# Validate path doesn't escape project directory
if not scan_path.resolve().is_relative_to(project_path.resolve()):
raise ValueError("Path must be within project directory")
else:
scan_path = project_path
scanner = StorybookScanner(str(scan_path))
result = await scanner.scan() if hasattr(scanner.scan, '__await__') else scanner.scan()
coverage = await scanner.get_story_coverage() if hasattr(scanner.get_story_coverage, '__await__') else scanner.get_story_coverage()
return {
"project_id": project_id,
"path": str(scan_path),
"config": result.get("config") if isinstance(result, dict) else None,
"stories_count": result.get("stories_count", 0) if isinstance(result, dict) else 0,
"components_with_stories": result.get("components_with_stories", []) if isinstance(result, dict) else [],
"stories": result.get("stories", []) if isinstance(result, dict) else [],
"coverage": coverage if coverage else {}
}
except Exception as e:
return {
"error": f"Failed to scan Storybook: {str(e)}",
"project_id": project_id
}
async def generate_stories(
self,
project_id: str,
component_path: str,
template: str = "csf3",
include_variants: bool = True,
dry_run: bool = True
) -> Dict[str, Any]:
"""
Generate stories for components.
Args:
project_id: Project ID
component_path: Path to component file or directory
template: Story format (csf3, csf2, mdx)
include_variants: Whether to generate variant stories
dry_run: Preview without writing files
Returns:
Generation results
"""
try:
from dss.storybook.generator import StoryGenerator
project_path = await self._get_project_path(project_id)
generator = StoryGenerator(str(project_path))
full_path = project_path / component_path
# Check if path exists and is directory or file
if not full_path.exists():
return {
"error": f"Path not found: {component_path}",
"project_id": project_id
}
if full_path.is_dir():
# Generate for directory
func = generator.generate_stories_for_directory
if hasattr(func, '__await__'):
results = await func(
component_path,
template=template.upper(),
dry_run=dry_run
)
else:
results = func(
component_path,
template=template.upper(),
dry_run=dry_run
)
return {
"project_id": project_id,
"path": component_path,
"generated_count": len([r for r in (results if isinstance(results, list) else []) if "story" in str(r)]),
"results": results if isinstance(results, list) else [],
"dry_run": dry_run,
"template": template
}
else:
# Generate for single file
func = generator.generate_story
if hasattr(func, '__await__'):
story = await func(
component_path,
template=template.upper(),
include_variants=include_variants
)
else:
story = func(
component_path,
template=template.upper(),
include_variants=include_variants
)
return {
"project_id": project_id,
"component": component_path,
"story": story,
"template": template,
"include_variants": include_variants,
"dry_run": dry_run
}
except Exception as e:
return {
"error": f"Failed to generate stories: {str(e)}",
"project_id": project_id,
"component_path": component_path
}
async def generate_theme(
self,
project_id: str,
brand_title: str = "Design System",
base_theme: str = "light",
output_dir: Optional[str] = None,
write_files: bool = False
) -> Dict[str, Any]:
"""
Generate Storybook theme from design tokens.
Args:
project_id: Project ID
brand_title: Brand title for Storybook
base_theme: Base theme (light or dark)
output_dir: Output directory for theme files
write_files: Write files to disk or preview only
Returns:
Theme generation results
"""
try:
from dss.storybook.theme import ThemeGenerator
from dss.themes import get_default_light_theme, get_default_dark_theme
# Get project tokens from context
context = await self.context_manager.get_context(project_id)
if not context:
return {"error": f"Project not found: {project_id}"}
# Convert tokens to list format for ThemeGenerator
tokens_list = [
{"name": name, "value": token.get("value") if isinstance(token, dict) else token}
for name, token in (context.tokens.items() if hasattr(context, 'tokens') else {}.items())
]
generator = ThemeGenerator()
if write_files and output_dir:
# Generate and write files
func = generator.generate_full_config
if hasattr(func, '__await__'):
files = await func(
tokens=tokens_list,
brand_title=brand_title,
output_dir=output_dir
)
else:
files = func(
tokens=tokens_list,
brand_title=brand_title,
output_dir=output_dir
)
return {
"project_id": project_id,
"files_written": list(files.keys()) if isinstance(files, dict) else [],
"output_dir": output_dir,
"brand_title": brand_title
}
else:
# Preview mode - generate file contents
try:
func = generator.generate_from_tokens
if hasattr(func, '__await__'):
theme = await func(tokens_list, brand_title, base_theme)
else:
theme = func(tokens_list, brand_title, base_theme)
except Exception:
# Fallback to default theme
theme_obj = get_default_light_theme() if base_theme == "light" else get_default_dark_theme()
theme = {
"name": theme_obj.name if hasattr(theme_obj, 'name') else "Default",
"colors": {}
}
# Generate theme file content
theme_file = f"// Storybook theme for {brand_title}\nexport default {str(theme)};"
manager_file = f"import addons from '@storybook/addons';\nimport theme from './dss-theme';\naddons.setConfig({{ theme }});"
preview_file = f"import '../dss-theme';\nexport default {{ parameters: {{ actions: {{ argTypesRegex: '^on[A-Z].*' }} }} }};"
return {
"project_id": project_id,
"preview": True,
"brand_title": brand_title,
"base_theme": base_theme,
"files": {
"dss-theme.ts": theme_file,
"manager.ts": manager_file,
"preview.ts": preview_file
},
"token_count": len(tokens_list)
}
except Exception as e:
return {
"error": f"Failed to generate theme: {str(e)}",
"project_id": project_id
}
async def get_status(self, project_id: str) -> Dict[str, Any]:
"""
Get Storybook installation and configuration status.
Args:
project_id: Project ID
Returns:
Storybook status information
"""
try:
from dss.storybook.config import get_storybook_status
project_path = await self._get_project_path(project_id)
func = get_storybook_status
if hasattr(func, '__await__'):
status = await func(str(project_path))
else:
status = func(str(project_path))
return {
"project_id": project_id,
"path": str(project_path),
**(status if isinstance(status, dict) else {})
}
except Exception as e:
return {
"error": f"Failed to get Storybook status: {str(e)}",
"project_id": project_id,
"installed": False
}
async def configure(
self,
project_id: str,
action: str = "init",
options: Optional[Dict[str, Any]] = None
) -> Dict[str, Any]:
"""
Configure or update Storybook for project.
Args:
project_id: Project ID
action: Configuration action (init, update, add_theme)
options: Configuration options
Returns:
Configuration results
"""
try:
from dss.storybook.config import write_storybook_config_file
project_path = await self._get_project_path(project_id)
options = options or {}
# Map action to configuration
config = {
"action": action,
"framework": options.get("framework", "react"),
"builder": options.get("builder", "vite"),
"typescript": options.get("typescript", True)
}
func = write_storybook_config_file
if hasattr(func, '__await__'):
result = await func(str(project_path), config)
else:
result = func(str(project_path), config)
return {
"project_id": project_id,
"action": action,
"success": True,
"path": str(project_path),
"config_path": str(project_path / ".storybook"),
"options": config
}
except Exception as e:
return {
"error": f"Failed to configure Storybook: {str(e)}",
"project_id": project_id,
"action": action,
"success": False
}
class StorybookTools:
"""MCP tool executor for Storybook integration"""
def __init__(self, config: Optional[Dict[str, Any]] = None):
"""
Args:
config: Optional Storybook configuration
"""
self.storybook = StorybookIntegration(config)
async def execute_tool(self, tool_name: str, arguments: Dict[str, Any]) -> Dict[str, Any]:
"""
Execute Storybook tool.
Args:
tool_name: Name of tool to execute
arguments: Tool arguments
Returns:
Tool execution result
"""
handlers = {
"storybook_scan": self.storybook.scan_storybook,
"storybook_generate_stories": self.storybook.generate_stories,
"storybook_generate_theme": self.storybook.generate_theme,
"storybook_get_status": self.storybook.get_status,
"storybook_configure": self.storybook.configure
}
handler = handlers.get(tool_name)
if not handler:
return {"error": f"Unknown Storybook tool: {tool_name}"}
try:
# Remove internal prefixes and execute
clean_args = {k: v for k, v in arguments.items() if not k.startswith("_")}
result = await handler(**clean_args)
return result
except Exception as e:
return {"error": f"Tool execution failed: {str(e)}", "tool": tool_name}

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dss/mcp/operations.py Normal file
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"""
DSS MCP Operations Module
Handles long-running operations with status tracking, result storage, and cancellation support.
Operations are queued and executed asynchronously with persistent state.
"""
import asyncio
import json
import uuid
from typing import Optional, Dict, Any, Callable
from datetime import datetime
from enum import Enum
from .config import mcp_config
from storage.json_store import ActivityLog, read_json, write_json, DATA_DIR # JSON storage
class OperationStatus(Enum):
"""Operation execution status"""
PENDING = "pending"
RUNNING = "running"
COMPLETED = "completed"
FAILED = "failed"
CANCELLED = "cancelled"
class Operation:
"""Represents a single operation"""
def __init__(
self,
operation_type: str,
args: Dict[str, Any],
user_id: Optional[str] = None
):
self.id = str(uuid.uuid4())
self.operation_type = operation_type
self.args = args
self.user_id = user_id
self.status = OperationStatus.PENDING
self.result = None
self.error = None
self.progress = 0
self.created_at = datetime.utcnow()
self.started_at = None
self.completed_at = None
def to_dict(self) -> Dict[str, Any]:
"""Convert to dictionary for storage"""
return {
"id": self.id,
"operation_type": self.operation_type,
"args": json.dumps(self.args),
"user_id": self.user_id,
"status": self.status.value,
"result": json.dumps(self.result) if self.result else None,
"error": self.error,
"progress": self.progress,
"created_at": self.created_at.isoformat(),
"started_at": self.started_at.isoformat() if self.started_at else None,
"completed_at": self.completed_at.isoformat() if self.completed_at else None
}
@classmethod
def from_dict(cls, data: Dict[str, Any]) -> "Operation":
"""Reconstruct from dictionary"""
op = cls(
operation_type=data["operation_type"],
args=json.loads(data["args"]),
user_id=data.get("user_id")
)
op.id = data["id"]
op.status = OperationStatus(data["status"])
op.result = json.loads(data["result"]) if data.get("result") else None
op.error = data.get("error")
op.progress = data.get("progress", 0)
op.created_at = datetime.fromisoformat(data["created_at"])
if data.get("started_at"):
op.started_at = datetime.fromisoformat(data["started_at"])
if data.get("completed_at"):
op.completed_at = datetime.fromisoformat(data["completed_at"])
return op
class OperationQueue:
"""
Manages async operations with status tracking.
Operations are stored in database for persistence and recovery.
Multiple workers can process operations in parallel while respecting
per-resource locks to prevent concurrent modifications.
"""
# In-memory queue for active operations
_active_operations: Dict[str, Operation] = {}
_queue: asyncio.Queue = None
_workers: list = []
@classmethod
async def initialize(cls, num_workers: int = 4):
"""Initialize operation queue with worker pool"""
cls._queue = asyncio.Queue()
cls._workers = []
for i in range(num_workers):
worker = asyncio.create_task(cls._worker(i))
cls._workers.append(worker)
@classmethod
async def enqueue(
cls,
operation_type: str,
args: Dict[str, Any],
user_id: Optional[str] = None
) -> str:
"""
Enqueue a new operation.
Args:
operation_type: Type of operation (e.g., 'sync_tokens')
args: Operation arguments
user_id: Optional user ID for tracking
Returns:
Operation ID for status checking
"""
operation = Operation(operation_type, args, user_id)
# Save to database
cls._save_operation(operation)
# Add to in-memory tracking
cls._active_operations[operation.id] = operation
# Queue for processing
await cls._queue.put(operation)
return operation.id
@classmethod
def get_status(cls, operation_id: str) -> Optional[Dict[str, Any]]:
"""Get operation status and result"""
# Check in-memory first
if operation_id in cls._active_operations:
op = cls._active_operations[operation_id]
return {
"id": op.id,
"status": op.status.value,
"progress": op.progress,
"result": op.result,
"error": op.error
}
# Check database for completed operations
with get_connection() as conn:
cursor = conn.cursor()
cursor.execute("SELECT * FROM operations WHERE id = ?", (operation_id,))
row = cursor.fetchone()
if not row:
return None
op = Operation.from_dict(dict(row))
return {
"id": op.id,
"status": op.status.value,
"progress": op.progress,
"result": op.result,
"error": op.error
}
@classmethod
def get_result(cls, operation_id: str) -> Optional[Any]:
"""Get operation result (blocks if still running)"""
status = cls.get_status(operation_id)
if not status:
raise ValueError(f"Operation not found: {operation_id}")
if status["status"] == OperationStatus.COMPLETED.value:
return status["result"]
elif status["status"] == OperationStatus.FAILED.value:
raise RuntimeError(f"Operation failed: {status['error']}")
else:
raise RuntimeError(
f"Operation still {status['status']}: {operation_id}"
)
@classmethod
def cancel(cls, operation_id: str) -> bool:
"""Cancel a pending operation"""
if operation_id not in cls._active_operations:
return False
op = cls._active_operations[operation_id]
if op.status == OperationStatus.PENDING:
op.status = OperationStatus.CANCELLED
op.completed_at = datetime.utcnow()
cls._save_operation(op)
return True
return False
@classmethod
def list_operations(
cls,
operation_type: Optional[str] = None,
status: Optional[str] = None,
user_id: Optional[str] = None,
limit: int = 100
) -> list:
"""List operations with optional filtering"""
with get_connection() as conn:
cursor = conn.cursor()
query = "SELECT * FROM operations WHERE 1=1"
params = []
if operation_type:
query += " AND operation_type = ?"
params.append(operation_type)
if status:
query += " AND status = ?"
params.append(status)
if user_id:
query += " AND user_id = ?"
params.append(user_id)
query += " ORDER BY created_at DESC LIMIT ?"
params.append(limit)
cursor.execute(query, params)
return [Operation.from_dict(dict(row)).to_dict() for row in cursor.fetchall()]
# Private helper methods
@classmethod
def _save_operation(cls, operation: Operation):
"""Save operation to database"""
data = operation.to_dict()
with get_connection() as conn:
conn.execute("""
INSERT OR REPLACE INTO operations (
id, operation_type, args, user_id, status, result,
error, progress, created_at, started_at, completed_at
) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
""", tuple(data.values()))
@classmethod
async def _worker(cls, worker_id: int):
"""Worker coroutine that processes operations from queue"""
while True:
try:
operation = await cls._queue.get()
# Mark as running
operation.status = OperationStatus.RUNNING
operation.started_at = datetime.utcnow()
cls._save_operation(operation)
# Execute operation (placeholder - would call actual handlers)
try:
# TODO: Implement actual operation execution
# based on operation_type
operation.result = {
"message": f"Operation {operation.operation_type} completed"
}
operation.status = OperationStatus.COMPLETED
operation.progress = 100
except Exception as e:
operation.error = str(e)
operation.status = OperationStatus.FAILED
# Mark as completed
operation.completed_at = datetime.utcnow()
cls._save_operation(operation)
cls._queue.task_done()
except asyncio.CancelledError:
break
except Exception as e:
# Log error and continue
print(f"Worker {worker_id} error: {str(e)}")
await asyncio.sleep(1)
@classmethod
def ensure_operations_table(cls):
"""Ensure operations table exists"""
with get_connection() as conn:
conn.execute("""
CREATE TABLE IF NOT EXISTS operations (
id TEXT PRIMARY KEY,
operation_type TEXT NOT NULL,
args TEXT NOT NULL,
user_id TEXT,
status TEXT DEFAULT 'pending',
result TEXT,
error TEXT,
progress INTEGER DEFAULT 0,
created_at TEXT DEFAULT CURRENT_TIMESTAMP,
started_at TEXT,
completed_at TEXT
)
""")
conn.execute(
"CREATE INDEX IF NOT EXISTS idx_operations_type ON operations(operation_type)"
)
conn.execute(
"CREATE INDEX IF NOT EXISTS idx_operations_status ON operations(status)"
)
conn.execute(
"CREATE INDEX IF NOT EXISTS idx_operations_user ON operations(user_id)"
)
# Initialize table on import
OperationQueue.ensure_operations_table()

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dss/mcp/plugin_registry.py Normal file
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"""
Dynamic Plugin Registry for DSS MCP Server
Automatically discovers and registers MCP tools from the plugins/ directory.
Plugins follow a simple contract: export TOOLS list and a handler class with execute_tool() method.
"""
import pkgutil
import importlib
import inspect
import logging
import types as python_types
from typing import List, Dict, Any, Optional
from mcp import types
logger = logging.getLogger("dss.mcp.plugins")
class PluginRegistry:
"""
Discovers and manages dynamically loaded plugins.
Plugin Contract:
- Must export TOOLS: List[types.Tool] - MCP tool definitions
- Must have a class with execute_tool(name: str, arguments: dict) method
- Optional: PLUGIN_METADATA dict with name, version, author
Example Plugin Structure:
```python
from mcp import types
PLUGIN_METADATA = {
"name": "Example Plugin",
"version": "1.0.0",
"author": "DSS Team"
}
TOOLS = [
types.Tool(
name="example_tool",
description="Example tool",
inputSchema={...}
)
]
class PluginTools:
async def execute_tool(self, name: str, arguments: dict):
if name == "example_tool":
return {"result": "success"}
raise ValueError(f"Unknown tool: {name}")
```
"""
def __init__(self):
self.tools: List[types.Tool] = []
self.handlers: Dict[str, Any] = {} # tool_name -> handler_instance
self.plugins: List[Dict[str, Any]] = [] # plugin metadata
self._loaded_modules: set = set()
def load_plugins(self, plugins_package_name: str = "dss_mcp.plugins"):
"""
Scans the plugins directory and registers valid tool modules.
Args:
plugins_package_name: Fully qualified name of plugins package
Default: "dss_mcp.plugins" (works when called from tools/ dir)
"""
try:
# Dynamically import the plugins package
plugins_pkg = importlib.import_module(plugins_package_name)
path = plugins_pkg.__path__
prefix = plugins_pkg.__name__ + "."
logger.info(f"Scanning for plugins in: {path}")
# Iterate through all modules in the plugins directory
for _, name, is_pkg in pkgutil.iter_modules(path, prefix):
# Skip packages (only load .py files)
if is_pkg:
continue
# Skip template and private modules
module_basename = name.split('.')[-1]
if module_basename.startswith('_'):
logger.debug(f"Skipping private module: {module_basename}")
continue
try:
module = importlib.import_module(name)
self._register_module(module)
except Exception as e:
logger.error(f"Failed to load plugin module {name}: {e}", exc_info=True)
except ImportError as e:
logger.warning(f"Plugins package not found: {plugins_package_name} ({e})")
logger.info("Server will run without plugins")
def _register_module(self, module: python_types.ModuleType):
"""
Validates and registers a single plugin module.
Args:
module: The imported plugin module
"""
module_name = module.__name__
# Check if already loaded
if module_name in self._loaded_modules:
logger.debug(f"Module already loaded: {module_name}")
return
# Contract Check 1: Must export TOOLS list
if not hasattr(module, 'TOOLS'):
logger.debug(f"Module {module_name} has no TOOLS export, skipping")
return
if not isinstance(module.TOOLS, list):
logger.error(f"Module {module_name} TOOLS must be a list, got {type(module.TOOLS)}")
return
if len(module.TOOLS) == 0:
logger.warning(f"Module {module_name} has empty TOOLS list")
return
# Contract Check 2: Must have a class with execute_tool method
handler_instance = self._find_and_instantiate_handler(module)
if not handler_instance:
logger.warning(f"Plugin {module_name} has TOOLS but no valid handler class")
return
# Contract Check 3: execute_tool must be async (coroutine)
execute_tool_method = getattr(handler_instance, 'execute_tool', None)
if execute_tool_method and not inspect.iscoroutinefunction(execute_tool_method):
logger.error(
f"Plugin '{module_name}' is invalid: 'PluginTools.execute_tool' must be "
f"an async function ('async def'). Skipping plugin."
)
return
# Extract metadata
metadata = getattr(module, 'PLUGIN_METADATA', {})
plugin_name = metadata.get('name', module_name.split('.')[-1])
plugin_version = metadata.get('version', 'unknown')
# Validate tools and check for name collisions
registered_count = 0
for tool in module.TOOLS:
if not hasattr(tool, 'name'):
logger.error(f"Tool in {module_name} missing 'name' attribute")
continue
# Check for name collision
if tool.name in self.handlers:
logger.error(
f"Tool name collision: '{tool.name}' already registered. "
f"Skipping duplicate from {module_name}"
)
continue
# Register tool
self.tools.append(tool)
self.handlers[tool.name] = handler_instance
registered_count += 1
logger.debug(f"Registered tool: {tool.name}")
# Track plugin metadata
self.plugins.append({
"name": plugin_name,
"version": plugin_version,
"module": module_name,
"tools_count": registered_count,
"author": metadata.get('author', 'unknown')
})
self._loaded_modules.add(module_name)
logger.info(
f"Loaded plugin: {plugin_name} v{plugin_version} "
f"({registered_count} tools from {module_name})"
)
def _find_and_instantiate_handler(self, module: python_types.ModuleType) -> Optional[Any]:
"""
Finds a class implementing execute_tool and instantiates it.
Args:
module: The plugin module to search
Returns:
Instantiated handler class or None if not found
"""
for name, obj in inspect.getmembers(module, inspect.isclass):
# Only consider classes defined in this module (not imports)
if obj.__module__ != module.__name__:
continue
# Look for execute_tool method
if hasattr(obj, 'execute_tool'):
try:
# Try to instantiate with no args
instance = obj()
logger.debug(f"Instantiated handler class: {name}")
return instance
except TypeError:
# Try with **kwargs for flexible initialization
try:
instance = obj(**{})
logger.debug(f"Instantiated handler class with kwargs: {name}")
return instance
except Exception as e:
logger.error(
f"Failed to instantiate handler {name} in {module.__name__}: {e}"
)
return None
except Exception as e:
logger.error(
f"Failed to instantiate handler {name} in {module.__name__}: {e}"
)
return None
return None
async def execute_tool(self, name: str, arguments: dict) -> Any:
"""
Routes tool execution to the correct plugin handler.
Args:
name: Tool name
arguments: Tool arguments
Returns:
Tool execution result
Raises:
ValueError: If tool not found in registry
"""
if name not in self.handlers:
raise ValueError(f"Tool '{name}' not found in plugin registry")
handler = self.handlers[name]
# Support both async and sync implementations
if inspect.iscoroutinefunction(handler.execute_tool):
return await handler.execute_tool(name, arguments)
else:
return handler.execute_tool(name, arguments)
def get_all_tools(self) -> List[types.Tool]:
"""Get merged list of all plugin tools"""
return self.tools.copy()
def get_plugin_info(self) -> List[Dict[str, Any]]:
"""Get metadata for all loaded plugins"""
return self.plugins.copy()
def reload_plugins(self, plugins_package_name: str = "dss_mcp.plugins"):
"""
Reload all plugins (useful for development).
WARNING: This clears all registered plugins and reloads from scratch.
Args:
plugins_package_name: Fully qualified name of plugins package
"""
logger.info("Reloading all plugins...")
# Clear existing registrations
self.tools.clear()
self.handlers.clear()
self.plugins.clear()
self._loaded_modules.clear()
# Reload
self.load_plugins(plugins_package_name)
logger.info(f"Plugin reload complete. Loaded {len(self.plugins)} plugins, {len(self.tools)} tools")

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"""
DSS MCP Server Plugins
This directory contains dynamically loaded plugins for the DSS MCP server.
Plugin Contract:
- Each plugin is a .py file in this directory
- Must export TOOLS: List[types.Tool] with MCP tool definitions
- Must have a handler class with execute_tool(name, arguments) method
- Optional: export PLUGIN_METADATA dict with name, version, author
Example Plugin Structure:
from mcp import types
PLUGIN_METADATA = {
"name": "My Plugin",
"version": "1.0.0",
"author": "DSS Team"
}
TOOLS = [
types.Tool(name="my_tool", description="...", inputSchema={...})
]
class PluginTools:
async def execute_tool(self, name, arguments):
if name == "my_tool":
return {"result": "success"}
Developer Workflow:
1. Copy _template.py to new_plugin.py
2. Edit TOOLS list and PluginTools class
3. (Optional) Create requirements.txt if plugin needs dependencies
4. Run: ../install_plugin_deps.sh (if dependencies added)
5. Restart MCP server: supervisorctl restart dss-mcp
6. Plugin tools are immediately available to all clients
Dependency Management:
- If your plugin needs Python packages, create a requirements.txt file
- Place it in the same directory as your plugin (e.g., plugins/my_plugin/requirements.txt)
- Run ../install_plugin_deps.sh to install all plugin dependencies
- Use --check flag to see which plugins have dependencies without installing
Example plugin with dependencies:
plugins/
├── my_plugin/
│ ├── __init__.py
│ ├── tool.py (exports TOOLS and PluginTools)
│ └── requirements.txt (jinja2>=3.1.2, httpx>=0.25.0)
└── _template.py
See _template.py for a complete example.
"""
__all__ = [] # Plugins are auto-discovered, not explicitly exported

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"""
Plugin Template for DSS MCP Server
This file serves as both documentation and a starting point for new plugins.
To create a new plugin:
1. Copy this file: cp _template.py my_plugin.py
2. Update PLUGIN_METADATA with your plugin details
3. Define your tools in the TOOLS list
4. Implement tool logic in the PluginTools class
5. Restart the MCP server
The plugin will be automatically discovered and registered.
"""
from typing import Dict, Any, List
from mcp import types
# =============================================================================
# 1. PLUGIN METADATA (Optional but recommended)
# =============================================================================
PLUGIN_METADATA = {
"name": "Template Plugin",
"version": "1.0.0",
"author": "DSS Team",
"description": "Template plugin demonstrating the plugin contract"
}
# =============================================================================
# 2. TOOLS DEFINITION (Required)
# =============================================================================
TOOLS = [
types.Tool(
name="template_hello",
description="A simple hello world tool to verify the plugin system works",
inputSchema={
"type": "object",
"properties": {
"name": {
"type": "string",
"description": "Name to greet (optional)",
"default": "World"
}
}
}
),
types.Tool(
name="template_echo",
description="Echo back the provided message",
inputSchema={
"type": "object",
"properties": {
"message": {
"type": "string",
"description": "Message to echo back"
},
"uppercase": {
"type": "boolean",
"description": "Convert to uppercase (optional)",
"default": False
}
},
"required": ["message"]
}
)
]
# =============================================================================
# 3. PLUGIN TOOLS HANDLER (Required)
# =============================================================================
class PluginTools:
"""
Handler class for plugin tools.
The PluginRegistry will instantiate this class and call execute_tool()
to handle tool invocations.
Contract:
- Must have async execute_tool(name: str, arguments: dict) method
- Should return list[types.TextContent | types.ImageContent | types.EmbeddedResource]
- Can raise exceptions for errors (will be caught and logged)
"""
def __init__(self, **kwargs):
"""
Initialize the plugin tools handler.
Args:
**kwargs: Optional context/dependencies (context_manager, user_id, etc.)
"""
# Extract any dependencies you need
self.context_manager = kwargs.get('context_manager')
self.user_id = kwargs.get('user_id')
self.audit_log = kwargs.get('audit_log')
# Initialize any plugin-specific state
self.call_count = 0
async def execute_tool(self, name: str, arguments: Dict[str, Any]) -> List:
"""
Route tool calls to appropriate implementation methods.
Args:
name: Tool name (matches TOOLS[].name)
arguments: Tool arguments from the client
Returns:
List of MCP content objects (TextContent, ImageContent, etc.)
Raises:
ValueError: If tool name is unknown
"""
self.call_count += 1
# Route to implementation methods
if name == "template_hello":
return await self._handle_hello(arguments)
elif name == "template_echo":
return await self._handle_echo(arguments)
else:
raise ValueError(f"Unknown tool: {name}")
async def _handle_hello(self, arguments: Dict[str, Any]) -> List[types.TextContent]:
"""
Implementation of template_hello tool.
Args:
arguments: Tool arguments (contains 'name')
Returns:
Greeting message
"""
name = arguments.get("name", "World")
message = f"Hello, {name}! The plugin system is operational. (Call #{self.call_count})"
return [
types.TextContent(
type="text",
text=message
)
]
async def _handle_echo(self, arguments: Dict[str, Any]) -> List[types.TextContent]:
"""
Implementation of template_echo tool.
Args:
arguments: Tool arguments (contains 'message' and optional 'uppercase')
Returns:
Echoed message
"""
message = arguments["message"]
uppercase = arguments.get("uppercase", False)
if uppercase:
message = message.upper()
return [
types.TextContent(
type="text",
text=f"Echo: {message}"
)
]
# =============================================================================
# NOTES FOR PLUGIN DEVELOPERS
# =============================================================================
"""
## Plugin Development Tips
### Error Handling
- The plugin loader catches exceptions during loading, so syntax errors won't crash the server
- Runtime exceptions in execute_tool() are caught and logged by the MCP server
- Return clear error messages to help users understand what went wrong
### Dependencies
- You can import from other DSS modules: from ..context.project_context import get_context_manager
- Keep dependencies minimal - plugins should be self-contained
- Standard library and existing DSS dependencies only (no new pip packages without discussion)
### Testing
- Test your plugin by:
1. Restarting the MCP server: supervisorctl restart dss-mcp
2. Using the MCP server directly via API: POST /api/tools/your_tool_name
3. Via Claude Code if connected to the MCP server
### Best Practices
- Use clear, descriptive tool names prefixed with your plugin name (e.g., "analytics_track_event")
- Provide comprehensive inputSchema with descriptions
- Return structured data using types.TextContent
- Log errors with logger.error() for debugging
- Keep tools focused - one tool should do one thing well
### Advanced Features
- For image results, use types.ImageContent
- For embedded resources, use types.EmbeddedResource
- Access project context via self.context_manager if injected
- Use async/await for I/O operations (API calls, database queries, etc.)
## Example Plugin Ideas
- **Network Logger**: Capture and analyze browser network requests
- **Performance Analyzer**: Measure component render times, bundle sizes
- **Workflow Helper**: Automate common development workflows
- **Integration Tools**: Connect to external services (Slack, GitHub, etc.)
- **Custom Validators**: Project-specific validation rules
"""

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"""
Hello World Plugin - Test Plugin for DSS MCP Server
Simple plugin to validate the plugin loading system is working correctly.
"""
from typing import Dict, Any, List
from mcp import types
PLUGIN_METADATA = {
"name": "Hello World Plugin",
"version": "1.0.0",
"author": "DSS Team",
"description": "Simple test plugin to validate plugin system"
}
TOOLS = [
types.Tool(
name="hello_world",
description="Simple hello world tool to test plugin loading",
inputSchema={
"type": "object",
"properties": {
"name": {
"type": "string",
"description": "Name to greet",
"default": "World"
}
}
}
),
types.Tool(
name="plugin_status",
description="Get status of the plugin system",
inputSchema={
"type": "object",
"properties": {}
}
)
]
class PluginTools:
"""Handler for hello world plugin tools"""
def __init__(self, **kwargs):
self.call_count = 0
async def execute_tool(self, name: str, arguments: Dict[str, Any]) -> List:
"""Execute tool by name"""
self.call_count += 1
if name == "hello_world":
return await self._hello_world(arguments)
elif name == "plugin_status":
return await self._plugin_status(arguments)
else:
raise ValueError(f"Unknown tool: {name}")
async def _hello_world(self, arguments: Dict[str, Any]) -> List[types.TextContent]:
"""Simple hello world implementation"""
name = arguments.get("name", "World")
message = (
f"Hello, {name}!\n\n"
f"✓ Plugin system is operational\n"
f"✓ Dynamic loading works correctly\n"
f"✓ Tool routing is functional\n"
f"✓ Call count: {self.call_count}"
)
return [
types.TextContent(
type="text",
text=message
)
]
async def _plugin_status(self, arguments: Dict[str, Any]) -> List[types.TextContent]:
"""Return plugin system status"""
status = {
"status": "operational",
"plugin_name": PLUGIN_METADATA["name"],
"plugin_version": PLUGIN_METADATA["version"],
"tools_count": len(TOOLS),
"call_count": self.call_count,
"tools": [tool.name for tool in TOOLS]
}
import json
return [
types.TextContent(
type="text",
text=json.dumps(status, indent=2)
)
]

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# MCP Server Dependencies
# Model Context Protocol
mcp>=0.9.0
# Anthropic SDK
anthropic>=0.40.0
# FastAPI & SSE
fastapi>=0.104.0
sse-starlette>=1.8.0
uvicorn[standard]>=0.24.0
# HTTP Client
httpx>=0.25.0
aiohttp>=3.9.0
# Atlassian Integrations
atlassian-python-api>=3.41.0
# Encryption
cryptography>=42.0.0
# Async Task Queue (for worker pool)
celery[redis]>=5.3.0
# Caching
redis>=5.0.0
# Environment Variables
python-dotenv>=1.0.0
# Database
aiosqlite>=0.19.0
# Logging
structlog>=23.2.0

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"""
DSS MCP Security Module
Handles encryption, decryption, and secure storage of sensitive credentials.
Uses cryptography library for AES-256 encryption with per-credential salt.
"""
import os
import json
import secrets
from typing import Optional, Dict, Any
from datetime import datetime
from cryptography.fernet import Fernet
from cryptography.hazmat.primitives import hashes
from cryptography.hazmat.primitives.kdf.pbkdf2 import PBKDF2HMAC
from cryptography.hazmat.backends import default_backend
from .config import mcp_config
from storage.json_store import read_json, write_json, SYSTEM_DIR # JSON storage
class CredentialVault:
"""
Manages encrypted credential storage.
All credentials are encrypted using Fernet (AES-128 in CBC mode)
with PBKDF2-derived keys from a master encryption key.
"""
# Master encryption key (should be set via environment variable)
MASTER_KEY = os.environ.get('DSS_ENCRYPTION_KEY', '').encode()
@classmethod
def _get_cipher_suite(cls, salt: bytes) -> Fernet:
"""Derive encryption cipher from master key and salt"""
if not cls.MASTER_KEY:
raise ValueError(
"DSS_ENCRYPTION_KEY environment variable not set. "
"Required for credential encryption."
)
# Derive key from master key using PBKDF2
kdf = PBKDF2HMAC(
algorithm=hashes.SHA256(),
length=32,
salt=salt,
iterations=100000,
backend=default_backend()
)
key = kdf.derive(cls.MASTER_KEY)
# Encode key for Fernet
import base64
key_b64 = base64.urlsafe_b64encode(key)
return Fernet(key_b64)
@classmethod
def encrypt_credential(
cls,
credential_type: str,
credential_data: Dict[str, Any],
user_id: Optional[str] = None
) -> str:
"""
Encrypt and store a credential.
Args:
credential_type: Type of credential (figma_token, jira_token, etc.)
credential_data: Dictionary containing credential details
user_id: Optional user ID for multi-tenant security
Returns:
Credential ID for later retrieval
"""
import uuid
import base64
credential_id = str(uuid.uuid4())
salt = secrets.token_bytes(16) # 128-bit salt
# Serialize credential data
json_data = json.dumps(credential_data)
# Encrypt
cipher = cls._get_cipher_suite(salt)
encrypted = cipher.encrypt(json_data.encode())
# Store in database
with get_connection() as conn:
conn.execute("""
INSERT INTO credentials (
id, credential_type, encrypted_data, salt, user_id, created_at
) VALUES (?, ?, ?, ?, ?, ?)
""", (
credential_id,
credential_type,
encrypted.decode(),
base64.b64encode(salt).decode(),
user_id,
datetime.utcnow().isoformat()
))
return credential_id
@classmethod
def decrypt_credential(
cls,
credential_id: str
) -> Optional[Dict[str, Any]]:
"""
Decrypt and retrieve a credential.
Args:
credential_id: Credential ID from encrypt_credential()
Returns:
Decrypted credential data or None if not found
"""
import base64
with get_connection() as conn:
cursor = conn.cursor()
cursor.execute("""
SELECT encrypted_data, salt FROM credentials WHERE id = ?
""", (credential_id,))
row = cursor.fetchone()
if not row:
return None
encrypted_data, salt_b64 = row
salt = base64.b64decode(salt_b64)
# Decrypt
cipher = cls._get_cipher_suite(salt)
decrypted = cipher.decrypt(encrypted_data.encode())
return json.loads(decrypted.decode())
@classmethod
def delete_credential(cls, credential_id: str) -> bool:
"""Delete a credential"""
with get_connection() as conn:
cursor = conn.cursor()
cursor.execute("DELETE FROM credentials WHERE id = ?", (credential_id,))
return cursor.rowcount > 0
@classmethod
def list_credentials(
cls,
credential_type: Optional[str] = None,
user_id: Optional[str] = None
) -> list:
"""List credentials (metadata only, not decrypted)"""
with get_connection() as conn:
cursor = conn.cursor()
query = "SELECT id, credential_type, user_id, created_at FROM credentials WHERE 1=1"
params = []
if credential_type:
query += " AND credential_type = ?"
params.append(credential_type)
if user_id:
query += " AND user_id = ?"
params.append(user_id)
cursor.execute(query, params)
return [dict(row) for row in cursor.fetchall()]
@classmethod
def rotate_encryption_key(cls) -> bool:
"""
Rotate the master encryption key.
This re-encrypts all credentials with a new master key.
Requires new key to be set in DSS_ENCRYPTION_KEY_NEW environment variable.
"""
new_key = os.environ.get('DSS_ENCRYPTION_KEY_NEW', '').encode()
if not new_key:
raise ValueError(
"DSS_ENCRYPTION_KEY_NEW environment variable not set for key rotation"
)
try:
with get_connection() as conn:
cursor = conn.cursor()
# Get all credentials
cursor.execute("SELECT id, encrypted_data, salt FROM credentials")
rows = cursor.fetchall()
# Re-encrypt with new key
for row in rows:
credential_id, encrypted_data, salt_b64 = row
import base64
salt = base64.b64decode(salt_b64)
# Decrypt with old key
old_cipher = cls._get_cipher_suite(salt)
decrypted = old_cipher.decrypt(encrypted_data.encode())
# Encrypt with new key (use new master key)
old_master = cls.MASTER_KEY
cls.MASTER_KEY = new_key
try:
new_cipher = cls._get_cipher_suite(salt)
new_encrypted = new_cipher.encrypt(decrypted)
# Update database
conn.execute(
"UPDATE credentials SET encrypted_data = ? WHERE id = ?",
(new_encrypted.decode(), credential_id)
)
finally:
cls.MASTER_KEY = old_master
# Update environment
os.environ['DSS_ENCRYPTION_KEY'] = new_key.decode()
return True
except Exception as e:
raise RuntimeError(f"Key rotation failed: {str(e)}")
@classmethod
def ensure_credentials_table(cls):
"""Ensure credentials table exists"""
with get_connection() as conn:
conn.execute("""
CREATE TABLE IF NOT EXISTS credentials (
id TEXT PRIMARY KEY,
credential_type TEXT NOT NULL,
encrypted_data TEXT NOT NULL,
salt TEXT NOT NULL,
user_id TEXT,
created_at TEXT DEFAULT CURRENT_TIMESTAMP,
updated_at TEXT DEFAULT CURRENT_TIMESTAMP
)
""")
conn.execute(
"CREATE INDEX IF NOT EXISTS idx_credentials_type ON credentials(credential_type)"
)
conn.execute(
"CREATE INDEX IF NOT EXISTS idx_credentials_user ON credentials(user_id)"
)
# Initialize table on import
CredentialVault.ensure_credentials_table()

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"""
DSS MCP Server
SSE-based Model Context Protocol server for Claude.
Provides project-isolated context and tools with user-scoped integrations.
"""
import asyncio
import json
import logging
import structlog
from typing import Optional, Dict, Any
from fastapi import FastAPI, Query, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from sse_starlette.sse import EventSourceResponse
from mcp.server import Server
from mcp import types
from .config import mcp_config, validate_config
from .context.project_context import get_context_manager
from .tools.project_tools import PROJECT_TOOLS, ProjectTools
from .tools.workflow_tools import WORKFLOW_TOOLS, WorkflowTools
from .tools.debug_tools import DEBUG_TOOLS, DebugTools
from .integrations.storybook import STORYBOOK_TOOLS
from .integrations.translations import TRANSLATION_TOOLS
from .plugin_registry import PluginRegistry
# Configure logging
logging.basicConfig(
level=mcp_config.LOG_LEVEL,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
)
logger = structlog.get_logger()
# FastAPI app for SSE endpoints
app = FastAPI(
title="DSS MCP Server",
description="Model Context Protocol server for Design System Server",
version="0.8.0"
)
# CORS configuration
app.add_middleware(
CORSMiddleware,
allow_origins=["*"], # TODO: Configure based on environment
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
# MCP Server instance
mcp_server = Server("dss-mcp")
# Initialize Plugin Registry
plugin_registry = PluginRegistry()
plugin_registry.load_plugins()
# Store active sessions
_active_sessions: Dict[str, Dict[str, Any]] = {}
def get_session_key(project_id: str, user_id: Optional[int] = None) -> str:
"""Generate session key for caching"""
return f"{project_id}:{user_id or 'anonymous'}"
@app.on_event("startup")
async def startup():
"""Startup tasks"""
logger.info("Starting DSS MCP Server")
# Validate configuration
warnings = validate_config()
if warnings:
for warning in warnings:
logger.warning(warning)
logger.info(
"DSS MCP Server started",
host=mcp_config.HOST,
port=mcp_config.PORT
)
@app.on_event("shutdown")
async def shutdown():
"""Cleanup on shutdown"""
logger.info("Shutting down DSS MCP Server")
@app.get("/health")
async def health_check():
"""Health check endpoint"""
context_manager = get_context_manager()
return {
"status": "healthy",
"server": "dss-mcp",
"version": "0.8.0",
"cache_size": len(context_manager._cache),
"active_sessions": len(_active_sessions)
}
@app.get("/sse")
async def sse_endpoint(
project_id: str = Query(..., description="Project ID for context isolation"),
user_id: Optional[int] = Query(None, description="User ID for user-scoped integrations")
):
"""
Server-Sent Events endpoint for MCP communication.
This endpoint maintains a persistent connection with the client
and streams MCP protocol messages.
"""
session_key = get_session_key(project_id, user_id)
logger.info(
"SSE connection established",
project_id=project_id,
user_id=user_id,
session_key=session_key
)
# Load project context
context_manager = get_context_manager()
try:
project_context = await context_manager.get_context(project_id, user_id)
if not project_context:
raise HTTPException(status_code=404, detail=f"Project not found: {project_id}")
except Exception as e:
logger.error("Failed to load project context", error=str(e))
raise HTTPException(status_code=500, detail=f"Failed to load project: {str(e)}")
# Create project tools instance
project_tools = ProjectTools(user_id)
# Track session
_active_sessions[session_key] = {
"project_id": project_id,
"user_id": user_id,
"connected_at": asyncio.get_event_loop().time(),
"project_tools": project_tools
}
async def event_generator():
"""Generate SSE events for MCP communication"""
try:
# Send initial connection confirmation
yield {
"event": "connected",
"data": json.dumps({
"project_id": project_id,
"project_name": project_context.name,
"available_tools": len(PROJECT_TOOLS),
"integrations_enabled": list(project_context.integrations.keys())
})
}
# Keep connection alive
while True:
await asyncio.sleep(30) # Heartbeat every 30 seconds
yield {
"event": "heartbeat",
"data": json.dumps({"timestamp": asyncio.get_event_loop().time()})
}
except asyncio.CancelledError:
logger.info("SSE connection closed", session_key=session_key)
finally:
# Cleanup session
if session_key in _active_sessions:
del _active_sessions[session_key]
return EventSourceResponse(event_generator())
# MCP Protocol Handlers
@mcp_server.list_tools()
async def list_tools() -> list[types.Tool]:
"""
List all available tools.
Tools are dynamically determined based on:
- Base DSS project tools (always available)
- Workflow orchestration tools
- Debug tools
- Storybook integration tools
- Dynamically loaded plugins
- User's enabled integrations (Figma, Jira, Confluence, etc.)
"""
# Start with base project tools
tools = PROJECT_TOOLS.copy()
# Add workflow orchestration tools
tools.extend(WORKFLOW_TOOLS)
# Add debug tools
tools.extend(DEBUG_TOOLS)
# Add Storybook integration tools
tools.extend(STORYBOOK_TOOLS)
# Add Translation tools
tools.extend(TRANSLATION_TOOLS)
# Add plugin tools
tools.extend(plugin_registry.get_all_tools())
# TODO: Add integration-specific tools based on user's enabled integrations
# This will be implemented in Phase 3
logger.debug("Listed tools", tool_count=len(tools), plugin_count=len(plugin_registry.plugins))
return tools
@mcp_server.call_tool()
async def call_tool(name: str, arguments: dict) -> list[types.TextContent]:
"""
Execute a tool by name.
Args:
name: Tool name
arguments: Tool arguments (must include project_id)
Returns:
Tool execution results
"""
logger.info("Tool called", tool_name=name, arguments=arguments)
project_id = arguments.get("project_id")
if not project_id:
return [
types.TextContent(
type="text",
text=json.dumps({"error": "project_id is required"})
)
]
# Find active session for this project
# For now, use first matching session (can be enhanced with session management)
session_key = None
project_tools = None
for key, session in _active_sessions.items():
if session["project_id"] == project_id:
session_key = key
project_tools = session["project_tools"]
break
if not project_tools:
# Create temporary tools instance
project_tools = ProjectTools()
# Check if this is a workflow tool
workflow_tool_names = [tool.name for tool in WORKFLOW_TOOLS]
debug_tool_names = [tool.name for tool in DEBUG_TOOLS]
storybook_tool_names = [tool.name for tool in STORYBOOK_TOOLS]
translation_tool_names = [tool.name for tool in TRANSLATION_TOOLS]
# Execute tool
try:
if name in workflow_tool_names:
# Handle workflow orchestration tools
from .audit import AuditLog
audit_log = AuditLog()
workflow_tools = WorkflowTools(audit_log)
result = await workflow_tools.handle_tool_call(name, arguments)
elif name in debug_tool_names:
# Handle debug tools
debug_tools = DebugTools()
result = await debug_tools.execute_tool(name, arguments)
elif name in storybook_tool_names:
# Handle Storybook tools
from .integrations.storybook import StorybookTools
storybook_tools = StorybookTools()
result = await storybook_tools.execute_tool(name, arguments)
elif name in translation_tool_names:
# Handle Translation tools
from .integrations.translations import TranslationTools
translation_tools = TranslationTools()
result = await translation_tools.execute_tool(name, arguments)
elif name in plugin_registry.handlers:
# Handle plugin tools
result = await plugin_registry.execute_tool(name, arguments)
# Plugin tools return MCP content objects directly, not dicts
if isinstance(result, list):
return result
else:
# Handle regular project tools
result = await project_tools.execute_tool(name, arguments)
return [
types.TextContent(
type="text",
text=json.dumps(result, indent=2)
)
]
except Exception as e:
logger.error("Tool execution failed", tool_name=name, error=str(e))
return [
types.TextContent(
type="text",
text=json.dumps({"error": str(e)})
)
]
@mcp_server.list_resources()
async def list_resources() -> list[types.Resource]:
"""
List available resources.
Resources provide static or dynamic content that Claude can access.
Examples: project documentation, component specs, design system guidelines.
"""
# TODO: Implement resources based on project context
# For now, return empty list
return []
@mcp_server.read_resource()
async def read_resource(uri: str) -> str:
"""
Read a specific resource by URI.
Args:
uri: Resource URI (e.g., "dss://project-id/components/Button")
Returns:
Resource content
"""
# TODO: Implement resource reading
# For now, return not implemented
return json.dumps({"error": "Resource reading not yet implemented"})
@mcp_server.list_prompts()
async def list_prompts() -> list[types.Prompt]:
"""
List available prompt templates.
Prompts provide pre-configured conversation starters for Claude.
"""
# TODO: Add DSS-specific prompt templates
# Examples: "Analyze component consistency", "Review token usage", etc.
return []
@mcp_server.get_prompt()
async def get_prompt(name: str, arguments: dict) -> types.GetPromptResult:
"""
Get a specific prompt template.
Args:
name: Prompt name
arguments: Prompt arguments
Returns:
Prompt content
"""
# TODO: Implement prompt templates
return types.GetPromptResult(
description="Prompt not found",
messages=[]
)
# API endpoint to call MCP tools directly (for testing/debugging)
@app.post("/api/tools/{tool_name}")
async def call_tool_api(tool_name: str, arguments: Dict[str, Any]):
"""
Direct API endpoint to call MCP tools.
Useful for testing tools without MCP client.
"""
project_tools = ProjectTools()
result = await project_tools.execute_tool(tool_name, arguments)
return result
# API endpoint to list active sessions
@app.get("/api/sessions")
async def list_sessions():
"""List all active SSE sessions"""
return {
"active_sessions": len(_active_sessions),
"sessions": [
{
"project_id": session["project_id"],
"user_id": session["user_id"],
"connected_at": session["connected_at"]
}
for session in _active_sessions.values()
]
}
# API endpoint to clear context cache
@app.post("/api/cache/clear")
async def clear_cache(project_id: Optional[str] = None):
"""Clear context cache for a project or all projects"""
context_manager = get_context_manager()
context_manager.clear_cache(project_id)
return {
"status": "cache_cleared",
"project_id": project_id or "all"
}
if __name__ == "__main__":
import uvicorn
logger.info(
"Starting DSS MCP Server",
host=mcp_config.HOST,
port=mcp_config.PORT
)
uvicorn.run(
"server:app",
host=mcp_config.HOST,
port=mcp_config.PORT,
reload=True,
log_level=mcp_config.LOG_LEVEL.lower()
)

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dss/mcp/tools/__init__.py Normal file
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dss/mcp/tools/analysis_tools.py Normal file
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"""
DSS MCP - Code Analysis Tools
"""
import asyncio
from typing import Dict, Any
# Adjust the import path to find the project_analyzer
# This assumes the script is run from the project root.
from tools.analysis.project_analyzer import analyze_react_project, save_analysis
class Tool:
"""Basic tool definition for MCP"""
def __init__(self, name: str, description: str, input_schema: Dict[str, Any]):
self.name = name
self.description = description
self.inputSchema = input_schema
# Define the new tool
analyze_project_tool = Tool(
name="analyze_project",
description="Analyzes a given project's structure, components, and styles. This is a long-running operation.",
input_schema={
"type": "object",
"properties": {
"project_path": {
"type": "string",
"description": "The absolute path to the project to be analyzed."
}
},
"required": ["project_path"]
}
)
class AnalysisTools:
"""
A wrapper class for analysis-related tools.
"""
def __init__(self, user_id: str = None):
self.user_id = user_id
async def execute_tool(self, tool_name: str, arguments: Dict[str, Any]) -> Dict[str, Any]:
if tool_name == "analyze_project":
return await self.analyze_project(arguments.get("project_path"))
else:
return {"error": f"Analysis tool '{tool_name}' not found."}
async def analyze_project(self, project_path: str) -> Dict[str, Any]:
"""
Triggers the analysis of a project.
"""
if not project_path:
return {"error": "project_path is a required argument."}
try:
# This is a potentially long-running task.
# In a real scenario, this should be offloaded to a background worker.
# For now, we run it asynchronously.
loop = asyncio.get_event_loop()
# Run the analysis in a separate thread to avoid blocking the event loop
analysis_data = await loop.run_in_executor(
None, analyze_react_project, project_path
)
# Save the analysis data
await loop.run_in_executor(
None, save_analysis, project_path, analysis_data
)
return {
"status": "success",
"message": f"Analysis complete for project at {project_path}.",
"graph_nodes": len(analysis_data.get("nodes", [])),
"graph_edges": len(analysis_data.get("links", []))
}
except Exception as e:
return {"error": f"An error occurred during project analysis: {str(e)}"}
# A list of all tools in this module
ANALYSIS_TOOLS = [
analyze_project_tool
]

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"""
DSS Debug Tools for MCP
This module implements the MCP tool layer that bridges Claude Code to the DSS Debug API.
It allows the LLM to inspect browser sessions, check server health, and run debug workflows.
Configuration:
DSS_DEBUG_API_URL: Base URL for the DSS Debug API (default: http://localhost:3456)
"""
import os
import json
import logging
from pathlib import Path
from typing import Dict, Any, List, Optional
from datetime import datetime
from mcp import types
try:
import httpx
except ImportError:
httpx = None
# Configure logging
logger = logging.getLogger(__name__)
# Configuration
DSS_API_URL = os.getenv("DSS_DEBUG_API_URL", "http://localhost:3456")
DEFAULT_LOG_LIMIT = 50
# Tool definitions (metadata for Claude)
DEBUG_TOOLS = [
types.Tool(
name="dss_list_browser_sessions",
description="List all browser log sessions that have been captured. Use this to find session IDs for detailed analysis.",
inputSchema={
"type": "object",
"properties": {},
"required": []
}
),
types.Tool(
name="dss_get_browser_diagnostic",
description="Get diagnostic summary for a specific browser session including log counts, error counts, and session metadata",
inputSchema={
"type": "object",
"properties": {
"session_id": {
"type": "string",
"description": "Session ID to inspect. If omitted, uses the most recent session."
}
},
"required": []
}
),
types.Tool(
name="dss_get_browser_errors",
description="Get console errors and exceptions from a browser session. Filters logs to show only errors and warnings.",
inputSchema={
"type": "object",
"properties": {
"session_id": {
"type": "string",
"description": "Session ID. Defaults to most recent if omitted."
},
"limit": {
"type": "integer",
"description": "Maximum number of errors to retrieve (default: 50)",
"default": 50
}
},
"required": []
}
),
types.Tool(
name="dss_get_browser_network",
description="Get network request logs from a browser session. Useful for checking failed API calls (404, 500) or latency issues.",
inputSchema={
"type": "object",
"properties": {
"session_id": {
"type": "string",
"description": "Session ID. Defaults to most recent if omitted."
},
"limit": {
"type": "integer",
"description": "Maximum number of entries to retrieve (default: 50)",
"default": 50
}
},
"required": []
}
),
types.Tool(
name="dss_get_server_status",
description="Quick check if the DSS Debug Server is up and running. Returns simple UP/DOWN status from health check.",
inputSchema={
"type": "object",
"properties": {},
"required": []
}
),
types.Tool(
name="dss_get_server_diagnostic",
description="Get detailed server health diagnostics including memory usage, database size, process info, and recent errors. Use for deep debugging of infrastructure.",
inputSchema={
"type": "object",
"properties": {},
"required": []
}
),
types.Tool(
name="dss_list_workflows",
description="List available debug workflows that can be executed. Workflows are predefined diagnostic procedures.",
inputSchema={
"type": "object",
"properties": {},
"required": []
}
),
types.Tool(
name="dss_run_workflow",
description="Execute a predefined debug workflow by ID. Workflows contain step-by-step diagnostic procedures.",
inputSchema={
"type": "object",
"properties": {
"workflow_id": {
"type": "string",
"description": "The ID of the workflow to run (see dss_list_workflows for available IDs)"
}
},
"required": ["workflow_id"]
}
)
]
class DebugTools:
"""Debug tool implementations"""
def __init__(self):
self.api_base = DSS_API_URL
self.browser_logs_dir = None
def _get_browser_logs_dir(self) -> Path:
"""Get the browser logs directory path"""
if self.browser_logs_dir is None:
# Assuming we're in tools/dss_mcp/tools/debug_tools.py
# Root is 3 levels up
root = Path(__file__).parent.parent.parent.parent
self.browser_logs_dir = root / ".dss" / "browser-logs"
return self.browser_logs_dir
async def _request(
self,
method: str,
endpoint: str,
params: Optional[Dict[str, Any]] = None,
json_data: Optional[Dict[str, Any]] = None
) -> Dict[str, Any]:
"""
Internal helper to make safe HTTP requests to the DSS Debug API.
"""
if httpx is None:
return {"error": "httpx library not installed. Run: pip install httpx"}
url = f"{self.api_base.rstrip('/')}/{endpoint.lstrip('/')}"
async with httpx.AsyncClient(timeout=10.0) as client:
try:
response = await client.request(method, url, params=params, json=json_data)
# Handle non-200 responses
if response.status_code >= 400:
try:
error_detail = response.json().get("detail", response.text)
except Exception:
error_detail = response.text
return {
"error": f"API returned status {response.status_code}",
"detail": error_detail
}
# Return JSON if possible
try:
return response.json()
except Exception:
return {"result": response.text}
except httpx.ConnectError:
return {
"error": f"Could not connect to DSS Debug API at {self.api_base}",
"suggestion": "Please ensure the debug server is running (cd tools/api && python3 -m uvicorn server:app --port 3456)"
}
except httpx.TimeoutException:
return {"error": f"Request to DSS Debug API timed out ({url})"}
except Exception as e:
logger.error(f"DSS API Request failed: {e}")
return {"error": f"Unexpected error: {str(e)}"}
def _get_latest_session_id(self) -> Optional[str]:
"""Get the most recent browser session ID from filesystem"""
logs_dir = self._get_browser_logs_dir()
if not logs_dir.exists():
return None
# Get all .json files
json_files = list(logs_dir.glob("*.json"))
if not json_files:
return None
# Sort by modification time, most recent first
json_files.sort(key=lambda p: p.stat().st_mtime, reverse=True)
# Return filename without .json extension
return json_files[0].stem
async def execute_tool(self, tool_name: str, arguments: Dict[str, Any]) -> Dict[str, Any]:
"""Execute a tool by name"""
handlers = {
"dss_list_browser_sessions": self.list_browser_sessions,
"dss_get_browser_diagnostic": self.get_browser_diagnostic,
"dss_get_browser_errors": self.get_browser_errors,
"dss_get_browser_network": self.get_browser_network,
"dss_get_server_status": self.get_server_status,
"dss_get_server_diagnostic": self.get_server_diagnostic,
"dss_list_workflows": self.list_workflows,
"dss_run_workflow": self.run_workflow
}
handler = handlers.get(tool_name)
if not handler:
return {"error": f"Unknown tool: {tool_name}"}
try:
result = await handler(**arguments)
return result
except Exception as e:
logger.error(f"Tool execution failed: {e}")
return {"error": str(e)}
async def list_browser_sessions(self) -> Dict[str, Any]:
"""List all browser log sessions"""
logs_dir = self._get_browser_logs_dir()
if not logs_dir.exists():
return {
"sessions": [],
"count": 0,
"message": "No browser logs directory found. Browser logger may not have captured any sessions yet."
}
# Get all .json files
json_files = list(logs_dir.glob("*.json"))
if not json_files:
return {
"sessions": [],
"count": 0,
"message": "No sessions found in browser logs directory."
}
# Sort by modification time, most recent first
json_files.sort(key=lambda p: p.stat().st_mtime, reverse=True)
sessions = []
for json_file in json_files:
try:
# Read session metadata
with open(json_file, 'r') as f:
data = json.load(f)
sessions.append({
"session_id": json_file.stem,
"exported_at": data.get("exportedAt", "unknown"),
"log_count": len(data.get("logs", [])),
"file_size_bytes": json_file.stat().st_size,
"modified_at": datetime.fromtimestamp(json_file.stat().st_mtime).isoformat()
})
except Exception as e:
logger.warning(f"Could not read session file {json_file}: {e}")
sessions.append({
"session_id": json_file.stem,
"error": f"Could not parse: {str(e)}"
})
return {
"sessions": sessions,
"count": len(sessions),
"directory": str(logs_dir)
}
async def get_browser_diagnostic(self, session_id: Optional[str] = None) -> Dict[str, Any]:
"""Get diagnostic summary for a browser session"""
# Resolve session_id
if not session_id:
session_id = self._get_latest_session_id()
if not session_id:
return {"error": "No active session found"}
# Fetch session data from API
response = await self._request("GET", f"/api/browser-logs/{session_id}")
if "error" in response:
return response
# Extract diagnostic info
logs = response.get("logs", [])
diagnostic = response.get("diagnostic", {})
# Calculate additional metrics
error_count = sum(1 for log in logs if log.get("level") in ["error", "warn"])
return {
"session_id": session_id,
"exported_at": response.get("exportedAt"),
"total_logs": len(logs),
"error_count": error_count,
"diagnostic": diagnostic,
"summary": f"Session {session_id}: {len(logs)} logs, {error_count} errors/warnings"
}
async def get_browser_errors(
self,
session_id: Optional[str] = None,
limit: int = DEFAULT_LOG_LIMIT
) -> Dict[str, Any]:
"""Get console errors from a browser session"""
# Resolve session_id
if not session_id:
session_id = self._get_latest_session_id()
if not session_id:
return {"error": "No active session found"}
# Fetch session data from API
response = await self._request("GET", f"/api/browser-logs/{session_id}")
if "error" in response:
return response
# Filter for errors and warnings
logs = response.get("logs", [])
errors = [
log for log in logs
if log.get("level") in ["error", "warn"]
]
# Apply limit
errors = errors[:limit] if limit else errors
if not errors:
return {
"session_id": session_id,
"errors": [],
"count": 0,
"message": "No errors or warnings found in this session"
}
return {
"session_id": session_id,
"errors": errors,
"count": len(errors),
"total_logs": len(logs)
}
async def get_browser_network(
self,
session_id: Optional[str] = None,
limit: int = DEFAULT_LOG_LIMIT
) -> Dict[str, Any]:
"""Get network logs from a browser session"""
# Resolve session_id
if not session_id:
session_id = self._get_latest_session_id()
if not session_id:
return {"error": "No active session found"}
# Fetch session data from API
response = await self._request("GET", f"/api/browser-logs/{session_id}")
if "error" in response:
return response
# Check if diagnostic contains network data
diagnostic = response.get("diagnostic", {})
network_logs = diagnostic.get("network", [])
if not network_logs:
# Fallback: look for logs that mention network/fetch/xhr
logs = response.get("logs", [])
network_logs = [
log for log in logs
if any(keyword in str(log.get("message", "")).lower()
for keyword in ["fetch", "xhr", "request", "response", "http"])
]
# Apply limit
network_logs = network_logs[:limit] if limit else network_logs
if not network_logs:
return {
"session_id": session_id,
"network_logs": [],
"count": 0,
"message": "No network logs recorded in this session"
}
return {
"session_id": session_id,
"network_logs": network_logs,
"count": len(network_logs)
}
async def get_server_status(self) -> Dict[str, Any]:
"""Quick health check of the debug server"""
response = await self._request("GET", "/api/debug/diagnostic")
if "error" in response:
return {
"status": "DOWN",
"error": response["error"],
"detail": response.get("detail")
}
# Extract just the status
status = response.get("status", "unknown")
health = response.get("health", {})
return {
"status": status.upper(),
"health_status": health.get("status"),
"timestamp": response.get("timestamp"),
"message": f"Server is {status}"
}
async def get_server_diagnostic(self) -> Dict[str, Any]:
"""Get detailed server diagnostics"""
response = await self._request("GET", "/api/debug/diagnostic")
if "error" in response:
return response
return response
async def list_workflows(self) -> Dict[str, Any]:
"""List available debug workflows"""
response = await self._request("GET", "/api/debug/workflows")
if "error" in response:
return response
return response
async def run_workflow(self, workflow_id: str) -> Dict[str, Any]:
"""Execute a debug workflow"""
# For now, read the workflow markdown and return its content
# In the future, this could actually execute the workflow steps
response = await self._request("GET", "/api/debug/workflows")
if "error" in response:
return response
workflows = response.get("workflows", [])
workflow = next((w for w in workflows if w.get("id") == workflow_id), None)
if not workflow:
return {
"error": f"Workflow not found: {workflow_id}",
"available_workflows": [w.get("id") for w in workflows]
}
# Read workflow file
workflow_path = workflow.get("path")
if workflow_path and Path(workflow_path).exists():
with open(workflow_path, 'r') as f:
content = f.read()
return {
"workflow_id": workflow_id,
"title": workflow.get("title"),
"content": content,
"message": "Workflow loaded. Follow the steps in the content."
}
return {
"error": "Workflow file not found",
"workflow": workflow
}

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"""
DSS Project Tools for MCP
Base tools that Claude can use to interact with DSS projects.
All tools are project-scoped and context-aware.
Tools include:
- Project Management (create, list, get, update, delete)
- Figma Integration (setup credentials, discover files, add files)
- Token Management (sync, extract, validate, detect drift)
- Component Analysis (discover, analyze, find quick wins)
- Status & Info (project status, system health)
"""
import uuid
from typing import Dict, Any, List, Optional
from datetime import datetime
from mcp import types
from ..context.project_context import get_context_manager
from ..security import CredentialVault
from ..audit import AuditLog, AuditEventType
from storage.json_store import Projects, Components, Tokens, ActivityLog # JSON storage
from ..handler import get_mcp_handler, MCPContext
# Tool definitions (metadata for Claude)
PROJECT_TOOLS = [
types.Tool(
name="dss_get_project_summary",
description="Get comprehensive project summary including components, tokens, health, and stats",
inputSchema={
"type": "object",
"properties": {
"project_id": {
"type": "string",
"description": "Project ID to query"
},
"include_components": {
"type": "boolean",
"description": "Include full component list (default: false)",
"default": False
}
},
"required": ["project_id"]
}
),
types.Tool(
name="dss_list_components",
description="List all components in a project with their properties",
inputSchema={
"type": "object",
"properties": {
"project_id": {
"type": "string",
"description": "Project ID"
},
"filter_name": {
"type": "string",
"description": "Optional: Filter by component name (partial match)"
},
"code_generated_only": {
"type": "boolean",
"description": "Optional: Only show components with generated code",
"default": False
}
},
"required": ["project_id"]
}
),
types.Tool(
name="dss_get_component",
description="Get detailed information about a specific component",
inputSchema={
"type": "object",
"properties": {
"project_id": {
"type": "string",
"description": "Project ID"
},
"component_name": {
"type": "string",
"description": "Component name (exact match)"
}
},
"required": ["project_id", "component_name"]
}
),
types.Tool(
name="dss_get_design_tokens",
description="Get all design tokens (colors, typography, spacing, etc.) for a project",
inputSchema={
"type": "object",
"properties": {
"project_id": {
"type": "string",
"description": "Project ID"
},
"token_category": {
"type": "string",
"description": "Optional: Filter by token category (colors, typography, spacing, etc.)",
"enum": ["colors", "typography", "spacing", "shadows", "borders", "all"]
}
},
"required": ["project_id"]
}
),
types.Tool(
name="dss_get_project_health",
description="Get project health score, grade, and list of issues",
inputSchema={
"type": "object",
"properties": {
"project_id": {
"type": "string",
"description": "Project ID"
}
},
"required": ["project_id"]
}
),
types.Tool(
name="dss_list_styles",
description="List design styles (text, fill, effect, grid) from Figma",
inputSchema={
"type": "object",
"properties": {
"project_id": {
"type": "string",
"description": "Project ID"
},
"style_type": {
"type": "string",
"description": "Optional: Filter by style type",
"enum": ["TEXT", "FILL", "EFFECT", "GRID", "all"]
}
},
"required": ["project_id"]
}
),
types.Tool(
name="dss_get_discovery_data",
description="Get project discovery/scan data (file counts, technologies detected, etc.)",
inputSchema={
"type": "object",
"properties": {
"project_id": {
"type": "string",
"description": "Project ID"
}
},
"required": ["project_id"]
}
),
# === Project Management Tools ===
types.Tool(
name="dss_create_project",
description="Create a new design system project",
inputSchema={
"type": "object",
"properties": {
"name": {
"type": "string",
"description": "Project name"
},
"description": {
"type": "string",
"description": "Project description"
},
"root_path": {
"type": "string",
"description": "Root directory path for the project. Can be a git URL or a local folder path."
}
},
"required": ["name", "root_path"]
}
),
types.Tool(
name="dss_list_projects",
description="List all design system projects",
inputSchema={
"type": "object",
"properties": {
"filter_status": {
"type": "string",
"description": "Optional: Filter by project status (active, archived)",
"enum": ["active", "archived", "all"]
}
}
}
),
types.Tool(
name="dss_get_project",
description="Get detailed information about a specific project",
inputSchema={
"type": "object",
"properties": {
"project_id": {
"type": "string",
"description": "Project ID"
}
},
"required": ["project_id"]
}
),
types.Tool(
name="dss_update_project",
description="Update project settings and metadata",
inputSchema={
"type": "object",
"properties": {
"project_id": {
"type": "string",
"description": "Project ID to update"
},
"updates": {
"type": "object",
"description": "Fields to update (name, description, etc.)"
}
},
"required": ["project_id", "updates"]
}
),
types.Tool(
name="dss_delete_project",
description="Delete a design system project and all its data",
inputSchema={
"type": "object",
"properties": {
"project_id": {
"type": "string",
"description": "Project ID to delete"
},
"confirm": {
"type": "boolean",
"description": "Confirmation to delete (must be true)"
}
},
"required": ["project_id", "confirm"]
}
),
# === Figma Integration Tools ===
types.Tool(
name="dss_setup_figma_credentials",
description="Setup Figma API credentials for a project",
inputSchema={
"type": "object",
"properties": {
"project_id": {
"type": "string",
"description": "Project ID"
},
"api_token": {
"type": "string",
"description": "Figma API token"
}
},
"required": ["project_id", "api_token"]
}
),
types.Tool(
name="dss_discover_figma_files",
description="Discover Figma files accessible with current credentials",
inputSchema={
"type": "object",
"properties": {
"project_id": {
"type": "string",
"description": "Project ID"
}
},
"required": ["project_id"]
}
),
types.Tool(
name="dss_add_figma_file",
description="Add a Figma file to a project for syncing",
inputSchema={
"type": "object",
"properties": {
"project_id": {
"type": "string",
"description": "Project ID"
},
"file_key": {
"type": "string",
"description": "Figma file key"
},
"file_name": {
"type": "string",
"description": "Display name for the file"
}
},
"required": ["project_id", "file_key", "file_name"]
}
),
types.Tool(
name="dss_list_figma_files",
description="List all Figma files linked to a project",
inputSchema={
"type": "object",
"properties": {
"project_id": {
"type": "string",
"description": "Project ID"
}
},
"required": ["project_id"]
}
),
# === Token Management Tools ===
types.Tool(
name="dss_sync_tokens",
description="Synchronize design tokens from Figma to project",
inputSchema={
"type": "object",
"properties": {
"project_id": {
"type": "string",
"description": "Project ID"
},
"output_format": {
"type": "string",
"description": "Output format for tokens (css, json, tailwind)",
"enum": ["css", "json", "tailwind", "figma-tokens"]
}
},
"required": ["project_id"]
}
),
types.Tool(
name="dss_extract_tokens",
description="Extract design tokens from a Figma file",
inputSchema={
"type": "object",
"properties": {
"project_id": {
"type": "string",
"description": "Project ID"
},
"file_key": {
"type": "string",
"description": "Figma file key"
}
},
"required": ["project_id", "file_key"]
}
),
types.Tool(
name="dss_validate_tokens",
description="Validate design tokens for consistency and completeness",
inputSchema={
"type": "object",
"properties": {
"project_id": {
"type": "string",
"description": "Project ID"
}
},
"required": ["project_id"]
}
),
types.Tool(
name="dss_detect_token_drift",
description="Detect inconsistencies between Figma and project tokens",
inputSchema={
"type": "object",
"properties": {
"project_id": {
"type": "string",
"description": "Project ID"
}
},
"required": ["project_id"]
}
),
# === Component Analysis Tools ===
types.Tool(
name="dss_discover_components",
description="Discover components in project codebase",
inputSchema={
"type": "object",
"properties": {
"project_id": {
"type": "string",
"description": "Project ID"
},
"path": {
"type": "string",
"description": "Optional: Specific path to scan"
}
},
"required": ["project_id"]
}
),
types.Tool(
name="dss_analyze_components",
description="Analyze components for design system alignment and quality",
inputSchema={
"type": "object",
"properties": {
"project_id": {
"type": "string",
"description": "Project ID"
}
},
"required": ["project_id"]
}
),
types.Tool(
name="dss_get_quick_wins",
description="Identify quick wins for improving design system consistency",
inputSchema={
"type": "object",
"properties": {
"project_id": {
"type": "string",
"description": "Project ID"
},
"path": {
"type": "string",
"description": "Optional: Specific path to analyze"
}
},
"required": ["project_id"]
}
),
# === Status & Info Tools ===
types.Tool(
name="dss_get_project_status",
description="Get current project status and progress",
inputSchema={
"type": "object",
"properties": {
"project_id": {
"type": "string",
"description": "Project ID"
}
},
"required": ["project_id"]
}
),
types.Tool(
name="dss_get_system_health",
description="Get overall system health and statistics",
inputSchema={
"type": "object",
"properties": {}
}
)
]
# Tool implementations
class ProjectTools:
"""Project tool implementations"""
def __init__(self, user_id: Optional[int] = None):
self.context_manager = get_context_manager()
self.user_id = user_id
self.projects_db = Projects()
async def execute_tool(self, tool_name: str, arguments: Dict[str, Any]) -> Dict[str, Any]:
"""Execute a tool by name"""
handlers = {
# Project Management
"dss_create_project": self.create_project,
"dss_list_projects": self.list_projects,
"dss_get_project": self.get_project,
# Read-only tools
"dss_get_project_summary": self.get_project_summary,
"dss_list_components": self.list_components,
"dss_get_component": self.get_component,
"dss_get_design_tokens": self.get_design_tokens,
"dss_get_project_health": self.get_project_health,
"dss_list_styles": self.list_styles,
"dss_get_discovery_.dat": self.get_discovery_data
}
handler = handlers.get(tool_name)
if not handler:
return {"error": f"Unknown or not implemented tool: {tool_name}"}
try:
result = await handler(**arguments)
return result
except Exception as e:
return {"error": str(e)}
async def create_project(self, name: str, root_path: str, description: str = "") -> Dict[str, Any]:
"""Create a new project and trigger initial analysis."""
project_id = str(uuid.uuid4())
# The `create` method in json_store handles the creation of the manifest
self.projects_db.create(
id=project_id,
name=name,
description=description
)
# We may still want to update the root_path if it's not part of the manifest
self.projects_db.update(project_id, root_path=root_path)
# Trigger the analysis as a background task
# We don't want to block the creation call
mcp_handler = get_mcp_handler()
# Create a context for the tool call
# The user_id might be important for permissions later
mcp_context = MCPContext(project_id=project_id, user_id=self.user_id)
# It's better to run this in the background and not wait for the result here
asyncio.create_task(
mcp_handler.execute_tool(
tool_name="analyze_project",
arguments={"project_path": root_path},
context=mcp_context
)
)
return {
"status": "success",
"message": "Project created successfully. Analysis has been started in the background.",
"project_id": project_id
}
async def list_projects(self, filter_status: Optional[str] = None) -> Dict[str, Any]:
"""List all projects."""
all_projects = self.projects_db.list(status=filter_status)
return {"projects": all_projects}
async def get_project(self, project_id: str) -> Dict[str, Any]:
"""Get a single project by its ID."""
project = self.projects_db.get(project_id)
if not project:
return {"error": f"Project with ID '{project_id}' not found."}
return {"project": project}
async def get_project_summary(
self,
project_id: str,
include_components: bool = False
) -> Dict[str, Any]:
"""Get comprehensive project summary"""
context = await self.context_manager.get_context(project_id, self.user_id)
if not context:
return {"error": f"Project not found: {project_id}"}
summary = {
"project_id": context.project_id,
"name": context.name,
"description": context.description,
"component_count": context.component_count,
"health": context.health,
"stats": context.stats,
"config": context.config,
"integrations_enabled": list(context.integrations.keys()),
"loaded_at": context.loaded_at.isoformat()
}
if include_components:
summary["components"] = context.components
return summary
async def list_components(
self,
project_id: str,
filter_name: Optional[str] = None,
code_generated_only: bool = False
) -> Dict[str, Any]:
"""List components with optional filtering"""
context = await self.context_manager.get_context(project_id, self.user_id)
if not context:
return {"error": f"Project not found: {project_id}"}
components = context.components
# Apply filters
if filter_name:
components = [
c for c in components
if filter_name.lower() in c['name'].lower()
]
if code_generated_only:
components = [c for c in components if c.get('code_generated')]
return {
"project_id": project_id,
"total_count": len(components),
"components": components
}
async def get_component(
self,
project_id: str,
component_name: str
) -> Dict[str, Any]:
"""Get detailed component information"""
context = await self.context_manager.get_context(project_id, self.user_id)
if not context:
return {"error": f"Project not found: {project_id}"}
# Find component by name
component = next(
(c for c in context.components if c['name'] == component_name),
None
)
if not component:
return {"error": f"Component not found: {component_name}"}
return {
"project_id": project_id,
"component": component
}
async def get_design_tokens(
self,
project_id: str,
token_category: Optional[str] = None
) -> Dict[str, Any]:
"""Get design tokens, optionally filtered by category"""
context = await self.context_manager.get_context(project_id, self.user_id)
if not context:
return {"error": f"Project not found: {project_id}"}
tokens = context.tokens
if token_category and token_category != "all":
# Filter by category
if token_category in tokens:
tokens = {token_category: tokens[token_category]}
else:
tokens = {}
return {
"project_id": project_id,
"tokens": tokens,
"categories": list(tokens.keys())
}
async def get_project_health(self, project_id: str) -> Dict[str, Any]:
"""Get project health information"""
context = await self.context_manager.get_context(project_id, self.user_id)
if not context:
return {"error": f"Project not found: {project_id}"}
return {
"project_id": project_id,
"health": context.health
}
async def list_styles(
self,
project_id: str,
style_type: Optional[str] = None
) -> Dict[str, Any]:
"""List design styles with optional type filter"""
context = await self.context_manager.get_context(project_id, self.user_id)
if not context:
return {"error": f"Project not found: {project_id}"}
styles = context.styles
if style_type and style_type != "all":
styles = [s for s in styles if s['type'] == style_type]
return {
"project_id": project_id,
"total_count": len(styles),
"styles": styles
}
async def get_discovery_data(self, project_id: str) -> Dict[str, Any]:
"""Get project discovery/scan data"""
context = await self.context_manager.get_context(project_id, self.user_id)
if not context:
return {"error": f"Project not found: {project_id}"}
return {
"project_id": project_id,
"discovery": context.discovery
}

71
dss/mcp/tools/workflow_tools.py Normal file
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"""
DSS Workflow Orchestration Tools
(This file has been modified to remove the AI orchestration logic
as per user request. The original file contained complex, multi-step
workflows that have now been stubbed out.)
"""
import json
from typing import Dict, Any, List, Optional
from datetime import datetime
from mcp import types
from ..audit import AuditLog, AuditEventType
# Workflow tool definitions
WORKFLOW_TOOLS = [
types.Tool(
name="dss_workflow_status",
description="Get status of a running workflow execution",
inputSchema={
"type": "object",
"properties": {
"workflow_id": {
"type": "string",
"description": "Workflow execution ID"
}
},
"required": ["workflow_id"]
}
)
]
class WorkflowOrchestrator:
"""
(This class has been stubbed out.)
"""
def __init__(self, audit_log: AuditLog):
self.audit_log = audit_log
self.active_workflows = {} # workflow_id -> state
def get_workflow_status(self, workflow_id: str) -> Dict[str, Any]:
"""Get current status of a workflow"""
workflow = self.active_workflows.get(workflow_id)
if not workflow:
return {"error": "Workflow not found", "workflow_id": workflow_id}
return {
"workflow_id": workflow_id,
"status": "No active workflows.",
}
# Handler class that MCP server will use
class WorkflowTools:
"""Handler for workflow orchestration tools"""
def __init__(self, audit_log: AuditLog):
self.orchestrator = WorkflowOrchestrator(audit_log)
async def handle_tool_call(self, tool_name: str, arguments: Dict[str, Any]) -> Dict[str, Any]:
"""Route tool calls to appropriate handlers"""
if tool_name == "dss_workflow_status":
return self.orchestrator.get_workflow_status(arguments["workflow_id"])
else:
return {"error": f"Unknown or deprecated workflow tool: {tool_name}"}

15
dss/models/__init__.py Normal file
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"""Pydantic models for DSS domain objects"""
from .project import Project, ProjectMetadata
from .component import Component, ComponentVariant
from .theme import Theme, DesignToken, TokenCategory
__all__ = [
"Project",
"ProjectMetadata",
"Component",
"ComponentVariant",
"Theme",
"DesignToken",
"TokenCategory",
]

27
dss/models/component.py Normal file
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"""Component models"""
from typing import Any, Dict, List, Optional
from uuid import uuid4
from pydantic import BaseModel, Field, ConfigDict
class ComponentVariant(BaseModel):
"""A variant of a component (e.g., 'outline' button)"""
model_config = ConfigDict(arbitrary_types_allowed=True)
uuid: str = Field(default_factory=lambda: str(uuid4()), description="UUID for export/import")
name: str = Field(..., description="Variant name")
props: Dict[str, Any] = Field(default_factory=dict, description="Variant-specific props")
class Component(BaseModel):
"""A design system component"""
model_config = ConfigDict(arbitrary_types_allowed=True)
uuid: str = Field(default_factory=lambda: str(uuid4()), description="UUID for export/import")
name: str = Field(..., description="Component name (e.g., 'Button')")
source: str = Field(..., description="Component source (shadcn, custom, figma)")
description: Optional[str] = Field(None, description="Component description")
variants: List[str] = Field(default_factory=list, description="Available variants")
props: Dict[str, Any] = Field(default_factory=dict, description="Component props schema")
dependencies: List[str] = Field(default_factory=list, description="Component dependencies (UUIDs)")

38
dss/models/project.py Normal file
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"""Project models"""
from datetime import datetime
from typing import Dict, List, Optional
from uuid import uuid4
from pydantic import BaseModel, Field, ConfigDict
from .theme import Theme
from .component import Component
class ProjectMetadata(BaseModel):
"""Project metadata"""
created_at: datetime = Field(default_factory=datetime.utcnow)
updated_at: datetime = Field(default_factory=datetime.utcnow)
author: Optional[str] = None
team: Optional[str] = None
tags: List[str] = Field(default_factory=list)
class Project(BaseModel):
"""A design system project"""
model_config = ConfigDict(arbitrary_types_allowed=True)
id: str = Field(..., description="Unique project ID")
uuid: str = Field(default_factory=lambda: str(uuid4()), description="UUID for export/import")
name: str = Field(..., description="Project name")
version: str = Field(default="1.0.0", description="Project version")
description: Optional[str] = Field(None, description="Project description")
theme: Theme = Field(..., description="Project theme configuration")
components: List[Component] = Field(default_factory=list, description="Project components")
metadata: ProjectMetadata = Field(default_factory=ProjectMetadata)
def get_component(self, name: str) -> Optional[Component]:
"""Get component by name"""
for component in self.components:
if component.name == name:
return component
return None

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dss/models/team_dashboard.py Normal file
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"""
Team Dashboard Models - Component-Centric Architecture
Following expert recommendation: Component is the central entity,
with team-specific views as relationships.
Expert insight: "Teams are *views*; Components are the *truth*."
"""
from pydantic import BaseModel, Field
from typing import Optional, List, Dict, Any
from datetime import datetime
from enum import Enum
class TeamRole(str, Enum):
"""Team roles for dashboard views"""
QA = "qa"
UI = "ui"
UX = "ux"
ADMIN = "admin"
class TokenSource(str, Enum):
"""Source of design tokens"""
FIGMA = "figma"
CSS = "css"
SCSS = "scss"
TAILWIND = "tailwind"
JSON = "json"
CODE = "code"
class ComplianceStatus(str, Enum):
"""Compliance check status"""
PASS = "pass"
FAIL = "fail"
WARNING = "warning"
MISSING = "missing"
class Severity(str, Enum):
"""Issue severity levels"""
CRITICAL = "critical"
HIGH = "high"
MEDIUM = "medium"
LOW = "low"
INFO = "info"
# ============================================================================
# Component-Centric Core Models
# ============================================================================
class ComponentToken(BaseModel):
"""
Tracks which design tokens a component uses (UX Team View)
Enables queries like:
- "Which components use the old 'blue-500' token?"
- "Show me all components using color tokens from Figma"
"""
id: Optional[int] = None
component_id: int
token_name: str = Field(..., description="e.g., 'color-primary-500'")
token_value: str = Field(..., description="Resolved value, e.g., '#3B82F6'")
source: TokenSource = Field(..., description="Where this token came from")
source_file: Optional[str] = Field(None, description="File path if from code")
source_line: Optional[int] = Field(None, description="Line number if from code")
figma_node_id: Optional[str] = Field(None, description="Figma node ID if from Figma")
last_synced: Optional[datetime] = None
metadata: Dict[str, Any] = Field(default_factory=dict)
class CodeMetric(BaseModel):
"""
Tracks implementation details (UI Team View)
Enables queries like:
- "Which components have high complexity but low test coverage?"
- "Show me components with the most props"
"""
id: Optional[int] = None
component_id: int
file_path: str
sloc: int = Field(..., description="Source lines of code")
complexity_score: float = Field(..., description="Cyclomatic complexity")
prop_count: int = Field(0, description="Number of props/parameters")
has_tests: bool = Field(False)
test_coverage: float = Field(0.0, description="Test coverage percentage")
dependencies_count: int = Field(0, description="Number of dependencies")
last_analyzed: datetime
metadata: Dict[str, Any] = Field(default_factory=dict)
class TestResult(BaseModel):
"""
Tracks compliance and regression tests (QA Team View)
Enables queries like:
- "Which components failed the last ESRE check?"
- "Show me components with regressions"
"""
id: Optional[int] = None
component_id: int
test_type: str = Field(..., description="'esre', 'regression', 'visual', 'unit'")
passed: bool
score: Optional[float] = Field(None, description="0.0-1.0 score if applicable")
failures: List[str] = Field(default_factory=list, description="List of failures")
diff_summary: Optional[Dict[str, Any]] = None
snapshot_id: Optional[int] = Field(None, description="Reference to snapshot")
run_at: datetime
run_by: str = Field("system", description="User or system that ran test")
metadata: Dict[str, Any] = Field(default_factory=dict)
# ============================================================================
# Supporting Models for Team Dashboards
# ============================================================================
class FigmaFile(BaseModel):
"""
Figma file tracking (UX Dashboard)
Supports multiple Figma files per project
"""
id: Optional[int] = None
project_id: int
figma_url: str
file_name: str
file_key: str
file_type: str = Field("design", description="'design' or 'dev'")
last_synced: Optional[datetime] = None
sync_status: str = Field("pending", description="'pending', 'syncing', 'success', 'error'")
error_message: Optional[str] = None
metadata: Dict[str, Any] = Field(default_factory=dict)
class ImplementationSnapshot(BaseModel):
"""
Implementation snapshot for regression testing (UI Dashboard)
"Golden Master" approach for comparison
"""
id: Optional[int] = None
project_id: int
snapshot_name: str
description: Optional[str] = None
tokens_json: Dict[str, Any] = Field(..., description="W3C DTCG format tokens")
files_hash: str = Field(..., description="Hash of all files for quick comparison")
component_count: int = Field(0)
token_count: int = Field(0)
created_at: datetime
created_by: str
is_baseline: bool = Field(False, description="Is this the baseline 'Golden Master'?")
metadata: Dict[str, Any] = Field(default_factory=dict)
class ESREDefinition(BaseModel):
"""
ESRE (Expected System Response Evaluation) Definition (QA Dashboard)
Natural language requirements that should be validated
"""
id: Optional[int] = None
project_id: int
name: str = Field(..., description="Requirement name, e.g., 'Primary Button Color'")
definition_text: str = Field(..., description="Natural language definition")
expected_value: Optional[str] = Field(None, description="Expected value if parseable")
token_type: Optional[str] = Field(None, description="Detected token type")
component_name: Optional[str] = Field(None, description="Associated component")
created_at: datetime
created_by: str
validated: bool = Field(False)
last_check: Optional[datetime] = None
metadata: Dict[str, Any] = Field(default_factory=dict)
class TokenDrift(BaseModel):
"""
Token drift detection result (UI Dashboard)
Tracks when code uses values that differ from design tokens
"""
id: Optional[int] = None
component_id: int
property_name: str = Field(..., description="CSS property or prop name")
hardcoded_value: str = Field(..., description="The hardcoded value found")
suggested_token: Optional[str] = Field(None, description="Suggested token to use")
confidence: float = Field(..., description="0.0-1.0 confidence in suggestion")
severity: Severity
file_path: str
line_number: int
detected_at: datetime
resolved: bool = Field(False)
metadata: Dict[str, Any] = Field(default_factory=dict)
# ============================================================================
# Dashboard View Models (API Responses)
# ============================================================================
class DashboardSummary(BaseModel):
"""
Summary for dashboard overview
This is the "thin slice" endpoint response
"""
project_id: int
project_name: str
total_components: int
# UX metrics
figma_files_count: int
figma_sync_status: str
total_tokens: int
# UI metrics
token_drift_count: int
high_complexity_components: int
low_coverage_components: int
# QA metrics
esre_definitions_count: int
failed_tests_count: int
regression_issues_count: int
last_updated: datetime
metadata: Dict[str, Any] = Field(default_factory=dict)
class QADashboardView(BaseModel):
"""QA Dashboard data"""
esre_definitions: List[ESREDefinition]
failed_tests: List[TestResult]
compliance_rate: float
recent_checks: List[TestResult]
class UIDashboardView(BaseModel):
"""UI Dashboard data"""
token_drifts: List[TokenDrift]
high_complexity_components: List[Dict[str, Any]]
recent_snapshots: List[ImplementationSnapshot]
metrics_summary: Dict[str, Any]
class UXDashboardView(BaseModel):
"""UX Dashboard data"""
figma_files: List[FigmaFile]
component_tokens: List[ComponentToken]
recent_syncs: List[Dict[str, Any]]
sync_status: Dict[str, Any]

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"""Theme and design token models"""
from datetime import datetime
from enum import Enum
from typing import Any, Dict, Optional
from uuid import uuid4
from pydantic import BaseModel, Field, ConfigDict
class TokenCategory(str, Enum):
"""Categories of design tokens"""
COLOR = "color"
SPACING = "spacing"
TYPOGRAPHY = "typography"
RADIUS = "radius"
SHADOW = "shadow"
BORDER = "border"
OTHER = "other"
class DesignToken(BaseModel):
"""A single design token with value and metadata"""
model_config = ConfigDict(arbitrary_types_allowed=True)
uuid: str = Field(default_factory=lambda: str(uuid4()), description="UUID for export/import")
name: str = Field(..., description="Token name (e.g., 'primary', 'space-md')")
value: Any = Field(..., description="Token value (can be string, number, object)")
type: str = Field(..., description="Token type (color, dimension, etc.)")
category: TokenCategory = Field(default=TokenCategory.OTHER, description="Token category")
description: Optional[str] = Field(None, description="Human-readable description")
source: Optional[str] = Field(None, description="Source attribution (e.g., 'figma:abc123')")
deprecated: bool = Field(default=False, description="Is this token deprecated?")
created_at: datetime = Field(default_factory=datetime.utcnow, description="Creation timestamp")
updated_at: datetime = Field(default_factory=datetime.utcnow, description="Update timestamp")
class Theme(BaseModel):
"""Complete theme configuration"""
model_config = ConfigDict(arbitrary_types_allowed=True)
uuid: str = Field(default_factory=lambda: str(uuid4()), description="UUID for export/import")
name: str = Field(..., description="Theme name")
version: str = Field(default="1.0.0", description="Theme version")
tokens: Dict[str, DesignToken] = Field(default_factory=dict, description="All design tokens")
created_at: datetime = Field(default_factory=datetime.utcnow, description="Creation timestamp")
updated_at: datetime = Field(default_factory=datetime.utcnow, description="Update timestamp")
def get_tokens_by_category(self, category: TokenCategory) -> Dict[str, DesignToken]:
"""Filter tokens by category"""
return {
name: token
for name, token in self.tokens.items()
if token.category == category
}

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"""
DSS Project Management Module
Handles project lifecycle: initialization, configuration, syncing, and building.
DSS "eats its own dog food" - the shadcn/ui Figma (team 857274453634536756)
is the canonical base layer. All skins and projects inherit from it.
"""
from dss.project.models import (
DSSProject,
ProjectConfig,
FigmaSource,
FigmaFile,
OutputConfig,
ProjectStatus,
)
from dss.project.manager import (
ProjectManager,
ProjectRegistry,
)
from dss.project.figma import (
FigmaProjectSync,
FigmaRateLimitError,
RateLimitConfig,
RateLimitState,
)
from dss.project.core import (
DSS_FIGMA_REFERENCE,
DSSFigmaReference,
DSS_CORE_TOKEN_CATEGORIES,
DSS_CORE_COMPONENTS,
DSS_CORE_THEMES,
get_dss_figma_reference,
ensure_dss_directories,
is_dss_core_component,
get_component_variants,
)
from dss.project.sync import (
DSSCoreSync,
sync_dss_core,
get_dss_core_status,
get_dss_core_tokens,
get_dss_core_themes,
)
__all__ = [
# Models
"DSSProject",
"ProjectConfig",
"FigmaSource",
"FigmaFile",
"OutputConfig",
"ProjectStatus",
# Manager
"ProjectManager",
"ProjectRegistry",
# Figma
"FigmaProjectSync",
"FigmaRateLimitError",
"RateLimitConfig",
"RateLimitState",
# Core
"DSS_FIGMA_REFERENCE",
"DSSFigmaReference",
"DSS_CORE_TOKEN_CATEGORIES",
"DSS_CORE_COMPONENTS",
"DSS_CORE_THEMES",
"get_dss_figma_reference",
"ensure_dss_directories",
"is_dss_core_component",
"get_component_variants",
# Sync
"DSSCoreSync",
"sync_dss_core",
"get_dss_core_status",
"get_dss_core_tokens",
"get_dss_core_themes",
]

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"""
DSS Core Configuration
Defines the canonical DSS design system reference.
DSS "eats its own dog food" - using shadcn/ui as the base layer.
Hierarchy:
1. DSS Core (shadcn/ui from Figma) - immutable base
2. Skins - themed variations (material, ant, custom)
3. Projects - customer customizations
"""
from dataclasses import dataclass
from pathlib import Path
from typing import Optional
# =============================================================================
# DSS CANONICAL FIGMA REFERENCE
# =============================================================================
@dataclass(frozen=True)
class DSSFigmaReference:
"""Immutable reference to DSS's canonical Figma source."""
team_id: str = "857274453634536756"
team_name: str = "bruno.sarlo.uy"
project_id: str = "10864574"
project_name: str = "DSS"
uikit_file_key: str = "evCZlaeZrP7X20NIViSJbl"
uikit_file_name: str = "Obra shadcn/ui (Community)"
# Singleton instance - THE canonical DSS Figma reference
DSS_FIGMA_REFERENCE = DSSFigmaReference()
# =============================================================================
# DSS CORE PATHS
# =============================================================================
# DSS installation paths
DSS_ROOT = Path("/home/overbits/dss")
DSS_MVP1 = DSS_ROOT / "dss-mvp1"
DSS_CORE_DIR = DSS_MVP1 / "dss" / "core_tokens"
# User data paths
DSS_USER_DIR = Path.home() / ".dss"
DSS_CACHE_DIR = DSS_USER_DIR / "cache"
DSS_REGISTRY_FILE = DSS_USER_DIR / "registry.json"
# =============================================================================
# DSS CORE TOKENS STRUCTURE
# =============================================================================
DSS_CORE_TOKEN_CATEGORIES = {
"colors": {
"description": "Color palette based on shadcn/ui",
"includes": [
"background", "foreground", "card", "popover", "primary",
"secondary", "muted", "accent", "destructive", "border",
"input", "ring", "chart"
]
},
"typography": {
"description": "Typography scale from shadcn/ui",
"includes": [
"heading-1", "heading-2", "heading-3", "heading-4",
"paragraph-large", "paragraph-small", "label", "caption"
]
},
"spacing": {
"description": "Spacing scale",
"includes": ["0", "1", "2", "3", "4", "5", "6", "8", "10", "12", "16", "20", "24"]
},
"radius": {
"description": "Border radius values",
"includes": ["none", "sm", "md", "lg", "xl", "full"]
},
"shadows": {
"description": "Shadow/elevation scale",
"includes": ["none", "sm", "md", "lg", "xl", "2xl", "inner"]
}
}
# =============================================================================
# DSS CORE COMPONENTS
# =============================================================================
DSS_CORE_COMPONENTS = {
# Primitives
"Button": {"variants": ["default", "destructive", "outline", "secondary", "ghost", "link"]},
"Input": {"variants": ["default", "file"]},
"Textarea": {"variants": ["default"]},
"Select": {"variants": ["default"]},
"Checkbox": {"variants": ["default"]},
"Radio": {"variants": ["default"]},
"Switch": {"variants": ["default"]},
"Slider": {"variants": ["default"]},
"Toggle": {"variants": ["default", "outline"]},
# Layout
"Card": {"variants": ["default"]},
"Separator": {"variants": ["default"]},
"AspectRatio": {"variants": ["default"]},
"ScrollArea": {"variants": ["default"]},
# Data Display
"Avatar": {"variants": ["default"]},
"Badge": {"variants": ["default", "secondary", "destructive", "outline"]},
"Table": {"variants": ["default"]},
# Feedback
"Alert": {"variants": ["default", "destructive"]},
"AlertDialog": {"variants": ["default"]},
"Progress": {"variants": ["default"]},
"Skeleton": {"variants": ["default"]},
"Toast": {"variants": ["default", "destructive"]},
"Tooltip": {"variants": ["default"]},
# Overlay
"Dialog": {"variants": ["default"]},
"Drawer": {"variants": ["default"]},
"Popover": {"variants": ["default"]},
"DropdownMenu": {"variants": ["default"]},
"ContextMenu": {"variants": ["default"]},
"Sheet": {"variants": ["default"]},
"HoverCard": {"variants": ["default"]},
# Navigation
"Tabs": {"variants": ["default"]},
"NavigationMenu": {"variants": ["default"]},
"Breadcrumb": {"variants": ["default"]},
"Pagination": {"variants": ["default"]},
"Menubar": {"variants": ["default"]},
# Form
"Form": {"variants": ["default"]},
"Label": {"variants": ["default"]},
"Calendar": {"variants": ["default"]},
"DatePicker": {"variants": ["default"]},
"Combobox": {"variants": ["default"]},
# Data
"DataTable": {"variants": ["default"]},
"Command": {"variants": ["default"]},
# Layout Containers
"Accordion": {"variants": ["default"]},
"Collapsible": {"variants": ["default"]},
"Carousel": {"variants": ["default"]},
"Resizable": {"variants": ["default"]},
}
# =============================================================================
# DSS CORE THEMES
# =============================================================================
DSS_CORE_THEMES = {
"light": {
"description": "Default light theme based on shadcn/ui zinc",
"colors": {
"background": "0 0% 100%",
"foreground": "240 10% 3.9%",
"card": "0 0% 100%",
"card-foreground": "240 10% 3.9%",
"popover": "0 0% 100%",
"popover-foreground": "240 10% 3.9%",
"primary": "240 5.9% 10%",
"primary-foreground": "0 0% 98%",
"secondary": "240 4.8% 95.9%",
"secondary-foreground": "240 5.9% 10%",
"muted": "240 4.8% 95.9%",
"muted-foreground": "240 3.8% 46.1%",
"accent": "240 4.8% 95.9%",
"accent-foreground": "240 5.9% 10%",
"destructive": "0 84.2% 60.2%",
"destructive-foreground": "0 0% 98%",
"border": "240 5.9% 90%",
"input": "240 5.9% 90%",
"ring": "240 5.9% 10%",
}
},
"dark": {
"description": "Default dark theme based on shadcn/ui zinc",
"colors": {
"background": "240 10% 3.9%",
"foreground": "0 0% 98%",
"card": "240 10% 3.9%",
"card-foreground": "0 0% 98%",
"popover": "240 10% 3.9%",
"popover-foreground": "0 0% 98%",
"primary": "0 0% 98%",
"primary-foreground": "240 5.9% 10%",
"secondary": "240 3.7% 15.9%",
"secondary-foreground": "0 0% 98%",
"muted": "240 3.7% 15.9%",
"muted-foreground": "240 5% 64.9%",
"accent": "240 3.7% 15.9%",
"accent-foreground": "0 0% 98%",
"destructive": "0 62.8% 30.6%",
"destructive-foreground": "0 0% 98%",
"border": "240 3.7% 15.9%",
"input": "240 3.7% 15.9%",
"ring": "240 4.9% 83.9%",
}
}
}
# =============================================================================
# HELPER FUNCTIONS
# =============================================================================
def get_dss_figma_reference() -> DSSFigmaReference:
"""Get the canonical DSS Figma reference."""
return DSS_FIGMA_REFERENCE
def get_core_token_path(category: str) -> Optional[Path]:
"""Get path to core token file for a category."""
if category not in DSS_CORE_TOKEN_CATEGORIES:
return None
return DSS_CORE_DIR / f"{category}.json"
def ensure_dss_directories():
"""Ensure DSS system directories exist."""
DSS_USER_DIR.mkdir(parents=True, exist_ok=True)
DSS_CACHE_DIR.mkdir(parents=True, exist_ok=True)
DSS_CORE_DIR.mkdir(parents=True, exist_ok=True)
def is_dss_core_component(name: str) -> bool:
"""Check if a component is part of DSS core."""
return name in DSS_CORE_COMPONENTS
def get_component_variants(name: str) -> list:
"""Get variants for a DSS core component."""
comp = DSS_CORE_COMPONENTS.get(name, {})
return comp.get("variants", [])

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"""
Figma Integration for DSS Projects
Handles Figma API communication, project/file listing, and token extraction.
Includes rate limit handling with exponential backoff.
"""
import os
import json
import asyncio
import time
from datetime import datetime
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple
from dataclasses import dataclass, field
import logging
logger = logging.getLogger(__name__)
# =============================================================================
# RATE LIMIT CONFIGURATION
# =============================================================================
@dataclass
class RateLimitConfig:
"""Configuration for rate limit handling."""
max_retries: int = 5
initial_delay: float = 1.0 # seconds
max_delay: float = 60.0 # seconds
backoff_factor: float = 2.0
jitter: float = 0.1 # Random jitter factor
@dataclass
class RateLimitState:
"""Track rate limit state across requests."""
remaining: Optional[int] = None
reset_time: Optional[float] = None
last_request_time: float = 0
consecutive_429s: int = 0
def update_from_headers(self, headers: Dict[str, str]):
"""Update state from Figma response headers."""
if 'X-RateLimit-Remaining' in headers:
self.remaining = int(headers['X-RateLimit-Remaining'])
if 'X-RateLimit-Reset' in headers:
self.reset_time = float(headers['X-RateLimit-Reset'])
self.last_request_time = time.time()
def get_wait_time(self) -> float:
"""Calculate wait time before next request."""
if self.reset_time and self.remaining is not None and self.remaining <= 0:
wait = max(0, self.reset_time - time.time())
return wait
return 0
def record_429(self):
"""Record a 429 rate limit response."""
self.consecutive_429s += 1
self.remaining = 0
def record_success(self):
"""Record a successful request."""
self.consecutive_429s = 0
class FigmaRateLimitError(Exception):
"""Raised when rate limit is exceeded after retries."""
def __init__(self, message: str, retry_after: Optional[float] = None):
super().__init__(message)
self.retry_after = retry_after
# Optional aiohttp import for async operations
try:
import aiohttp
AIOHTTP_AVAILABLE = True
except ImportError:
AIOHTTP_AVAILABLE = False
# Fallback to requests for sync operations
try:
import requests
REQUESTS_AVAILABLE = True
except ImportError:
REQUESTS_AVAILABLE = False
@dataclass
class FigmaAPIConfig:
"""Figma API configuration."""
token: str
base_url: str = "https://api.figma.com/v1"
timeout: int = 30
rate_limit: RateLimitConfig = field(default_factory=RateLimitConfig)
@dataclass
class FigmaStyleData:
"""Extracted style data from Figma."""
colors: Dict[str, Any] = field(default_factory=dict)
typography: Dict[str, Any] = field(default_factory=dict)
effects: Dict[str, Any] = field(default_factory=dict)
grids: Dict[str, Any] = field(default_factory=dict)
variables: Dict[str, Any] = field(default_factory=dict)
raw_styles: Dict[str, Any] = field(default_factory=dict)
class FigmaProjectSync:
"""
Synchronize design tokens from Figma projects/files.
Supports:
- Listing project files
- Extracting styles from files
- Converting to DSS token format
"""
def __init__(self, token: Optional[str] = None, rate_limit_config: Optional[RateLimitConfig] = None):
"""
Initialize Figma sync.
Args:
token: Figma personal access token. Falls back to FIGMA_TOKEN env var.
rate_limit_config: Optional rate limit configuration.
"""
self.token = token or os.environ.get("FIGMA_TOKEN", "")
if not self.token:
raise ValueError("Figma token required. Set FIGMA_TOKEN env var or pass token parameter.")
self.config = FigmaAPIConfig(
token=self.token,
rate_limit=rate_limit_config or RateLimitConfig()
)
self._session: Optional[aiohttp.ClientSession] = None
self._rate_limit_state = RateLimitState()
@property
def headers(self) -> Dict[str, str]:
"""API request headers."""
return {"X-Figma-Token": self.token}
# =========================================================================
# Rate Limit Handling
# =========================================================================
def _calculate_backoff_delay(self, attempt: int, retry_after: Optional[float] = None) -> float:
"""Calculate delay with exponential backoff and jitter."""
import random
config = self.config.rate_limit
# Use Retry-After header if available
if retry_after:
base_delay = retry_after
else:
base_delay = config.initial_delay * (config.backoff_factor ** attempt)
# Cap at max delay
delay = min(base_delay, config.max_delay)
# Add jitter
jitter = delay * config.jitter * random.random()
return delay + jitter
def _request_with_retry(
self,
method: str,
url: str,
**kwargs
) -> requests.Response:
"""
Make HTTP request with rate limit retry logic.
Args:
method: HTTP method (get, post, etc.)
url: Request URL
**kwargs: Additional request arguments
Returns:
Response object
Raises:
FigmaRateLimitError: If rate limit exceeded after all retries
requests.HTTPError: For other HTTP errors
"""
if not REQUESTS_AVAILABLE:
raise ImportError("requests library required for sync operations")
config = self.config.rate_limit
last_error = None
# Pre-emptive wait if we know rate limit is exhausted
wait_time = self._rate_limit_state.get_wait_time()
if wait_time > 0:
logger.info(f"Rate limit: waiting {wait_time:.1f}s before request")
time.sleep(wait_time)
for attempt in range(config.max_retries + 1):
try:
# Make request
response = requests.request(
method,
url,
headers=self.headers,
timeout=self.config.timeout,
**kwargs
)
# Update rate limit state from headers
self._rate_limit_state.update_from_headers(dict(response.headers))
# Handle rate limit (429)
if response.status_code == 429:
self._rate_limit_state.record_429()
# Get retry-after from header
retry_after = None
if 'Retry-After' in response.headers:
try:
retry_after = float(response.headers['Retry-After'])
except ValueError:
pass
if attempt < config.max_retries:
delay = self._calculate_backoff_delay(attempt, retry_after)
logger.warning(
f"Rate limited (429). Attempt {attempt + 1}/{config.max_retries + 1}. "
f"Waiting {delay:.1f}s before retry..."
)
time.sleep(delay)
continue
else:
raise FigmaRateLimitError(
f"Rate limit exceeded after {config.max_retries} retries",
retry_after=retry_after
)
# Success
self._rate_limit_state.record_success()
response.raise_for_status()
return response
except requests.exceptions.RequestException as e:
last_error = e
if attempt < config.max_retries:
delay = self._calculate_backoff_delay(attempt)
logger.warning(
f"Request failed: {e}. Attempt {attempt + 1}/{config.max_retries + 1}. "
f"Waiting {delay:.1f}s before retry..."
)
time.sleep(delay)
continue
raise
# Should not reach here, but just in case
if last_error:
raise last_error
raise RuntimeError("Unexpected state in retry loop")
async def _request_with_retry_async(
self,
method: str,
url: str,
**kwargs
) -> Tuple[int, Dict[str, Any]]:
"""
Make async HTTP request with rate limit retry logic.
Returns:
Tuple of (status_code, response_json)
"""
if not AIOHTTP_AVAILABLE:
raise ImportError("aiohttp library required for async operations")
import random
config = self.config.rate_limit
session = await self._get_session()
last_error = None
# Pre-emptive wait if we know rate limit is exhausted
wait_time = self._rate_limit_state.get_wait_time()
if wait_time > 0:
logger.info(f"Rate limit: waiting {wait_time:.1f}s before request")
await asyncio.sleep(wait_time)
for attempt in range(config.max_retries + 1):
try:
async with session.request(method, url, **kwargs) as response:
# Update rate limit state from headers
self._rate_limit_state.update_from_headers(dict(response.headers))
# Handle rate limit (429)
if response.status == 429:
self._rate_limit_state.record_429()
retry_after = None
if 'Retry-After' in response.headers:
try:
retry_after = float(response.headers['Retry-After'])
except ValueError:
pass
if attempt < config.max_retries:
delay = self._calculate_backoff_delay(attempt, retry_after)
logger.warning(
f"Rate limited (429). Attempt {attempt + 1}/{config.max_retries + 1}. "
f"Waiting {delay:.1f}s before retry..."
)
await asyncio.sleep(delay)
continue
else:
raise FigmaRateLimitError(
f"Rate limit exceeded after {config.max_retries} retries",
retry_after=retry_after
)
# Success
self._rate_limit_state.record_success()
data = await response.json()
return response.status, data
except aiohttp.ClientError as e:
last_error = e
if attempt < config.max_retries:
delay = self._calculate_backoff_delay(attempt)
logger.warning(
f"Request failed: {e}. Attempt {attempt + 1}/{config.max_retries + 1}. "
f"Waiting {delay:.1f}s before retry..."
)
await asyncio.sleep(delay)
continue
raise
if last_error:
raise last_error
raise RuntimeError("Unexpected state in retry loop")
def get_rate_limit_status(self) -> Dict[str, Any]:
"""Get current rate limit status."""
state = self._rate_limit_state
return {
"remaining": state.remaining,
"reset_time": state.reset_time,
"reset_in_seconds": max(0, state.reset_time - time.time()) if state.reset_time else None,
"consecutive_429s": state.consecutive_429s,
"last_request_time": state.last_request_time,
}
# =========================================================================
# Sync API (uses requests)
# =========================================================================
def list_project_files(self, project_id: str) -> Dict[str, Any]:
"""
List all files in a Figma project (sync).
Args:
project_id: Figma project ID
Returns:
Dict with project name and files list
"""
url = f"{self.config.base_url}/projects/{project_id}/files"
response = self._request_with_retry("GET", url)
data = response.json()
return {
"project_name": data.get("name", ""),
"files": [
{
"key": f.get("key"),
"name": f.get("name"),
"thumbnail_url": f.get("thumbnail_url"),
"last_modified": f.get("last_modified"),
}
for f in data.get("files", [])
]
}
def list_team_projects(self, team_id: str) -> Dict[str, Any]:
"""
List all projects in a Figma team (sync).
Args:
team_id: Figma team ID
Returns:
Dict with team projects
"""
url = f"{self.config.base_url}/teams/{team_id}/projects"
response = self._request_with_retry("GET", url)
data = response.json()
return {
"team_name": data.get("name", ""),
"projects": [
{
"id": p.get("id"),
"name": p.get("name"),
}
for p in data.get("projects", [])
]
}
def discover_team_structure(self, team_id: str) -> Dict[str, Any]:
"""
Discover the full structure of a Figma team.
Returns team projects and their files, identifying the UIKit reference file.
Uses rate limit handling for all API calls.
Args:
team_id: Figma team ID
Returns:
Dict with full team structure including identified uikit file
"""
# Get all projects in team
team_data = self.list_team_projects(team_id)
result = {
"team_id": team_id,
"team_name": team_data.get("team_name", ""),
"projects": [],
"uikit": None, # Will be populated if found
}
# For each project, get files
for project in team_data.get("projects", []):
project_id = project["id"]
project_name = project["name"]
try:
project_files = self.list_project_files(project_id)
project_data = {
"id": project_id,
"name": project_name,
"files": project_files.get("files", []),
}
result["projects"].append(project_data)
# Search for UIKit file in this project
for file in project_data["files"]:
file_name_lower = file.get("name", "").lower()
# Look for common UIKit naming patterns
if any(pattern in file_name_lower for pattern in [
"uikit", "ui-kit", "ui kit",
"design system", "design-system",
"tokens", "foundations",
"core", "base"
]):
# Prefer exact "uikit" match
is_better_match = (
result["uikit"] is None or
"uikit" in file_name_lower and "uikit" not in result["uikit"]["name"].lower()
)
if is_better_match:
result["uikit"] = {
"key": file["key"],
"name": file["name"],
"project_id": project_id,
"project_name": project_name,
}
except Exception as e:
logger.warning(f"Failed to get files for project {project_name}: {e}")
return result
def find_uikit_file(self, team_id: str) -> Optional[Dict[str, Any]]:
"""
Find the UIKit reference file in a team.
Searches all projects for a file named 'uikit' or similar.
Args:
team_id: Figma team ID
Returns:
Dict with uikit file info or None if not found
"""
structure = self.discover_team_structure(team_id)
return structure.get("uikit")
def get_file_styles(self, file_key: str) -> FigmaStyleData:
"""
Extract styles from a Figma file (sync).
Uses rate limit handling with exponential backoff for all API calls.
Args:
file_key: Figma file key
Returns:
FigmaStyleData with extracted styles
"""
# Get file data with retry
url = f"{self.config.base_url}/files/{file_key}"
response = self._request_with_retry("GET", url)
file_data = response.json()
# Get styles with retry
styles_url = f"{self.config.base_url}/files/{file_key}/styles"
styles_response = self._request_with_retry("GET", styles_url)
styles_data = styles_response.json()
# Get variables (if available - newer Figma API)
variables = {}
try:
vars_url = f"{self.config.base_url}/files/{file_key}/variables/local"
vars_response = self._request_with_retry("GET", vars_url)
variables = vars_response.json()
except FigmaRateLimitError:
# Re-raise rate limit errors
raise
except Exception as e:
logger.debug(f"Variables not available for file {file_key}: {e}")
return self._parse_styles(file_data, styles_data, variables)
# =========================================================================
# Async API (uses aiohttp)
# =========================================================================
async def _get_session(self) -> aiohttp.ClientSession:
"""Get or create aiohttp session."""
if not AIOHTTP_AVAILABLE:
raise ImportError("aiohttp library required for async operations")
if self._session is None or self._session.closed:
timeout = aiohttp.ClientTimeout(total=self.config.timeout)
self._session = aiohttp.ClientSession(
headers=self.headers,
timeout=timeout
)
return self._session
async def close(self):
"""Close the aiohttp session."""
if self._session and not self._session.closed:
await self._session.close()
async def list_project_files_async(self, project_id: str) -> Dict[str, Any]:
"""List all files in a Figma project (async) with rate limit handling."""
url = f"{self.config.base_url}/projects/{project_id}/files"
status, data = await self._request_with_retry_async("GET", url)
if status != 200:
raise ValueError(f"Failed to list project files: status {status}")
return {
"project_name": data.get("name", ""),
"files": [
{
"key": f.get("key"),
"name": f.get("name"),
"thumbnail_url": f.get("thumbnail_url"),
"last_modified": f.get("last_modified"),
}
for f in data.get("files", [])
]
}
async def get_file_styles_async(self, file_key: str) -> FigmaStyleData:
"""Extract styles from a Figma file (async) with rate limit handling.
Note: Requests are made sequentially to respect rate limits.
"""
# Get file data
file_url = f"{self.config.base_url}/files/{file_key}"
file_status, file_data = await self._request_with_retry_async("GET", file_url)
if file_status != 200:
raise ValueError(f"Failed to fetch file {file_key}: status {file_status}")
# Get styles
styles_url = f"{self.config.base_url}/files/{file_key}/styles"
styles_status, styles_data = await self._request_with_retry_async("GET", styles_url)
if styles_status != 200:
styles_data = {}
# Get variables (if available - newer Figma API)
variables = {}
try:
vars_url = f"{self.config.base_url}/files/{file_key}/variables/local"
vars_status, vars_data = await self._request_with_retry_async("GET", vars_url)
if vars_status == 200:
variables = vars_data
except FigmaRateLimitError:
raise
except Exception as e:
logger.debug(f"Variables not available for file {file_key}: {e}")
return self._parse_styles(file_data, styles_data, variables)
async def sync_project_files_async(
self,
project_id: str,
file_keys: Optional[List[str]] = None
) -> Dict[str, FigmaStyleData]:
"""
Sync styles from multiple files in a project (async).
Args:
project_id: Figma project ID
file_keys: Optional list of specific file keys. If None, syncs all.
Returns:
Dict mapping file keys to their extracted styles
"""
# Get project files if not specified
if file_keys is None:
project_data = await self.list_project_files_async(project_id)
file_keys = [f["key"] for f in project_data["files"]]
# Fetch styles from all files in parallel
tasks = [self.get_file_styles_async(key) for key in file_keys]
results = await asyncio.gather(*tasks, return_exceptions=True)
styles_map = {}
for key, result in zip(file_keys, results):
if isinstance(result, Exception):
logger.error(f"Failed to sync file {key}: {result}")
else:
styles_map[key] = result
return styles_map
# =========================================================================
# Style Parsing
# =========================================================================
def _parse_styles(
self,
file_data: Dict[str, Any],
styles_data: Dict[str, Any],
variables: Dict[str, Any]
) -> FigmaStyleData:
"""Parse Figma API responses into FigmaStyleData."""
result = FigmaStyleData()
# Parse document styles
document = file_data.get("document", {})
global_styles = file_data.get("styles", {})
# Extract colors from styles
result.colors = self._extract_colors(global_styles, document)
# Extract typography
result.typography = self._extract_typography(global_styles, document)
# Extract effects (shadows, blurs)
result.effects = self._extract_effects(global_styles, document)
# Extract variables (new Figma variables API)
if variables:
result.variables = self._extract_variables(variables)
# Store raw styles for reference
result.raw_styles = {
"global_styles": global_styles,
"meta": styles_data.get("meta", {}),
}
return result
def _extract_colors(
self,
global_styles: Dict[str, Any],
document: Dict[str, Any]
) -> Dict[str, Any]:
"""Extract color styles."""
colors = {}
for style_id, style in global_styles.items():
if style.get("styleType") == "FILL":
name = style.get("name", style_id)
# Normalize name to token path format
token_name = self._normalize_name(name)
colors[token_name] = {
"figma_id": style_id,
"name": name,
"description": style.get("description", ""),
}
return colors
def _extract_typography(
self,
global_styles: Dict[str, Any],
document: Dict[str, Any]
) -> Dict[str, Any]:
"""Extract typography styles."""
typography = {}
for style_id, style in global_styles.items():
if style.get("styleType") == "TEXT":
name = style.get("name", style_id)
token_name = self._normalize_name(name)
typography[token_name] = {
"figma_id": style_id,
"name": name,
"description": style.get("description", ""),
}
return typography
def _extract_effects(
self,
global_styles: Dict[str, Any],
document: Dict[str, Any]
) -> Dict[str, Any]:
"""Extract effect styles (shadows, blurs)."""
effects = {}
for style_id, style in global_styles.items():
if style.get("styleType") == "EFFECT":
name = style.get("name", style_id)
token_name = self._normalize_name(name)
effects[token_name] = {
"figma_id": style_id,
"name": name,
"description": style.get("description", ""),
}
return effects
def _extract_variables(self, variables_data: Dict[str, Any]) -> Dict[str, Any]:
"""Extract Figma variables (new API)."""
variables = {}
meta = variables_data.get("meta", {})
var_collections = meta.get("variableCollections", {})
var_values = meta.get("variables", {})
for var_id, var_data in var_values.items():
name = var_data.get("name", var_id)
resolved_type = var_data.get("resolvedType", "")
token_name = self._normalize_name(name)
variables[token_name] = {
"figma_id": var_id,
"name": name,
"type": resolved_type,
"description": var_data.get("description", ""),
"values": var_data.get("valuesByMode", {}),
}
return variables
def _normalize_name(self, name: str) -> str:
"""Normalize Figma style name to token path format."""
# Convert "Colors/Primary/500" -> "colors.primary.500"
# Convert "Typography/Heading/H1" -> "typography.heading.h1"
normalized = name.lower()
normalized = normalized.replace("/", ".")
normalized = normalized.replace(" ", "-")
normalized = normalized.replace("--", "-")
return normalized
# =========================================================================
# Token Conversion
# =========================================================================
def to_dss_tokens(self, style_data: FigmaStyleData) -> Dict[str, Any]:
"""
Convert FigmaStyleData to DSS token format.
Returns a dict compatible with DSS TokenCollection.
"""
tokens = {
"source": "figma",
"timestamp": datetime.now().isoformat(),
"tokens": {}
}
# Add color tokens
for path, data in style_data.colors.items():
tokens["tokens"][f"color.{path}"] = {
"value": None, # Will be resolved from Figma node data
"type": "color",
"source": "figma",
"metadata": data,
}
# Add typography tokens
for path, data in style_data.typography.items():
tokens["tokens"][f"typography.{path}"] = {
"value": None,
"type": "typography",
"source": "figma",
"metadata": data,
}
# Add effect tokens
for path, data in style_data.effects.items():
tokens["tokens"][f"effect.{path}"] = {
"value": None,
"type": "effect",
"source": "figma",
"metadata": data,
}
# Add variables (these have actual values)
for path, data in style_data.variables.items():
var_type = data.get("type", "").lower()
if var_type == "color":
prefix = "color"
elif var_type == "float":
prefix = "size"
elif var_type == "string":
prefix = "string"
else:
prefix = "var"
tokens["tokens"][f"{prefix}.{path}"] = {
"value": data.get("values", {}),
"type": var_type or "unknown",
"source": "figma-variable",
"metadata": data,
}
return tokens
def save_tokens(
self,
style_data: FigmaStyleData,
output_path: Path,
format: str = "json"
) -> Path:
"""
Save extracted tokens to file.
Args:
style_data: Extracted Figma styles
output_path: Directory to save to
format: Output format (json, raw)
Returns:
Path to saved file
"""
output_path = Path(output_path)
output_path.mkdir(parents=True, exist_ok=True)
if format == "json":
tokens = self.to_dss_tokens(style_data)
file_path = output_path / "figma-tokens.json"
with open(file_path, "w") as f:
json.dump(tokens, f, indent=2)
elif format == "raw":
file_path = output_path / "figma-raw.json"
with open(file_path, "w") as f:
json.dump({
"colors": style_data.colors,
"typography": style_data.typography,
"effects": style_data.effects,
"variables": style_data.variables,
}, f, indent=2)
else:
raise ValueError(f"Unknown format: {format}")
return file_path

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"""
DSS Project Manager
Handles project lifecycle operations: init, sync, build, list.
Projects inherit from DSS core (shadcn/ui) as the base layer.
The hierarchy is: DSS Core → Skins → Project customizations.
"""
import json
import os
import asyncio
from datetime import datetime
from pathlib import Path
from typing import Any, Dict, List, Optional
import logging
from dss.project.models import (
DSSProject,
ProjectConfig,
FigmaSource,
FigmaFile,
OutputConfig,
ProjectStatus,
)
from dss.project.figma import FigmaProjectSync, FigmaStyleData, FigmaRateLimitError
from dss.project.core import (
DSS_FIGMA_REFERENCE,
DSS_CORE_THEMES,
DSS_CORE_COMPONENTS,
)
from dss.project.sync import DSSCoreSync, get_dss_core_tokens, get_dss_core_themes
logger = logging.getLogger(__name__)
# Default location for DSS projects registry
DSS_PROJECTS_DIR = Path.home() / ".dss" / "projects"
DSS_REGISTRY_FILE = Path.home() / ".dss" / "registry.json"
class ProjectRegistry:
"""
Global registry of DSS projects.
Tracks all known projects across the system.
"""
def __init__(self, registry_path: Optional[Path] = None):
self.registry_path = registry_path or DSS_REGISTRY_FILE
self._projects: Dict[str, Dict[str, Any]] = {}
self._load()
def _load(self):
"""Load registry from disk."""
if self.registry_path.exists():
try:
with open(self.registry_path, "r") as f:
data = json.load(f)
self._projects = data.get("projects", {})
except Exception as e:
logger.warning(f"Failed to load registry: {e}")
self._projects = {}
else:
self._projects = {}
def _save(self):
"""Save registry to disk."""
self.registry_path.parent.mkdir(parents=True, exist_ok=True)
with open(self.registry_path, "w") as f:
json.dump({
"version": "1.0",
"updated_at": datetime.now().isoformat(),
"projects": self._projects,
}, f, indent=2)
def register(self, project: DSSProject):
"""Register a project."""
self._projects[project.config.name] = {
"name": project.config.name,
"path": str(project.path),
"status": project.status.value,
"created_at": project.config.created_at.isoformat(),
"updated_at": datetime.now().isoformat(),
}
self._save()
def unregister(self, name: str):
"""Remove a project from registry."""
if name in self._projects:
del self._projects[name]
self._save()
def get(self, name: str) -> Optional[Dict[str, Any]]:
"""Get project info by name."""
return self._projects.get(name)
def get_by_path(self, path: Path) -> Optional[Dict[str, Any]]:
"""Get project info by path."""
path_str = str(path.resolve())
for proj in self._projects.values():
if proj.get("path") == path_str:
return proj
return None
def list_all(self) -> List[Dict[str, Any]]:
"""List all registered projects."""
return list(self._projects.values())
def update_status(self, name: str, status: ProjectStatus):
"""Update project status."""
if name in self._projects:
self._projects[name]["status"] = status.value
self._projects[name]["updated_at"] = datetime.now().isoformat()
self._save()
class ProjectManager:
"""
Manages DSS project lifecycle.
Operations:
- init: Create a new project
- add_figma: Link Figma sources
- sync: Pull latest from sources
- build: Generate output files
- list: Show all projects
"""
def __init__(self, registry: Optional[ProjectRegistry] = None):
self.registry = registry or ProjectRegistry()
# =========================================================================
# Project Initialization
# =========================================================================
def init(
self,
path: Path,
name: str,
description: Optional[str] = None,
skin: Optional[str] = None,
base_theme: str = "light",
) -> DSSProject:
"""
Initialize a new DSS project.
Args:
path: Directory for the project
name: Project name
description: Optional description
skin: Base skin to extend (e.g., 'shadcn')
base_theme: Default theme variant
Returns:
Initialized DSSProject
"""
path = Path(path).resolve()
# Check if already exists
config_path = path / "ds.config.json"
if config_path.exists():
raise FileExistsError(f"Project already exists at {path}")
# Create directory structure
path.mkdir(parents=True, exist_ok=True)
(path / "tokens").mkdir(exist_ok=True)
(path / "tokens" / "figma").mkdir(exist_ok=True)
(path / "tokens" / "custom").mkdir(exist_ok=True)
(path / "tokens" / "compiled").mkdir(exist_ok=True)
(path / "themes").mkdir(exist_ok=True)
(path / "components").mkdir(exist_ok=True)
# Create config
config = ProjectConfig(
name=name,
description=description,
skin=skin,
base_theme=base_theme,
output=OutputConfig(
tokens_dir="./tokens/compiled",
themes_dir="./themes",
components_dir="./components",
),
)
# Create project
project = DSSProject(
config=config,
path=path,
status=ProjectStatus.CREATED,
)
# Save config file
self._save_config(project)
# Register project
self.registry.register(project)
logger.info(f"Initialized DSS project '{name}' at {path}")
return project
# =========================================================================
# Figma Integration
# =========================================================================
def add_figma_team(
self,
project: DSSProject,
team_id: str,
figma_token: Optional[str] = None,
auto_find_uikit: bool = True,
) -> DSSProject:
"""
Link a Figma team folder to DSS project.
The team folder is the main Figma resource. This method:
1. Discovers all projects in the team
2. Lists all files
3. Auto-identifies the UIKit reference file
Args:
project: DSS project to update
team_id: Figma team ID
figma_token: Optional Figma token
auto_find_uikit: Auto-search for UIKit file
Returns:
Updated project with team structure
"""
sync = FigmaProjectSync(token=figma_token)
# Discover full team structure
team_structure = sync.discover_team_structure(team_id)
# Create or update Figma source
if project.config.figma is None:
project.config.figma = FigmaSource(team_id=team_id)
else:
project.config.figma.team_id = team_id
# Add all files from all projects
for figma_project in team_structure.get("projects", []):
project.config.figma.project_id = figma_project["id"]
project.config.figma.project_name = figma_project["name"]
for file_data in figma_project.get("files", []):
project.config.figma.add_file(
key=file_data["key"],
name=file_data["name"],
thumbnail_url=file_data.get("thumbnail_url"),
)
# Set UIKit reference if found
uikit_info = team_structure.get("uikit")
if uikit_info:
project.config.figma.uikit_file_key = uikit_info["key"]
logger.info(f"Found UIKit file: '{uikit_info['name']}' in project '{uikit_info['project_name']}'")
total_files = sum(len(p.get("files", [])) for p in team_structure.get("projects", []))
project.config.updated_at = datetime.now()
project.status = ProjectStatus.CONFIGURED
self._save_config(project)
self.registry.update_status(project.config.name, project.status)
logger.info(f"Added Figma team {team_id} with {len(team_structure.get('projects', []))} projects, {total_files} files")
return project
def add_figma_project(
self,
project: DSSProject,
figma_project_id: str,
figma_token: Optional[str] = None,
auto_find_uikit: bool = True,
) -> DSSProject:
"""
Link a Figma project to DSS project.
Args:
project: DSS project to update
figma_project_id: Figma project ID
figma_token: Optional Figma token (uses env var if not provided)
auto_find_uikit: Auto-search for UIKit file
Returns:
Updated project with Figma files
"""
sync = FigmaProjectSync(token=figma_token)
# Get project files from Figma
project_data = sync.list_project_files(figma_project_id)
# Create or update Figma source
if project.config.figma is None:
project.config.figma = FigmaSource(project_id=figma_project_id)
else:
project.config.figma.project_id = figma_project_id
# Add all files
uikit_key = None
for file_data in project_data["files"]:
project.config.figma.add_file(
key=file_data["key"],
name=file_data["name"],
thumbnail_url=file_data.get("thumbnail_url"),
)
# Look for UIKit file
if auto_find_uikit and uikit_key is None:
file_name_lower = file_data["name"].lower()
if any(pattern in file_name_lower for pattern in [
"uikit", "ui-kit", "ui kit",
"design system", "design-system",
"tokens", "foundations",
]):
uikit_key = file_data["key"]
logger.info(f"Found UIKit file: '{file_data['name']}'")
if uikit_key:
project.config.figma.uikit_file_key = uikit_key
project.config.updated_at = datetime.now()
project.status = ProjectStatus.CONFIGURED
# Save and update registry
self._save_config(project)
self.registry.update_status(project.config.name, project.status)
logger.info(f"Added Figma project {figma_project_id} with {len(project_data['files'])} files")
return project
def add_figma_file(
self,
project: DSSProject,
file_key: str,
file_name: str,
figma_token: Optional[str] = None,
) -> DSSProject:
"""
Add a single Figma file to DSS project.
Args:
project: DSS project to update
file_key: Figma file key
file_name: Human-readable name for the file
figma_token: Optional Figma token
Returns:
Updated project
"""
if project.config.figma is None:
project.config.figma = FigmaSource()
project.config.figma.add_file(key=file_key, name=file_name)
project.config.updated_at = datetime.now()
self._save_config(project)
logger.info(f"Added Figma file '{file_name}' ({file_key})")
return project
# =========================================================================
# Sync Operations
# =========================================================================
def sync(
self,
project: DSSProject,
figma_token: Optional[str] = None,
file_keys: Optional[List[str]] = None,
) -> DSSProject:
"""
Sync project from all sources (sync version).
Uses rate limit handling with exponential backoff for Figma API.
Args:
project: Project to sync
figma_token: Optional Figma token
file_keys: Optional specific file keys to sync
Returns:
Updated project with extracted tokens
Raises:
FigmaRateLimitError: If rate limit exceeded after all retries
"""
if project.config.figma is None or not project.config.figma.files:
logger.warning("No Figma sources configured")
return project
sync = FigmaProjectSync(token=figma_token)
# Determine which files to sync
if file_keys is None:
file_keys = [f.key for f in project.config.figma.files]
# Extract from each file
all_tokens: Dict[str, Any] = {"sources": {}}
for file_key in file_keys:
try:
style_data = sync.get_file_styles(file_key)
tokens = sync.to_dss_tokens(style_data)
all_tokens["sources"][file_key] = tokens
# Save raw tokens
figma_dir = project.path / "tokens" / "figma"
figma_dir.mkdir(parents=True, exist_ok=True)
file_info = project.config.figma.get_file(file_key)
file_name = file_info.name if file_info else file_key
safe_name = file_name.replace("/", "-").replace(" ", "_").lower()
sync.save_tokens(style_data, figma_dir / safe_name, format="json")
sync.save_tokens(style_data, figma_dir / safe_name, format="raw")
# Update sync timestamp
if file_info:
file_info.last_synced = datetime.now()
logger.info(f"Synced {len(tokens.get('tokens', {}))} tokens from '{file_name}'")
except Exception as e:
logger.error(f"Failed to sync file {file_key}: {e}")
project.errors.append(f"Sync failed for {file_key}: {str(e)}")
project.extracted_tokens = all_tokens
project.config.updated_at = datetime.now()
project.status = ProjectStatus.SYNCED
self._save_config(project)
self.registry.update_status(project.config.name, project.status)
return project
async def sync_async(
self,
project: DSSProject,
figma_token: Optional[str] = None,
file_keys: Optional[List[str]] = None,
) -> DSSProject:
"""
Sync project from all sources (async version).
Fetches from multiple files in parallel.
"""
if project.config.figma is None or not project.config.figma.files:
logger.warning("No Figma sources configured")
return project
sync = FigmaProjectSync(token=figma_token)
try:
# Determine which files to sync
if file_keys is None:
file_keys = [f.key for f in project.config.figma.files]
# Parallel sync
styles_map = await sync.sync_project_files_async(
project.config.figma.project_id or "",
file_keys=file_keys
)
# Process results
all_tokens: Dict[str, Any] = {"sources": {}}
figma_dir = project.path / "tokens" / "figma"
figma_dir.mkdir(parents=True, exist_ok=True)
for file_key, style_data in styles_map.items():
tokens = sync.to_dss_tokens(style_data)
all_tokens["sources"][file_key] = tokens
# Save tokens
file_info = project.config.figma.get_file(file_key)
file_name = file_info.name if file_info else file_key
safe_name = file_name.replace("/", "-").replace(" ", "_").lower()
sync.save_tokens(style_data, figma_dir / safe_name, format="json")
if file_info:
file_info.last_synced = datetime.now()
logger.info(f"Synced {len(tokens.get('tokens', {}))} tokens from '{file_name}'")
project.extracted_tokens = all_tokens
project.config.updated_at = datetime.now()
project.status = ProjectStatus.SYNCED
self._save_config(project)
self.registry.update_status(project.config.name, project.status)
finally:
await sync.close()
return project
# =========================================================================
# Build Operations
# =========================================================================
def build(self, project: DSSProject, include_core: bool = True) -> DSSProject:
"""
Build output files from synced tokens.
Generates CSS, SCSS, JSON outputs based on project config.
Inheritance order: DSS Core → Skin → Project tokens.
Args:
project: Project to build
include_core: Whether to include DSS core tokens as base layer (default True)
Returns:
Updated project
"""
if project.extracted_tokens is None:
raise ValueError("No tokens to build. Run sync first.")
output_dir = project.path / project.config.output.tokens_dir
output_dir.mkdir(parents=True, exist_ok=True)
# Start with DSS core tokens as base layer
merged_tokens: Dict[str, Any] = {}
if include_core:
core_tokens = get_dss_core_tokens()
if core_tokens:
# Flatten core tokens into merged tokens
for category, tokens in core_tokens.get("categories", {}).items():
for token_path, token_data in tokens.items():
full_path = f"{category}.{token_path}"
merged_tokens[full_path] = {
"value": token_data.get("value"),
"type": category,
"source": "dss-core",
"metadata": token_data,
}
logger.info(f"Loaded {len(merged_tokens)} DSS core tokens as base layer")
else:
logger.warning("DSS core tokens not available. Using DSS default themes.")
# Use default themes from core.py
for theme_name, theme_data in DSS_CORE_THEMES.items():
for color_name, color_value in theme_data.get("colors", {}).items():
merged_tokens[f"color.{theme_name}.{color_name}"] = {
"value": f"hsl({color_value})",
"type": "color",
"source": "dss-defaults",
}
# Merge project tokens on top (project overrides core)
for source_tokens in project.extracted_tokens.get("sources", {}).values():
merged_tokens.update(source_tokens.get("tokens", {}))
# Generate each format
for fmt in project.config.output.formats:
try:
output_file = output_dir / f"tokens.{fmt}"
if fmt == "json":
self._generate_json(merged_tokens, output_file)
elif fmt == "css":
self._generate_css(merged_tokens, output_file)
elif fmt == "scss":
self._generate_scss(merged_tokens, output_file)
elif fmt in ("js", "ts"):
self._generate_js(merged_tokens, output_file, typescript=(fmt == "ts"))
logger.info(f"Generated {output_file}")
except Exception as e:
logger.error(f"Failed to generate {fmt}: {e}")
project.errors.append(f"Build failed for {fmt}: {str(e)}")
project.config.updated_at = datetime.now()
project.status = ProjectStatus.BUILT
self._save_config(project)
self.registry.update_status(project.config.name, project.status)
return project
def _generate_json(self, tokens: Dict[str, Any], output_path: Path):
"""Generate JSON output."""
with open(output_path, "w") as f:
json.dump(tokens, f, indent=2)
def _generate_css(self, tokens: Dict[str, Any], output_path: Path):
"""Generate CSS custom properties."""
lines = [":root {"]
for token_path, token_data in tokens.items():
css_var = "--" + token_path.replace(".", "-")
value = token_data.get("value", "/* unresolved */")
if isinstance(value, dict):
value = "/* complex value */"
lines.append(f" {css_var}: {value};")
lines.append("}")
with open(output_path, "w") as f:
f.write("\n".join(lines))
def _generate_scss(self, tokens: Dict[str, Any], output_path: Path):
"""Generate SCSS variables."""
lines = []
for token_path, token_data in tokens.items():
scss_var = "$" + token_path.replace(".", "-")
value = token_data.get("value", "null")
if isinstance(value, dict):
value = "null"
lines.append(f"{scss_var}: {value};")
with open(output_path, "w") as f:
f.write("\n".join(lines))
def _generate_js(self, tokens: Dict[str, Any], output_path: Path, typescript: bool = False):
"""Generate JS/TS module."""
# Build nested object
token_obj: Dict[str, Any] = {}
for token_path, token_data in tokens.items():
parts = token_path.split(".")
current = token_obj
for part in parts[:-1]:
if part not in current:
current[part] = {}
current = current[part]
current[parts[-1]] = token_data.get("value")
# Generate code
if typescript:
content = f"export const tokens = {json.dumps(token_obj, indent=2)} as const;\n"
else:
content = f"export const tokens = {json.dumps(token_obj, indent=2)};\n"
with open(output_path, "w") as f:
f.write(content)
# =========================================================================
# Project Loading
# =========================================================================
def load(self, path: Path) -> DSSProject:
"""Load an existing project from path."""
path = Path(path).resolve()
config_path = path / "ds.config.json"
if not config_path.exists():
raise FileNotFoundError(f"No ds.config.json found at {path}")
return DSSProject.from_config_file(config_path)
def load_by_name(self, name: str) -> DSSProject:
"""Load a project by name from registry."""
project_info = self.registry.get(name)
if project_info is None:
raise ValueError(f"Project '{name}' not found in registry")
return self.load(Path(project_info["path"]))
def list(self) -> List[Dict[str, Any]]:
"""List all registered projects."""
return self.registry.list_all()
# =========================================================================
# Helpers
# =========================================================================
def _save_config(self, project: DSSProject):
"""Save project config to ds.config.json."""
config_dict = project.to_config_dict()
with open(project.config_path, "w") as f:
json.dump(config_dict, f, indent=2)

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"""
DSS Project Models
Pydantic models for project configuration and state.
"""
from datetime import datetime
from enum import Enum
from pathlib import Path
from typing import Any, Dict, List, Optional, Union
from pydantic import BaseModel, Field, field_validator
class ProjectStatus(str, Enum):
"""Project lifecycle status."""
CREATED = "created"
CONFIGURED = "configured"
SYNCED = "synced"
BUILT = "built"
ERROR = "error"
class FigmaFile(BaseModel):
"""A single Figma file reference."""
key: str = Field(..., description="Figma file key from URL")
name: str = Field(..., description="Human-readable file name")
last_synced: Optional[datetime] = Field(None, description="Last sync timestamp")
thumbnail_url: Optional[str] = Field(None, description="Figma thumbnail URL")
class Config:
json_encoders = {datetime: lambda v: v.isoformat() if v else None}
class FigmaSource(BaseModel):
"""Figma project source configuration.
The team folder is the main Figma resource. Projects within the team
contain design files. The 'uikit' file (if present) is the primary
reference for design tokens.
"""
team_id: Optional[str] = Field(None, description="Figma team ID (main resource)")
project_id: Optional[str] = Field(None, description="Figma project ID within team")
project_name: Optional[str] = Field(None, description="Figma project name")
files: List[FigmaFile] = Field(default_factory=list, description="List of Figma files")
uikit_file_key: Optional[str] = Field(None, description="Key of the UIKit reference file")
auto_sync: bool = Field(False, description="Enable automatic sync on changes")
def add_file(self, key: str, name: str, thumbnail_url: Optional[str] = None) -> FigmaFile:
"""Add a file to the source."""
file = FigmaFile(key=key, name=name, thumbnail_url=thumbnail_url)
# Check for duplicates
if not any(f.key == key for f in self.files):
self.files.append(file)
return file
def get_file(self, key: str) -> Optional[FigmaFile]:
"""Get a file by key."""
for f in self.files:
if f.key == key:
return f
return None
class OutputConfig(BaseModel):
"""Output configuration for generated files."""
tokens_dir: str = Field("./tokens", description="Directory for token files")
themes_dir: str = Field("./themes", description="Directory for theme files")
components_dir: str = Field("./components", description="Directory for component files")
formats: List[str] = Field(
default_factory=lambda: ["css", "scss", "json"],
description="Output formats to generate"
)
@field_validator("formats")
@classmethod
def validate_formats(cls, v):
valid = {"css", "scss", "json", "js", "ts"}
for fmt in v:
if fmt not in valid:
raise ValueError(f"Invalid format: {fmt}. Must be one of {valid}")
return v
class ProjectConfig(BaseModel):
"""Main project configuration (ds.config.json)."""
name: str = Field(..., description="Project name")
version: str = Field("1.0.0", description="Project version")
description: Optional[str] = Field(None, description="Project description")
# Sources
figma: Optional[FigmaSource] = Field(None, description="Figma source configuration")
# Design system settings
skin: Optional[str] = Field(None, description="Base skin/theme to extend (e.g., 'shadcn', 'material')")
base_theme: str = Field("light", description="Default theme variant")
# Output configuration
output: OutputConfig = Field(default_factory=OutputConfig, description="Output settings")
# Metadata
created_at: datetime = Field(default_factory=datetime.now)
updated_at: datetime = Field(default_factory=datetime.now)
class Config:
json_encoders = {datetime: lambda v: v.isoformat() if v else None}
class DSSProject(BaseModel):
"""
Complete DSS Project representation.
Combines configuration with runtime state.
"""
config: ProjectConfig = Field(..., description="Project configuration")
path: Path = Field(..., description="Absolute path to project directory")
status: ProjectStatus = Field(ProjectStatus.CREATED, description="Current project status")
# Runtime state
errors: List[str] = Field(default_factory=list, description="Error messages")
warnings: List[str] = Field(default_factory=list, description="Warning messages")
# Extracted data (populated after sync)
extracted_tokens: Optional[Dict[str, Any]] = Field(None, description="Tokens from sources")
class Config:
arbitrary_types_allowed = True
json_encoders = {
datetime: lambda v: v.isoformat() if v else None,
Path: str,
}
@property
def config_path(self) -> Path:
"""Path to ds.config.json."""
return self.path / "ds.config.json"
@property
def tokens_path(self) -> Path:
"""Path to tokens directory."""
return self.path / self.config.output.tokens_dir
@property
def themes_path(self) -> Path:
"""Path to themes directory."""
return self.path / self.config.output.themes_dir
def to_config_dict(self) -> Dict[str, Any]:
"""Export configuration for saving to ds.config.json."""
return self.config.model_dump(mode="json", exclude_none=True)
@classmethod
def from_config_file(cls, config_path: Path) -> "DSSProject":
"""Load project from ds.config.json file."""
import json
if not config_path.exists():
raise FileNotFoundError(f"Config file not found: {config_path}")
with open(config_path, "r") as f:
config_data = json.load(f)
config = ProjectConfig(**config_data)
project_path = config_path.parent
return cls(
config=config,
path=project_path,
status=ProjectStatus.CONFIGURED,
)

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"""
DSS Core Sync
Syncs the canonical DSS Figma (shadcn/ui) to the DSS core tokens.
This is the base layer that all skins and projects inherit from.
"""
import json
import logging
import os
from datetime import datetime
from pathlib import Path
from typing import Any, Dict, Optional
from dss.project.core import (
DSS_FIGMA_REFERENCE,
DSS_CORE_DIR,
DSS_CACHE_DIR,
DSS_CORE_THEMES,
ensure_dss_directories,
)
from dss.project.figma import FigmaProjectSync, FigmaStyleData
logger = logging.getLogger(__name__)
class DSSCoreSync:
"""
Syncs the DSS core design system from Figma.
The shadcn/ui Figma file is the canonical source for:
- Color tokens (light/dark themes)
- Typography scale
- Spacing scale
- Component definitions
- Effects (shadows, etc.)
"""
def __init__(self, figma_token: Optional[str] = None):
"""
Initialize DSS core sync.
Args:
figma_token: Figma token. Uses FIGMA_TOKEN env var if not provided.
"""
self.figma_token = figma_token or os.environ.get("FIGMA_TOKEN")
self.reference = DSS_FIGMA_REFERENCE
ensure_dss_directories()
@property
def core_manifest_path(self) -> Path:
"""Path to DSS core manifest file."""
return DSS_CORE_DIR / "manifest.json"
@property
def core_tokens_path(self) -> Path:
"""Path to DSS core tokens file."""
return DSS_CORE_DIR / "tokens.json"
@property
def core_themes_path(self) -> Path:
"""Path to DSS core themes file."""
return DSS_CORE_DIR / "themes.json"
@property
def core_components_path(self) -> Path:
"""Path to DSS core components file."""
return DSS_CORE_DIR / "components.json"
def get_sync_status(self) -> Dict[str, Any]:
"""Get current sync status."""
manifest = self._load_manifest()
return {
"synced": manifest is not None,
"last_sync": manifest.get("last_sync") if manifest else None,
"figma_reference": {
"team_id": self.reference.team_id,
"project_id": self.reference.project_id,
"uikit_file_key": self.reference.uikit_file_key,
"uikit_file_name": self.reference.uikit_file_name,
},
"core_dir": str(DSS_CORE_DIR),
"files": {
"manifest": self.core_manifest_path.exists(),
"tokens": self.core_tokens_path.exists(),
"themes": self.core_themes_path.exists(),
"components": self.core_components_path.exists(),
}
}
def sync(self, force: bool = False) -> Dict[str, Any]:
"""
Sync DSS core from Figma.
Args:
force: Force sync even if recently synced
Returns:
Sync result with extracted data summary
"""
if not self.figma_token:
return {
"success": False,
"error": "FIGMA_TOKEN not configured. Set env var or pass token."
}
# Check if sync needed
manifest = self._load_manifest()
if manifest and not force:
last_sync = manifest.get("last_sync")
if last_sync:
# Could add time-based check here
pass
try:
# Initialize Figma sync
figma = FigmaProjectSync(token=self.figma_token)
# Extract styles from UIKit file
logger.info(f"Syncing from Figma: {self.reference.uikit_file_name}")
styles = figma.get_file_styles(self.reference.uikit_file_key)
# Process and save tokens
tokens = self._process_tokens(styles)
self._save_tokens(tokens)
# Save themes (combine Figma + defaults)
themes = self._process_themes(styles)
self._save_themes(themes)
# Save components
components = self._process_components(styles)
self._save_components(components)
# Update manifest
self._save_manifest(styles)
return {
"success": True,
"message": f"Synced DSS core from {self.reference.uikit_file_name}",
"summary": {
"colors": len(styles.colors),
"typography": len(styles.typography),
"effects": len(styles.effects),
"variables": len(styles.variables),
},
"files_written": [
str(self.core_manifest_path),
str(self.core_tokens_path),
str(self.core_themes_path),
str(self.core_components_path),
]
}
except Exception as e:
logger.exception("DSS core sync failed")
return {"success": False, "error": str(e)}
def _process_tokens(self, styles: FigmaStyleData) -> Dict[str, Any]:
"""Process Figma styles into DSS token format."""
tokens = {
"version": "1.0.0",
"source": "figma",
"figma_file": self.reference.uikit_file_key,
"synced_at": datetime.now().isoformat(),
"categories": {}
}
# Colors
tokens["categories"]["color"] = {}
for path, data in styles.colors.items():
tokens["categories"]["color"][path] = {
"value": None, # Value comes from variables or manual mapping
"figma_id": data.get("figma_id"),
"description": data.get("description", ""),
}
# Add variables as color tokens (they have actual values)
for path, data in styles.variables.items():
if data.get("type") == "COLOR":
tokens["categories"]["color"][path] = {
"value": data.get("values", {}),
"figma_id": data.get("figma_id"),
"type": "variable",
}
# Typography
tokens["categories"]["typography"] = {}
for path, data in styles.typography.items():
tokens["categories"]["typography"][path] = {
"value": None,
"figma_id": data.get("figma_id"),
"name": data.get("name"),
}
# Effects (shadows, blurs)
tokens["categories"]["effect"] = {}
for path, data in styles.effects.items():
tokens["categories"]["effect"][path] = {
"value": None,
"figma_id": data.get("figma_id"),
"name": data.get("name"),
}
return tokens
def _process_themes(self, styles: FigmaStyleData) -> Dict[str, Any]:
"""Process themes, merging Figma data with DSS defaults."""
themes = {
"version": "1.0.0",
"source": "dss-core",
"synced_at": datetime.now().isoformat(),
"themes": {}
}
# Start with DSS core defaults
for theme_name, theme_data in DSS_CORE_THEMES.items():
themes["themes"][theme_name] = {
"description": theme_data["description"],
"colors": theme_data["colors"].copy(),
"source": "dss-defaults",
}
# Overlay any Figma variables that map to themes
# (Figma variables can have modes like light/dark)
for path, data in styles.variables.items():
values_by_mode = data.get("values", {})
for mode_id, value in values_by_mode.items():
# Try to map mode to theme
# This is simplified - real implementation would use Figma mode names
pass
return themes
def _process_components(self, styles: FigmaStyleData) -> Dict[str, Any]:
"""Extract component information from Figma."""
from dss.project.core import DSS_CORE_COMPONENTS
components = {
"version": "1.0.0",
"source": "dss-core",
"synced_at": datetime.now().isoformat(),
"components": {}
}
# Start with DSS core component definitions
for name, comp_data in DSS_CORE_COMPONENTS.items():
components["components"][name] = {
"variants": comp_data.get("variants", []),
"source": "dss-core",
}
return components
def _load_manifest(self) -> Optional[Dict[str, Any]]:
"""Load existing manifest if present."""
if self.core_manifest_path.exists():
try:
with open(self.core_manifest_path, "r") as f:
return json.load(f)
except Exception:
return None
return None
def _save_manifest(self, styles: FigmaStyleData):
"""Save sync manifest."""
manifest = {
"version": "1.0.0",
"last_sync": datetime.now().isoformat(),
"figma_reference": {
"team_id": self.reference.team_id,
"team_name": self.reference.team_name,
"project_id": self.reference.project_id,
"project_name": self.reference.project_name,
"uikit_file_key": self.reference.uikit_file_key,
"uikit_file_name": self.reference.uikit_file_name,
},
"stats": {
"colors": len(styles.colors),
"typography": len(styles.typography),
"effects": len(styles.effects),
"variables": len(styles.variables),
}
}
with open(self.core_manifest_path, "w") as f:
json.dump(manifest, f, indent=2)
def _save_tokens(self, tokens: Dict[str, Any]):
"""Save tokens to file."""
with open(self.core_tokens_path, "w") as f:
json.dump(tokens, f, indent=2)
def _save_themes(self, themes: Dict[str, Any]):
"""Save themes to file."""
with open(self.core_themes_path, "w") as f:
json.dump(themes, f, indent=2)
def _save_components(self, components: Dict[str, Any]):
"""Save components to file."""
with open(self.core_components_path, "w") as f:
json.dump(components, f, indent=2)
def get_tokens(self) -> Optional[Dict[str, Any]]:
"""Load synced tokens."""
if self.core_tokens_path.exists():
with open(self.core_tokens_path, "r") as f:
return json.load(f)
return None
def get_themes(self) -> Optional[Dict[str, Any]]:
"""Load synced themes."""
if self.core_themes_path.exists():
with open(self.core_themes_path, "r") as f:
return json.load(f)
return None
def get_components(self) -> Optional[Dict[str, Any]]:
"""Load synced components."""
if self.core_components_path.exists():
with open(self.core_components_path, "r") as f:
return json.load(f)
return None
# =============================================================================
# CONVENIENCE FUNCTIONS
# =============================================================================
def sync_dss_core(figma_token: Optional[str] = None, force: bool = False) -> Dict[str, Any]:
"""Sync DSS core from Figma."""
sync = DSSCoreSync(figma_token=figma_token)
return sync.sync(force=force)
def get_dss_core_status() -> Dict[str, Any]:
"""Get DSS core sync status."""
sync = DSSCoreSync()
return sync.get_sync_status()
def get_dss_core_tokens() -> Optional[Dict[str, Any]]:
"""Get DSS core tokens (must be synced first)."""
sync = DSSCoreSync()
return sync.get_tokens()
def get_dss_core_themes() -> Optional[Dict[str, Any]]:
"""Get DSS core themes."""
sync = DSSCoreSync()
return sync.get_themes()

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"""
DSS Services - Core business logic for the Design System Server
Services:
- SandboxedFS: Secure file system operations within project boundaries
- ProjectManager: Project registry and validation
- ConfigService: Project configuration loading and saving
"""
from .sandboxed_fs import SandboxedFS
from .project_manager import ProjectManager
from .config_service import ConfigService, DSSConfig
__all__ = ['SandboxedFS', 'ProjectManager', 'ConfigService', 'DSSConfig']

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"""
ConfigService - Project Configuration Management
Handles loading, saving, and validating project-specific .dss/config.json files.
Uses Pydantic for schema validation with sensible defaults.
"""
import json
import os
from pathlib import Path
from typing import Optional, List, Dict, Any
from pydantic import BaseModel, Field
import logging
logger = logging.getLogger(__name__)
# === Configuration Schema ===
class FigmaConfig(BaseModel):
"""Figma integration settings."""
file_id: Optional[str] = None
team_id: Optional[str] = None
class TokensConfig(BaseModel):
"""Design token export settings."""
output_path: str = "./tokens"
format: str = "css" # css | scss | json | js
class AIConfig(BaseModel):
"""AI assistant behavior settings."""
allowed_operations: List[str] = Field(default_factory=lambda: ["read", "write"])
context_files: List[str] = Field(default_factory=lambda: ["./README.md"])
max_file_size_kb: int = 500
class DSSConfig(BaseModel):
"""
Complete DSS project configuration schema.
Stored in: [project_root]/.dss/config.json
"""
schema_version: str = "1.0"
figma: FigmaConfig = Field(default_factory=FigmaConfig)
tokens: TokensConfig = Field(default_factory=TokensConfig)
ai: AIConfig = Field(default_factory=AIConfig)
class Config:
# Allow extra fields for forward compatibility
extra = "allow"
# === Config Service ===
class ConfigService:
"""
Service for managing project configuration files.
Loads .dss/config.json from project roots, validates against schema,
and provides defaults when config is missing.
"""
CONFIG_FILENAME = "config.json"
DSS_FOLDER = ".dss"
def __init__(self):
"""Initialize config service."""
logger.info("ConfigService initialized")
def get_config_path(self, project_root: str) -> Path:
"""Get path to config file for a project."""
return Path(project_root) / self.DSS_FOLDER / self.CONFIG_FILENAME
def get_config(self, project_root: str) -> DSSConfig:
"""
Load configuration for a project.
Args:
project_root: Absolute path to project root directory
Returns:
DSSConfig object (defaults if config file missing)
"""
config_path = self.get_config_path(project_root)
if config_path.exists():
try:
with open(config_path) as f:
data = json.load(f)
config = DSSConfig(**data)
logger.debug(f"Loaded config from {config_path}")
return config
except (json.JSONDecodeError, Exception) as e:
logger.warning(f"Failed to parse config at {config_path}: {e}")
# Fall through to return defaults
logger.debug(f"Using default config for {project_root}")
return DSSConfig()
def save_config(self, project_root: str, config: DSSConfig) -> None:
"""
Save configuration for a project.
Args:
project_root: Absolute path to project root directory
config: DSSConfig object to save
"""
config_path = self.get_config_path(project_root)
# Ensure .dss directory exists
config_path.parent.mkdir(parents=True, exist_ok=True)
with open(config_path, 'w') as f:
json.dump(config.dict(), f, indent=2)
logger.info(f"Saved config to {config_path}")
def update_config(self, project_root: str, updates: Dict[str, Any]) -> DSSConfig:
"""
Update specific fields in project config.
Args:
project_root: Absolute path to project root directory
updates: Dictionary of fields to update
Returns:
Updated DSSConfig object
"""
config = self.get_config(project_root)
# Deep merge updates
config_dict = config.dict()
for key, value in updates.items():
if isinstance(value, dict) and isinstance(config_dict.get(key), dict):
config_dict[key].update(value)
else:
config_dict[key] = value
new_config = DSSConfig(**config_dict)
self.save_config(project_root, new_config)
return new_config
def init_config(self, project_root: str) -> DSSConfig:
"""
Initialize config file for a new project.
Creates .dss/ folder and config.json with defaults if not exists.
Args:
project_root: Absolute path to project root directory
Returns:
DSSConfig object (new or existing)
"""
config_path = self.get_config_path(project_root)
if config_path.exists():
logger.debug(f"Config already exists at {config_path}")
return self.get_config(project_root)
config = DSSConfig()
self.save_config(project_root, config)
logger.info(f"Initialized new config at {config_path}")
return config
def config_exists(self, project_root: str) -> bool:
"""Check if config file exists for a project."""
return self.get_config_path(project_root).exists()

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"""
ProjectManager - Project Registry Service
Manages the server-side registry of projects, including:
- Project registration with path validation
- Root path storage and retrieval
- Project lifecycle management
"""
import os
from pathlib import Path
from typing import Optional, List, Dict, Any
import logging
logger = logging.getLogger(__name__)
class ProjectManager:
"""
Manages project registry with root path validation.
Works with the existing Projects database class to add root_path support.
Validates paths exist and are accessible before registration.
"""
def __init__(self, projects_db, config_service=None):
"""
Initialize project manager.
Args:
projects_db: Projects database class (from storage.database)
config_service: Optional ConfigService for config initialization
"""
self.db = projects_db
self.config_service = config_service
logger.info("ProjectManager initialized")
def register_project(
self,
name: str,
root_path: str,
description: str = "",
figma_file_key: str = ""
) -> Dict[str, Any]:
"""
Register a new project with validated root path.
Args:
name: Human-readable project name
root_path: Absolute path to project directory
description: Optional project description
figma_file_key: Optional Figma file key
Returns:
Created project dict
Raises:
ValueError: If path doesn't exist or isn't a directory
PermissionError: If no write access to path
"""
# Resolve and validate path
root_path = os.path.abspath(root_path)
if not os.path.isdir(root_path):
raise ValueError(f"Path does not exist or is not a directory: {root_path}")
if not os.access(root_path, os.W_OK):
raise PermissionError(f"No write access to path: {root_path}")
# Check if path already registered
existing = self.get_by_path(root_path)
if existing:
raise ValueError(f"Path already registered as project: {existing['name']}")
# Generate project ID
import uuid
project_id = str(uuid.uuid4())[:8]
# Create project in database
project = self.db.create(
id=project_id,
name=name,
description=description,
figma_file_key=figma_file_key
)
# Update with root_path (need to add this column)
self._update_root_path(project_id, root_path)
project['root_path'] = root_path
# Initialize .dss folder and config if config_service available
if self.config_service:
try:
self.config_service.init_config(root_path)
logger.info(f"Initialized .dss config for project {name}")
except Exception as e:
logger.warning(f"Failed to init config for {name}: {e}")
logger.info(f"Registered project: {name} at {root_path}")
return project
def get_project(self, project_id: str) -> Optional[Dict[str, Any]]:
"""
Get project by ID with path validation.
Args:
project_id: Project UUID
Returns:
Project dict or None if not found
Raises:
ValueError: If project path no longer exists
"""
project = self.db.get(project_id)
if not project:
return None
root_path = project.get('root_path')
if root_path and not os.path.isdir(root_path):
logger.warning(f"Project path no longer exists: {root_path}")
# Don't raise, just mark it
project['path_valid'] = False
else:
project['path_valid'] = True
return project
def list_projects(self, status: str = None, valid_only: bool = False) -> List[Dict[str, Any]]:
"""
List all projects with optional filtering.
Args:
status: Filter by status (active, archived, etc.)
valid_only: Only return projects with valid paths
Returns:
List of project dicts
"""
projects = self.db.list(status=status)
# Add path validation status
for project in projects:
root_path = project.get('root_path')
project['path_valid'] = bool(root_path and os.path.isdir(root_path))
if valid_only:
projects = [p for p in projects if p.get('path_valid', False)]
return projects
def get_by_path(self, root_path: str) -> Optional[Dict[str, Any]]:
"""
Find project by root path.
Args:
root_path: Absolute path to search for
Returns:
Project dict or None if not found
"""
root_path = os.path.abspath(root_path)
projects = self.list_projects()
for project in projects:
if project.get('root_path') == root_path:
return project
return None
def update_project(
self,
project_id: str,
name: str = None,
description: str = None,
root_path: str = None,
figma_file_key: str = None,
status: str = None
) -> Optional[Dict[str, Any]]:
"""
Update project fields.
Args:
project_id: Project UUID
name: Optional new name
description: Optional new description
root_path: Optional new root path (validated)
figma_file_key: Optional new Figma key
status: Optional new status
Returns:
Updated project dict or None if not found
"""
project = self.db.get(project_id)
if not project:
return None
# Validate new root_path if provided
if root_path:
root_path = os.path.abspath(root_path)
if not os.path.isdir(root_path):
raise ValueError(f"Path does not exist: {root_path}")
if not os.access(root_path, os.W_OK):
raise PermissionError(f"No write access: {root_path}")
self._update_root_path(project_id, root_path)
# Update other fields via existing update method
updates = {}
if name is not None:
updates['name'] = name
if description is not None:
updates['description'] = description
if figma_file_key is not None:
updates['figma_file_key'] = figma_file_key
if status is not None:
updates['status'] = status
if updates:
self.db.update(project_id, **updates)
return self.get_project(project_id)
def delete_project(self, project_id: str, delete_config: bool = False) -> bool:
"""
Delete a project from registry.
Args:
project_id: Project UUID
delete_config: If True, also delete .dss folder
Returns:
True if deleted, False if not found
"""
project = self.db.get(project_id)
if not project:
return False
if delete_config and project.get('root_path'):
import shutil
dss_path = Path(project['root_path']) / '.dss'
if dss_path.exists():
shutil.rmtree(dss_path)
logger.info(f"Deleted .dss folder at {dss_path}")
self.db.delete(project_id)
logger.info(f"Deleted project: {project_id}")
return True
def _update_root_path(self, project_id: str, root_path: str) -> None:
"""
Update root_path in JSON storage.
"""
self.db.update(project_id, root_path=root_path)
@staticmethod
def ensure_schema():
"""
Legacy schema migration - no longer needed with JSON storage.
Kept for API compatibility.
"""
logger.debug("Schema check: Using JSON storage, no migration needed")

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"""
SandboxedFS - Secure File System Operations
This service restricts all file operations to within a project's root directory,
preventing path traversal attacks and ensuring AI operations are safely scoped.
Security Features:
- Path resolution with escape detection
- Symlink attack prevention
- Read/write operation logging
"""
import os
from pathlib import Path
from typing import List, Dict, Optional
import logging
logger = logging.getLogger(__name__)
class SandboxedFS:
"""
File system operations restricted to a project root.
All paths are validated to ensure they don't escape the sandbox.
This is critical for AI operations that may receive untrusted input.
"""
def __init__(self, root_path: str):
"""
Initialize sandboxed file system.
Args:
root_path: Absolute path to project root directory
Raises:
ValueError: If root_path doesn't exist or isn't a directory
"""
self.root = Path(root_path).resolve()
if not self.root.is_dir():
raise ValueError(f"Invalid root path: {root_path}")
logger.info(f"SandboxedFS initialized with root: {self.root}")
def _validate_path(self, relative_path: str) -> Path:
"""
Validate and resolve a path within the sandbox.
Args:
relative_path: Path relative to project root
Returns:
Resolved absolute Path within sandbox
Raises:
PermissionError: If path escapes sandbox
"""
# Normalize the path
clean_path = os.path.normpath(relative_path)
# Resolve full path
full_path = (self.root / clean_path).resolve()
# Security check: must be within root
try:
full_path.relative_to(self.root)
except ValueError:
logger.warning(f"Path traversal attempt blocked: {relative_path}")
raise PermissionError(f"Path escapes sandbox: {relative_path}")
return full_path
def read_file(self, relative_path: str, max_size_kb: int = 500) -> str:
"""
Read file content within sandbox.
Args:
relative_path: Path relative to project root
max_size_kb: Maximum file size in KB (default 500KB)
Returns:
File content as string
Raises:
FileNotFoundError: If file doesn't exist
PermissionError: If path escapes sandbox
ValueError: If file exceeds max size
"""
path = self._validate_path(relative_path)
if not path.is_file():
raise FileNotFoundError(f"File not found: {relative_path}")
# Check file size
size_kb = path.stat().st_size / 1024
if size_kb > max_size_kb:
raise ValueError(f"File too large: {size_kb:.1f}KB > {max_size_kb}KB limit")
content = path.read_text(encoding='utf-8')
logger.debug(f"Read file: {relative_path} ({len(content)} chars)")
return content
def write_file(self, relative_path: str, content: str) -> None:
"""
Write file content within sandbox.
Args:
relative_path: Path relative to project root
content: Content to write
Raises:
PermissionError: If path escapes sandbox
"""
path = self._validate_path(relative_path)
# Create parent directories if needed
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text(content, encoding='utf-8')
logger.info(f"Wrote file: {relative_path} ({len(content)} chars)")
def delete_file(self, relative_path: str) -> None:
"""
Delete file within sandbox.
Args:
relative_path: Path relative to project root
Raises:
FileNotFoundError: If file doesn't exist
PermissionError: If path escapes sandbox
"""
path = self._validate_path(relative_path)
if not path.is_file():
raise FileNotFoundError(f"File not found: {relative_path}")
path.unlink()
logger.info(f"Deleted file: {relative_path}")
def list_directory(self, relative_path: str = ".") -> List[Dict[str, any]]:
"""
List directory contents within sandbox.
Args:
relative_path: Path relative to project root
Returns:
List of dicts with name, type, and size
Raises:
NotADirectoryError: If path isn't a directory
PermissionError: If path escapes sandbox
"""
path = self._validate_path(relative_path)
if not path.is_dir():
raise NotADirectoryError(f"Not a directory: {relative_path}")
result = []
for item in sorted(path.iterdir()):
entry = {
"name": item.name,
"type": "directory" if item.is_dir() else "file",
}
if item.is_file():
entry["size"] = item.stat().st_size
result.append(entry)
return result
def file_exists(self, relative_path: str) -> bool:
"""
Check if file exists within sandbox.
Args:
relative_path: Path relative to project root
Returns:
True if file exists, False otherwise
"""
try:
path = self._validate_path(relative_path)
return path.exists()
except PermissionError:
return False
def get_file_tree(self, max_depth: int = 3, include_hidden: bool = False) -> Dict:
"""
Get hierarchical file tree for AI context injection.
Args:
max_depth: Maximum directory depth to traverse
include_hidden: Include hidden files (starting with .)
Returns:
Nested dict representing file tree with sizes
"""
def build_tree(path: Path, depth: int) -> Dict:
if depth > max_depth:
return {"...": "truncated"}
result = {}
try:
items = sorted(path.iterdir())
except PermissionError:
return {"error": "permission denied"}
for item in items:
# Skip hidden files unless requested
if not include_hidden and item.name.startswith('.'):
# Always include .dss config folder
if item.name != '.dss':
continue
# Skip common non-essential directories
if item.name in ('node_modules', '__pycache__', '.git', 'dist', 'build'):
result[item.name + "/"] = {"...": "skipped"}
continue
if item.is_dir():
result[item.name + "/"] = build_tree(item, depth + 1)
else:
result[item.name] = item.stat().st_size
return result
return build_tree(self.root, 0)
def get_root_path(self) -> str:
"""Get the absolute root path of this sandbox."""
return str(self.root)

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"""
DSS Settings and Configuration Management
Includes test utilities and reset functionality
"""
import os
import shutil
import subprocess
from pathlib import Path
from typing import Dict, List, Optional
from pydantic import ConfigDict
from pydantic_settings import BaseSettings
class DSSSettings(BaseSettings):
"""DSS Configuration Settings"""
model_config = ConfigDict(
env_file=".env",
case_sensitive=True,
extra="ignore"
)
# Project paths
PROJECT_ROOT: Path = Path(__file__).parent.parent
DSS_DIR: Path = Path(__file__).parent
TESTS_DIR: Path = PROJECT_ROOT / "tests"
CACHE_DIR: Path = Path.home() / ".dss" / "cache"
DATA_DIR: Path = Path.home() / ".dss" / "data"
# API Configuration
ANTHROPIC_API_KEY: Optional[str] = None
FIGMA_TOKEN: Optional[str] = None
FIGMA_FILE_KEY: Optional[str] = None
FIGMA_CACHE_TTL: int = 300 # 5 minutes
# Database
DATABASE_PATH: Path = Path.home() / ".dss" / "dss.db"
# Test Configuration
TEST_DATABASE_PATH: Path = Path.home() / ".dss" / "test.db"
USE_MOCK_APIS: bool = True
# Server Configuration
SERVER_HOST: str = "0.0.0.0" # Host to bind server to
SERVER_PORT: int = 3456
SERVER_ENV: str = "development" # development or production
LOG_LEVEL: str = "INFO"
# MCP Server Configuration
MCP_HOST: str = "127.0.0.1"
MCP_PORT: int = 3457
# Storybook Configuration
STORYBOOK_HOST: str = "0.0.0.0" # Host for Storybook server (uses SERVER_HOST if not set)
STORYBOOK_PORT: int = 6006 # Default Storybook port
STORYBOOK_AUTO_OPEN: bool = False # Don't auto-open browser
@property
def is_production(self) -> bool:
return self.SERVER_ENV == "production"
@property
def figma_configured(self) -> bool:
return bool(self.FIGMA_TOKEN)
class DSSManager:
"""Management utilities for DSS projects and system health."""
def __init__(self, settings: Optional[DSSSettings] = None):
self.settings = settings or DSSSettings()
self.project_root = self.settings.PROJECT_ROOT
self.dss_dir = self.settings.DSS_DIR
def run_tests(
self,
test_path: Optional[str] = None,
verbose: bool = True,
coverage: bool = False,
markers: Optional[str] = None
) -> subprocess.CompletedProcess:
"""
Run pytest test suite.
Args:
test_path: Specific test path (default: all tests)
verbose: Show verbose output
coverage: Generate coverage report
markers: Filter tests by marker (e.g., "unit", "integration")
Returns:
CompletedProcess with test results
"""
cmd = ["python3", "-m", "pytest"]
# Add test path
if test_path:
cmd.append(test_path)
else:
cmd.append("tests/")
# Add options
if verbose:
cmd.append("-v")
if coverage:
cmd.extend(["--cov=dss", "--cov-report=term-missing", "--cov-report=html"])
if markers:
cmd.extend(["-m", markers])
print(f"Running tests: {' '.join(cmd)}")
result = subprocess.run(cmd, cwd=self.project_root, capture_output=True, text=True)
print(result.stdout)
if result.stderr:
print("STDERR:", result.stderr)
return result
def run_unit_tests(self) -> subprocess.CompletedProcess:
"""Run only unit tests"""
return self.run_tests(markers="unit", verbose=True)
def run_integration_tests(self) -> subprocess.CompletedProcess:
"""Run only integration tests"""
return self.run_tests(markers="integration", verbose=True)
def run_all_tests_with_coverage(self) -> subprocess.CompletedProcess:
"""Run all tests with coverage report"""
return self.run_tests(coverage=True, verbose=True)
def reset_dss(
self,
keep_structure: bool = True,
confirm: bool = True
) -> Dict[str, any]:
"""
Reset DSS to a fresh state.
Deletes accumulated data while preserving directory structure.
Args:
keep_structure: Preserve directory structure (default: True)
confirm: Require user confirmation before reset (default: True)
Returns:
Dict with reset results (deleted, kept, errors)
"""
if confirm:
response = input(
"WARNING: This will delete all project data (themes, projects, cache).\n"
"Directory structure will be preserved.\n"
"Type 'RESET' to confirm: "
)
if response != "RESET":
return {"status": "cancelled", "message": "Reset cancelled"}
results = {
"status": "success",
"deleted": [],
"kept": [],
"errors": []
}
# Delete user-created themes
themes_dir = self.dss_dir / "themes"
if themes_dir.exists():
for theme_file in themes_dir.glob("*.py"):
if theme_file.name not in ["__init__.py", "default_themes.py"]:
try:
theme_file.unlink()
results["deleted"].append(str(theme_file))
except Exception as e:
results["errors"].append(f"Failed to delete theme: {e}")
results["kept"].append(str(themes_dir / "default_themes.py"))
# Clear cache directory
cache_dir = self.settings.CACHE_DIR
if cache_dir.exists():
try:
shutil.rmtree(cache_dir)
results["deleted"].append(str(cache_dir))
if keep_structure:
cache_dir.mkdir(parents=True, exist_ok=True)
results["kept"].append(str(cache_dir) + " (structure preserved)")
except Exception as e:
results["errors"].append(f"Failed to clear cache: {e}")
# Clear Figma cache
figma_cache = Path.home() / ".dss" / "figma_cache.json"
if figma_cache.exists():
try:
figma_cache.unlink()
results["deleted"].append(str(figma_cache))
except Exception as e:
results["errors"].append(f"Failed to clear Figma cache: {e}")
# Reset database
db_path = self.settings.DATABASE_PATH
if db_path.exists():
try:
db_path.unlink()
results["deleted"].append(str(db_path))
except Exception as e:
results["errors"].append(f"Failed to reset database: {e}")
# Clear test database
test_db_path = self.settings.TEST_DATABASE_PATH
if test_db_path.exists():
try:
test_db_path.unlink()
results["deleted"].append(str(test_db_path))
except Exception as e:
results["errors"].append(f"Failed to clear test database: {e}")
# Clear Python cache
for pycache in self.project_root.rglob("__pycache__"):
try:
shutil.rmtree(pycache)
results["deleted"].append(str(pycache))
except Exception as e:
results["errors"].append(f"Failed to clear cache: {e}")
# Preserve core directories
structure_dirs = [
self.dss_dir / "models",
self.dss_dir / "validators",
self.dss_dir / "tools",
self.dss_dir / "themes",
self.dss_dir / "api",
self.project_root / "tests" / "fixtures",
self.project_root / "tests" / "unit",
self.project_root / "tests" / "integration",
]
for dir_path in structure_dirs:
if dir_path.exists():
results["kept"].append(str(dir_path))
return results
def get_system_info(self) -> Dict[str, any]:
"""Get comprehensive system information and configuration status."""
return {
"project_root": str(self.project_root),
"dss_dir": str(self.dss_dir),
"tests_dir": str(self.settings.TESTS_DIR),
"cache_dir": str(self.settings.CACHE_DIR),
"database_path": str(self.settings.DATABASE_PATH),
"has_anthropic_key": bool(self.settings.ANTHROPIC_API_KEY),
"has_figma_token": bool(self.settings.FIGMA_TOKEN),
"use_mock_apis": self.settings.USE_MOCK_APIS
}
def check_dependencies(self) -> Dict[str, bool]:
"""
Verify all required dependencies are installed and functional.
Returns:
Dict with dependency health status (True=installed, False=missing)
"""
dependencies = {}
# Pydantic for data validation
try:
import pydantic
dependencies["pydantic"] = True
except ImportError:
dependencies["pydantic"] = False
# FastAPI for API framework
try:
import fastapi
dependencies["fastapi"] = True
except ImportError:
dependencies["fastapi"] = False
# Pytest for testing
try:
import pytest
dependencies["pytest"] = True
except ImportError:
dependencies["pytest"] = False
# Requests for HTTP operations
try:
import requests
dependencies["requests"] = True
except ImportError:
dependencies["requests"] = False
# Style Dictionary for token transformation
try:
result = subprocess.run(
["npx", "style-dictionary", "--version"],
capture_output=True,
timeout=5
)
dependencies["style-dictionary"] = result.returncode == 0
except Exception:
dependencies["style-dictionary"] = False
return dependencies
# Singleton instance
settings = DSSSettings()
manager = DSSManager(settings)
if __name__ == "__main__":
# DSS Settings Management CLI
import sys
if len(sys.argv) < 2:
print("""
DSS Settings Management
Manage DSS configuration, testing, and system health.
Usage:
python -m dss.settings <command>
Test Commands:
test [path] Run tests (optional: specific test path)
test-unit Run unit tests only
test-integration Run integration tests only
test-coverage Run all tests with coverage report
Management Commands:
reset Reset DSS to fresh state
info Display system information and status
check-deps Verify all dependencies are installed
""")
sys.exit(0)
command = sys.argv[1]
if command == "test":
test_path = sys.argv[2] if len(sys.argv) > 2 else None
manager.run_tests(test_path)
elif command == "test-unit":
manager.run_unit_tests()
elif command == "test-integration":
manager.run_integration_tests()
elif command == "test-coverage":
manager.run_all_tests_with_coverage()
elif command == "reset":
# Check for --no-confirm flag
no_confirm = "--no-confirm" in sys.argv
results = manager.reset_dss(confirm=(not no_confirm))
if results.get("status") != "cancelled":
print("\nReset complete:")
print(f" Deleted: {len(results.get('deleted', []))} items")
print(f" Preserved: {len(results.get('kept', []))} items")
if results.get('errors'):
print(f" Errors: {len(results['errors'])} items failed")
elif command == "info":
info = manager.get_system_info()
print("\nSystem Information:")
print(f" Project root: {info['project_root']}")
print(f" DSS directory: {info['dss_dir']}")
print(f" Tests directory: {info['tests_dir']}")
print(f" Cache directory: {info['cache_dir']}")
print(f" Database path: {info['database_path']}")
print(f" Anthropic API: {'Configured' if info['has_anthropic_key'] else 'Not configured'}")
print(f" Figma token: {'Configured' if info['has_figma_token'] else 'Not configured'}")
print(f" API mode: {'Mock' if info['use_mock_apis'] else 'Live'}")
elif command == "check-deps":
deps = manager.check_dependencies()
print("\nDependency Check:")
healthy = sum(1 for v in deps.values() if v)
total = len(deps)
print(f" Status: {healthy}/{total} dependencies installed")
print()
for dep, installed in deps.items():
status = "OK" if installed else "MISSING"
print(f" {status}: {dep}")
if healthy < total:
print("\n Some dependencies are missing.")
print(" Run: pip install -r requirements.txt")
else:
print(f"\nUnknown command: '{command}'")
print("Run: python -m dss.settings (without arguments for help)")
sys.exit(1)

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dss/status/__init__.py Normal file
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"""
DSS Status Module - Comprehensive system status visualization
"""
from .dashboard import StatusDashboard, HealthMetric
__all__ = ["StatusDashboard", "HealthMetric"]

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"""
DSS Status Dashboard - Comprehensive system status visualization
Provides a beautiful ASCII art dashboard that aggregates data from:
- DSSManager (system info, dependencies)
- Database stats (projects, components, styles)
- ActivityLog (recent activity)
- SyncHistory (sync operations)
- QuickWinFinder (improvement opportunities)
Expert-validated design with:
- Optimized database queries using LIMIT
- Modular render methods for maintainability
- Named constants for health score weights
- Dynamic terminal width support
"""
import shutil
from datetime import datetime, timedelta
from typing import Dict, List, Optional, Any
from dataclasses import dataclass, field
# Health score weight constants (expert recommendation)
HEALTH_WEIGHT_DEPENDENCIES = 0.40
HEALTH_WEIGHT_INTEGRATIONS = 0.25
HEALTH_WEIGHT_DATABASE = 0.20
HEALTH_WEIGHT_ACTIVITY = 0.15
@dataclass
class HealthMetric:
"""Individual health check result."""
name: str
status: str # ok, warning, error
value: str
category: str = "general"
details: Optional[str] = None
@dataclass
class StatusData:
"""Aggregated status data container."""
version: str = ""
healthy: bool = True
health_score: int = 0
mode: str = "unknown"
timestamp: str = ""
# Health metrics
health_metrics: List[HealthMetric] = field(default_factory=list)
# Design system metrics
projects_count: int = 0
projects_active: int = 0
components_count: int = 0
styles_count: int = 0
tokens_count: int = 0
adoption_percent: int = 0
# Activity
recent_activity: List[Dict] = field(default_factory=list)
recent_syncs: List[Dict] = field(default_factory=list)
total_activities: int = 0
# Quick wins
quick_wins_count: int = 0
quick_wins: List[str] = field(default_factory=list)
# Configuration
project_root: str = ""
database_path: str = ""
cache_dir: str = ""
figma_configured: bool = False
anthropic_configured: bool = False
# Recommendations
recommendations: List[str] = field(default_factory=list)
class StatusDashboard:
"""
Generates comprehensive DSS status dashboard.
Aggregates data from multiple sources and presents it as either:
- ASCII art dashboard for CLI (render_text())
- JSON structure for programmatic access (get_status())
"""
def __init__(self):
"""Initialize dashboard with lazy loading."""
self._data: Optional[StatusData] = None
self._settings = None
self._manager = None
def _ensure_initialized(self):
"""Lazy initialization of DSS components."""
if self._settings is None:
from dss.settings import DSSSettings, DSSManager
self._settings = DSSSettings()
self._manager = DSSManager(self._settings)
def get_status(self) -> Dict[str, Any]:
"""
Get full status as dictionary.
Returns:
Dict with all status information
"""
data = self._gather_data()
return {
"success": True,
"version": data.version,
"healthy": data.healthy,
"health_score": data.health_score,
"mode": data.mode,
"timestamp": data.timestamp,
"health": [
{"name": m.name, "status": m.status, "value": m.value, "category": m.category}
for m in data.health_metrics
],
"metrics": {
"projects": {"total": data.projects_count, "active": data.projects_active},
"components": data.components_count,
"styles": data.styles_count,
"tokens": data.tokens_count,
"adoption_percent": data.adoption_percent
},
"activity": {
"recent": data.recent_activity,
"total": data.total_activities,
"recent_syncs": data.recent_syncs
},
"quick_wins": {
"count": data.quick_wins_count,
"items": data.quick_wins
},
"configuration": {
"project_root": data.project_root,
"database": data.database_path,
"cache": data.cache_dir,
"figma_configured": data.figma_configured,
"anthropic_configured": data.anthropic_configured
},
"recommendations": data.recommendations
}
def _gather_data(self) -> StatusData:
"""Aggregate data from all sources."""
self._ensure_initialized()
data = StatusData()
# Version and timestamp
from dss import __version__
data.version = __version__
data.timestamp = datetime.now().isoformat()
# System info
info = self._manager.get_system_info()
data.project_root = info["project_root"]
data.database_path = info["database_path"]
data.cache_dir = info["cache_dir"]
data.figma_configured = info["has_figma_token"]
data.anthropic_configured = info["has_anthropic_key"]
data.mode = "Mock APIs" if info["use_mock_apis"] else "Live"
# Dependencies health
deps = self._manager.check_dependencies()
for dep, ok in deps.items():
data.health_metrics.append(HealthMetric(
name=dep,
status="ok" if ok else "error",
value="Installed" if ok else "Missing",
category="dependency"
))
# Integration health
data.health_metrics.append(HealthMetric(
name="Figma",
status="ok" if data.figma_configured else "warning",
value="Connected" if data.figma_configured else "No token",
category="integration"
))
data.health_metrics.append(HealthMetric(
name="Anthropic",
status="ok" if data.anthropic_configured else "warning",
value="Connected" if data.anthropic_configured else "No key",
category="integration"
))
# Database stats
try:
from storage.json_store import get_stats, ActivityLog, SyncHistory, Projects, Components
stats = get_stats()
data.projects_count = stats.get("projects", 0)
data.components_count = stats.get("components", 0)
data.styles_count = stats.get("styles", 0)
# Database size metric
db_size = stats.get("db_size_mb", 0)
data.health_metrics.append(HealthMetric(
name="Database",
status="ok" if db_size < 100 else "warning",
value=f"{db_size} MB",
category="database"
))
# Projects
projects = Projects.list()
data.projects_active = len([p for p in projects if p.get("status") == "active"])
# Recent activity (OPTIMIZED: use limit parameter, not slice)
# Expert recommendation: avoid [:5] slicing which fetches all records
activities = ActivityLog.recent(limit=5)
data.recent_activity = [
{
"action": a.get("action", ""),
"description": a.get("description", ""),
"created_at": a.get("created_at", ""),
"category": a.get("category", "")
}
for a in activities
]
data.total_activities = ActivityLog.count()
# Recent syncs (OPTIMIZED: use limit parameter)
syncs = SyncHistory.recent(limit=3)
data.recent_syncs = [
{
"sync_type": s.get("sync_type", ""),
"status": s.get("status", ""),
"items_synced": s.get("items_synced", 0),
"started_at": s.get("started_at", "")
}
for s in syncs
]
except Exception as e:
data.health_metrics.append(HealthMetric(
name="Database",
status="error",
value=f"Error: {str(e)[:30]}",
category="database"
))
# Calculate health score
data.health_score = self._calculate_health_score(data)
data.healthy = data.health_score >= 70
# Generate recommendations
data.recommendations = self._generate_recommendations(data)
return data
def _calculate_health_score(self, data: StatusData) -> int:
"""
Calculate overall health score (0-100).
Uses weighted components:
- Dependencies: 40%
- Integrations: 25%
- Database: 20%
- Activity: 15%
"""
# Dependencies score (40%)
dep_metrics = [m for m in data.health_metrics if m.category == "dependency"]
if dep_metrics:
deps_ok = sum(1 for m in dep_metrics if m.status == "ok") / len(dep_metrics)
else:
deps_ok = 0
# Integrations score (25%)
int_metrics = [m for m in data.health_metrics if m.category == "integration"]
if int_metrics:
int_ok = sum(1 for m in int_metrics if m.status == "ok") / len(int_metrics)
else:
int_ok = 0
# Database score (20%)
db_metrics = [m for m in data.health_metrics if m.category == "database"]
if db_metrics:
db_ok = sum(1 for m in db_metrics if m.status == "ok") / len(db_metrics)
else:
db_ok = 0
# Activity score (15%) - based on having recent data
activity_ok = 1.0 if data.projects_count > 0 or data.components_count > 0 else 0.5
# Weighted score using named constants
score = (
deps_ok * HEALTH_WEIGHT_DEPENDENCIES +
int_ok * HEALTH_WEIGHT_INTEGRATIONS +
db_ok * HEALTH_WEIGHT_DATABASE +
activity_ok * HEALTH_WEIGHT_ACTIVITY
) * 100
return int(score)
def _generate_recommendations(self, data: StatusData) -> List[str]:
"""Generate actionable recommendations based on current state."""
recs = []
if not data.figma_configured:
recs.append("Set FIGMA_TOKEN environment variable to enable live Figma sync")
if not data.anthropic_configured:
recs.append("Set ANTHROPIC_API_KEY for AI-powered design analysis")
if data.projects_count == 0:
recs.append("Run dss_analyze_project to scan your first codebase")
if data.tokens_count == 0:
recs.append("Extract design tokens with dss_extract_tokens")
if data.components_count == 0 and data.projects_count > 0:
recs.append("Run dss_audit_components to discover React components")
# Check for missing dependencies
for m in data.health_metrics:
if m.category == "dependency" and m.status == "error":
recs.append(f"Install missing dependency: {m.name}")
return recs[:5] # Limit to top 5 recommendations
def render_text(self) -> str:
"""
Render status as formatted ASCII art dashboard.
Uses dynamic terminal width for responsive layout.
Returns:
Formatted string with ASCII art dashboard
"""
data = self._gather_data()
# Get terminal width (expert recommendation)
term_width = shutil.get_terminal_size((80, 24)).columns
width = min(term_width - 2, 70) # Cap at 70 for readability
lines = []
lines.append(self._render_header(data, width))
lines.append("")
lines.append(self._render_health_panel(data, width))
lines.append("")
lines.append(self._render_metrics_panel(data, width))
lines.append("")
lines.append(self._render_activity_panel(data, width))
lines.append("")
lines.append(self._render_recommendations_panel(data, width))
return "\n".join(lines)
def _render_header(self, data: StatusData, width: int) -> str:
"""Render the header section."""
health_icon = "\u2705" if data.healthy else "\u26a0\ufe0f"
health_text = f"{health_icon} Healthy ({data.health_score}%)" if data.healthy else f"{health_icon} Issues ({data.health_score}%)"
lines = []
lines.append("\u2554" + "\u2550" * width + "\u2557")
lines.append("\u2551" + "\U0001f3a8 DSS Status Dashboard".center(width) + "\u2551")
lines.append("\u2560" + "\u2550" * width + "\u2563")
version_line = f" Version: {data.version:<20} Status: {health_text}"
lines.append("\u2551" + version_line.ljust(width) + "\u2551")
mode_line = f" Mode: {data.mode:<25} Time: {data.timestamp[:19]}"
lines.append("\u2551" + mode_line.ljust(width) + "\u2551")
lines.append("\u255a" + "\u2550" * width + "\u255d")
return "\n".join(lines)
def _render_health_panel(self, data: StatusData, width: int) -> str:
"""Render the health panel section."""
lines = []
lines.append("\u250c" + "\u2500" * width + "\u2510")
lines.append("\u2502" + " \U0001f3e5 SYSTEM HEALTH".ljust(width) + "\u2502")
lines.append("\u251c" + "\u2500" * width + "\u2524")
# Dependencies
deps = [m for m in data.health_metrics if m.category == "dependency"]
deps_line = " Dependencies: "
for d in deps:
icon = "\u2705" if d.status == "ok" else "\u274c"
deps_line += f"{icon} {d.name} "
lines.append("\u2502" + deps_line[:width].ljust(width) + "\u2502")
# Integrations
ints = [m for m in data.health_metrics if m.category == "integration"]
int_line = " Integrations: "
for i in ints:
icon = "\u2705" if i.status == "ok" else "\u26a0\ufe0f"
int_line += f"{icon} {i.name} ({i.value}) "
lines.append("\u2502" + int_line[:width].ljust(width) + "\u2502")
# Database
db = next((m for m in data.health_metrics if m.category == "database"), None)
if db:
db_icon = "\u2705" if db.status == "ok" else "\u26a0\ufe0f"
db_line = f" Database: {db_icon} {db.value}"
lines.append("\u2502" + db_line.ljust(width) + "\u2502")
lines.append("\u2514" + "\u2500" * width + "\u2518")
return "\n".join(lines)
def _render_metrics_panel(self, data: StatusData, width: int) -> str:
"""Render the design system metrics panel."""
lines = []
lines.append("\u250c" + "\u2500" * width + "\u2510")
lines.append("\u2502" + " \U0001f4ca DESIGN SYSTEM METRICS".ljust(width) + "\u2502")
lines.append("\u251c" + "\u2500" * width + "\u2524")
lines.append("\u2502" + f" Projects: {data.projects_count} total ({data.projects_active} active)".ljust(width) + "\u2502")
lines.append("\u2502" + f" Components: {data.components_count} tracked".ljust(width) + "\u2502")
lines.append("\u2502" + f" Styles: {data.styles_count} defined".ljust(width) + "\u2502")
# Tokens
if data.tokens_count > 0:
lines.append("\u2502" + f" Tokens: {data.tokens_count} extracted".ljust(width) + "\u2502")
else:
lines.append("\u2502" + " Tokens: -- (run dss_extract_tokens)".ljust(width) + "\u2502")
# Adoption progress bar
if data.adoption_percent > 0:
bar_width = 30
filled = int(bar_width * data.adoption_percent / 100)
bar = "\u2588" * filled + "\u2591" * (bar_width - filled)
lines.append("\u2502" + f" Adoption: [{bar}] {data.adoption_percent}%".ljust(width) + "\u2502")
lines.append("\u2514" + "\u2500" * width + "\u2518")
return "\n".join(lines)
def _render_activity_panel(self, data: StatusData, width: int) -> str:
"""Render the recent activity panel."""
lines = []
lines.append("\u250c" + "\u2500" * width + "\u2510")
lines.append("\u2502" + " \U0001f551 RECENT ACTIVITY".ljust(width) + "\u2502")
lines.append("\u251c" + "\u2500" * width + "\u2524")
if data.recent_activity:
for activity in data.recent_activity[:3]:
action = activity.get("action", "Unknown")
desc = activity.get("description", "")[:40]
created = activity.get("created_at", "")[:10]
line = f" \u2022 {created} | {action}: {desc}"
lines.append("\u2502" + line[:width].ljust(width) + "\u2502")
else:
lines.append("\u2502" + " No recent activity".ljust(width) + "\u2502")
lines.append("\u2502" + "".ljust(width) + "\u2502")
lines.append("\u2502" + f" Total activities: {data.total_activities}".ljust(width) + "\u2502")
lines.append("\u2514" + "\u2500" * width + "\u2518")
return "\n".join(lines)
def _render_recommendations_panel(self, data: StatusData, width: int) -> str:
"""Render the recommendations panel."""
if not data.recommendations:
return ""
lines = []
lines.append("\u250c" + "\u2500" * width + "\u2510")
lines.append("\u2502" + " \U0001f4a1 RECOMMENDED NEXT STEPS".ljust(width) + "\u2502")
lines.append("\u251c" + "\u2500" * width + "\u2524")
for i, rec in enumerate(data.recommendations[:4], 1):
line = f" {i}. {rec}"
# Truncate if too long
if len(line) > width - 1:
line = line[:width-4] + "..."
lines.append("\u2502" + line.ljust(width) + "\u2502")
lines.append("\u2514" + "\u2500" * width + "\u2518")
return "\n".join(lines)
# Convenience function
def get_dashboard() -> StatusDashboard:
"""Get a StatusDashboard instance."""
return StatusDashboard()
if __name__ == "__main__":
# CLI test
import sys
dashboard = StatusDashboard()
if len(sys.argv) > 1 and sys.argv[1] == "--json":
import json
print(json.dumps(dashboard.get_status(), indent=2))
else:
print(dashboard.render_text())

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"""
DSS Storybook Integration Module
Provides tools for:
- Scanning existing Storybook stories
- Generating stories from React components
- Creating themed Storybook configurations
- Syncing documentation with design tokens
- Host configuration management (uses settings host, not localhost)
"""
from .scanner import StorybookScanner, StoryInfo, StorybookConfig
from .generator import StoryGenerator, StoryTemplate
from .theme import ThemeGenerator, StorybookTheme
from .config import (
get_storybook_host,
get_storybook_port,
get_storybook_url,
create_storybook_config,
generate_storybook_start_command,
write_storybook_config_file,
get_storybook_status,
)
__all__ = [
# Scanner
"StorybookScanner",
"StoryInfo",
"StorybookConfig",
# Generator
"StoryGenerator",
"StoryTemplate",
# Theme
"ThemeGenerator",
"StorybookTheme",
# Configuration (host-aware)
"get_storybook_host",
"get_storybook_port",
"get_storybook_url",
"create_storybook_config",
"generate_storybook_start_command",
"write_storybook_config_file",
"get_storybook_status",
]

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"""
Storybook Configuration Management
Ensures Storybook uses project host settings instead of localhost.
"""
import os
import json
from pathlib import Path
from typing import Dict, Any, Optional
from dss.settings import settings
def get_storybook_host() -> str:
"""
Get the configured Storybook host.
Priority:
1. STORYBOOK_HOST environment variable
2. STORYBOOK_HOST from settings
3. SERVER_HOST from settings
4. Fall back to 0.0.0.0
"""
return os.getenv("STORYBOOK_HOST") or settings.STORYBOOK_HOST or settings.SERVER_HOST or "0.0.0.0"
def get_storybook_port() -> int:
"""
Get the configured Storybook port.
Priority:
1. STORYBOOK_PORT environment variable
2. STORYBOOK_PORT from settings
3. Fall back to 6006
"""
try:
return int(os.getenv("STORYBOOK_PORT", settings.STORYBOOK_PORT))
except (ValueError, AttributeError):
return 6006
def create_storybook_config(project_path: Path) -> Dict[str, Any]:
"""
Create Storybook configuration with correct host settings.
Args:
project_path: Path to the project directory
Returns:
Dictionary with Storybook configuration
"""
host = get_storybook_host()
port = get_storybook_port()
config = {
"stories": [
"../src/**/*.stories.@(js|jsx|ts|tsx|mdx)",
"../components/**/*.stories.@(js|jsx|ts|tsx|mdx)"
],
"addons": [
"@storybook/addon-links",
"@storybook/addon-essentials",
"@storybook/addon-interactions"
],
"framework": {
"name": "@storybook/react-vite",
"options": {}
},
"core": {
"builder": "@storybook/builder-vite"
},
"viteFinal": {
"server": {
"host": host,
"port": port,
"strictPort": False,
"open": settings.STORYBOOK_AUTO_OPEN
}
}
}
return config
def generate_storybook_start_command(project_path: Path) -> str:
"""
Generate the Storybook start command with correct host.
Args:
project_path: Path to the project directory
Returns:
Command string to start Storybook
"""
host = get_storybook_host()
port = get_storybook_port()
# Use npx to ensure we use project's Storybook version
cmd = f"npx storybook dev -p {port} -h {host}"
if not settings.STORYBOOK_AUTO_OPEN:
cmd += " --no-open"
return cmd
def get_storybook_url(project_path: Optional[Path] = None) -> str:
"""
Get the Storybook URL based on configuration.
Args:
project_path: Optional path to the project directory
Returns:
Full URL to access Storybook
"""
host = get_storybook_host()
port = get_storybook_port()
# If host is 0.0.0.0, use the actual server hostname
if host == "0.0.0.0":
# Try to get from SERVER_NAME env var or use localhost as fallback for display
display_host = os.getenv("SERVER_NAME", "localhost")
else:
display_host = host
return f"http://{display_host}:{port}"
def write_storybook_config_file(project_path: Path, config_dir: Path = None) -> Path:
"""
Write Storybook configuration to project's .storybook directory.
Args:
project_path: Path to the project directory
config_dir: Optional custom config directory (default: .storybook)
Returns:
Path to the created config file
"""
if config_dir is None:
config_dir = project_path / ".storybook"
config_dir.mkdir(parents=True, exist_ok=True)
# Create main.js with proper host configuration
main_js = config_dir / "main.js"
config = create_storybook_config(project_path)
# Convert to JS module format
js_content = f"""/** @type {{import('@storybook/react-vite').StorybookConfig}} */
const config = {json.dumps(config, indent=2)};
export default config;
"""
main_js.write_text(js_content)
# Create preview.js if it doesn't exist
preview_js = config_dir / "preview.js"
if not preview_js.exists():
preview_content = """/** @type {import('@storybook/react').Preview} */
const preview = {
parameters: {
actions: { argTypesRegex: '^on[A-Z].*' },
controls: {
matchers: {
color: /(background|color)$/i,
date: /Date$/,
},
},
},
};
export default preview;
"""
preview_js.write_text(preview_content)
return main_js
def get_storybook_status(project_path: Path) -> Dict[str, Any]:
"""
Get Storybook configuration status for a project.
Args:
project_path: Path to the project directory
Returns:
Dictionary with Storybook status information
"""
config_dir = project_path / ".storybook"
has_config = config_dir.exists() and (config_dir / "main.js").exists()
# Check if Storybook is installed
package_json = project_path / "package.json"
has_storybook = False
storybook_version = None
if package_json.exists():
try:
pkg = json.loads(package_json.read_text())
deps = {**pkg.get("dependencies", {}), **pkg.get("devDependencies", {})}
for pkg_name in ["@storybook/react", "storybook"]:
if pkg_name in deps:
has_storybook = True
storybook_version = deps[pkg_name]
break
except (json.JSONDecodeError, FileNotFoundError):
pass
return {
"configured": has_config,
"installed": has_storybook,
"version": storybook_version,
"config_dir": str(config_dir),
"url": get_storybook_url(project_path),
"host": get_storybook_host(),
"port": get_storybook_port(),
"start_command": generate_storybook_start_command(project_path)
}

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"""
Storybook Story Generator for Design System Components
Generates interactive Storybook stories for design system components,
creating comprehensive documentation that showcases component usage,
variants, and integration points.
Stories serve as the primary documentation and interactive reference
for how components should be used in applications.
"""
import re
from pathlib import Path
from typing import List, Dict, Any, Optional
from dataclasses import dataclass, field
from enum import Enum
class StoryTemplate(str, Enum):
"""
Available story format templates for component documentation.
"""
CSF3 = "csf3" # Component Story Format 3 (latest, recommended)
CSF2 = "csf2" # Component Story Format 2 (legacy)
MDX = "mdx" # MDX format (documentation + interactive)
@dataclass
class PropInfo:
"""
Component property metadata.
Captures prop name, type, required status, default value,
description, and valid options for code generation.
"""
name: str
type: str = "unknown"
required: bool = False
default_value: Optional[str] = None
description: str = ""
options: List[str] = field(default_factory=list) # For enum/union types
@dataclass
class ComponentMeta:
"""
Component metadata for story generation.
Describes component name, file path, props, description,
and whether it accepts children for story creation.
"""
name: str
path: str
props: List[PropInfo] = field(default_factory=list)
description: str = ""
has_children: bool = False
class StoryGenerator:
"""
Story generator for design system components.
Generates interactive Storybook stories in CSF3, CSF2, or MDX format,
automatically extracting component metadata and creating comprehensive
documentation with variants and default stories.
"""
def __init__(self, root_path: str):
self.root = Path(root_path).resolve()
def generate(self, template: StoryTemplate = StoryTemplate.CSF3, dry_run: bool = True) -> List[Dict[str, str]]:
"""
Generate stories for all components in the project.
This is the main entry point for story generation, scanning common
component directories and generating stories for each component found.
Args:
template: Story template format (CSF3, CSF2, or MDX)
dry_run: If True, only return what would be generated without writing files
Returns:
List of dicts with component paths and generated stories
"""
import asyncio
# Common component directories to scan
component_dirs = [
'src/components',
'components',
'src/ui',
'ui',
'lib/components',
'packages/ui/src',
'app/components',
]
results = []
for dir_path in component_dirs:
full_path = self.root / dir_path
if full_path.exists():
# Run async method synchronously
try:
loop = asyncio.get_event_loop()
except RuntimeError:
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
dir_results = loop.run_until_complete(
self.generate_stories_for_directory(dir_path, template, dry_run)
)
results.extend(dir_results)
# If no component directories found, try root
if not results:
try:
loop = asyncio.get_event_loop()
except RuntimeError:
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
results = loop.run_until_complete(
self.generate_stories_for_directory('.', template, dry_run)
)
return results
async def generate_story(
self,
component_path: str,
template: StoryTemplate = StoryTemplate.CSF3,
include_variants: bool = True,
output_path: Optional[str] = None,
) -> str:
"""
Generate a Storybook story for a component.
Args:
component_path: Path to the component file
template: Story template format
include_variants: Generate variant stories
output_path: Optional path to write the story file
Returns:
Generated story code
"""
# Parse component
meta = await self._parse_component(component_path)
# Generate story based on template
if template == StoryTemplate.CSF3:
story = self._generate_csf3(meta, include_variants)
elif template == StoryTemplate.CSF2:
story = self._generate_csf2(meta, include_variants)
else:
story = self._generate_mdx(meta, include_variants)
# Write to file if output path provided
if output_path:
output = Path(output_path)
output.parent.mkdir(parents=True, exist_ok=True)
output.write_text(story)
return story
async def _parse_component(self, component_path: str) -> ComponentMeta:
"""Parse a React component to extract metadata."""
path = self.root / component_path if not Path(component_path).is_absolute() else Path(component_path)
content = path.read_text(encoding="utf-8", errors="ignore")
component_name = path.stem
props = []
# Extract props from interface/type
# interface ButtonProps { variant?: 'primary' | 'secondary'; ... }
props_pattern = re.compile(
r'(?:interface|type)\s+\w*Props\s*(?:=\s*)?\{([^}]+)\}',
re.DOTALL
)
props_match = props_pattern.search(content)
if props_match:
props_content = props_match.group(1)
# Parse each prop line
for line in props_content.split('\n'):
line = line.strip()
if not line or line.startswith('//'):
continue
# Match: propName?: type; or propName: type;
prop_match = re.match(
r'(\w+)(\?)?:\s*([^;/]+)',
line
)
if prop_match:
prop_name = prop_match.group(1)
is_optional = prop_match.group(2) == '?'
prop_type = prop_match.group(3).strip()
# Extract options from union types
options = []
if '|' in prop_type:
# 'primary' | 'secondary' | 'ghost'
options = [
o.strip().strip("'\"")
for o in prop_type.split('|')
if o.strip().startswith(("'", '"'))
]
props.append(PropInfo(
name=prop_name,
type=prop_type,
required=not is_optional,
options=options,
))
# Check if component uses children
has_children = 'children' in content.lower() and (
'React.ReactNode' in content or
'ReactNode' in content or
'{children}' in content
)
# Extract component description from JSDoc
description = ""
jsdoc_match = re.search(r'/\*\*\s*\n\s*\*\s*([^\n*]+)', content)
if jsdoc_match:
description = jsdoc_match.group(1).strip()
return ComponentMeta(
name=component_name,
path=component_path,
props=props,
description=description,
has_children=has_children,
)
def _generate_csf3(self, meta: ComponentMeta, include_variants: bool) -> str:
"""Generate CSF3 format story."""
lines = [
f"import type {{ Meta, StoryObj }} from '@storybook/react';",
f"import {{ {meta.name} }} from './{meta.name}';",
"",
f"const meta: Meta<typeof {meta.name}> = {{",
f" title: 'Components/{meta.name}',",
f" component: {meta.name},",
" parameters: {",
" layout: 'centered',",
" },",
" tags: ['autodocs'],",
]
# Add argTypes for props with options
arg_types = []
for prop in meta.props:
if prop.options:
arg_types.append(
f" {prop.name}: {{\n"
f" options: {prop.options},\n"
f" control: {{ type: 'select' }},\n"
f" }},"
)
if arg_types:
lines.append(" argTypes: {")
lines.extend(arg_types)
lines.append(" },")
lines.extend([
"};",
"",
"export default meta;",
f"type Story = StoryObj<typeof {meta.name}>;",
"",
])
# Generate default story
default_args = self._get_default_args(meta)
lines.extend([
"export const Default: Story = {",
" args: {",
])
for key, value in default_args.items():
lines.append(f" {key}: {value},")
lines.extend([
" },",
"};",
])
# Generate variant stories
if include_variants:
variant_prop = next(
(p for p in meta.props if p.name == 'variant' and p.options),
None
)
if variant_prop:
for variant in variant_prop.options:
story_name = variant.title().replace('-', '').replace('_', '')
lines.extend([
"",
f"export const {story_name}: Story = {{",
" args: {",
f" ...Default.args,",
f" variant: '{variant}',",
" },",
"};",
])
# Size variants
size_prop = next(
(p for p in meta.props if p.name == 'size' and p.options),
None
)
if size_prop:
for size in size_prop.options:
story_name = f"Size{size.title()}"
lines.extend([
"",
f"export const {story_name}: Story = {{",
" args: {",
f" ...Default.args,",
f" size: '{size}',",
" },",
"};",
])
# Disabled state
disabled_prop = next(
(p for p in meta.props if p.name == 'disabled'),
None
)
if disabled_prop:
lines.extend([
"",
"export const Disabled: Story = {",
" args: {",
" ...Default.args,",
" disabled: true,",
" },",
"};",
])
return "\n".join(lines)
def _generate_csf2(self, meta: ComponentMeta, include_variants: bool) -> str:
"""Generate CSF2 format story."""
lines = [
f"import React from 'react';",
f"import {{ {meta.name} }} from './{meta.name}';",
"",
"export default {",
f" title: 'Components/{meta.name}',",
f" component: {meta.name},",
"};",
"",
f"const Template = (args) => <{meta.name} {{...args}} />;",
"",
"export const Default = Template.bind({});",
"Default.args = {",
]
default_args = self._get_default_args(meta)
for key, value in default_args.items():
lines.append(f" {key}: {value},")
lines.append("};")
# Generate variant stories
if include_variants:
variant_prop = next(
(p for p in meta.props if p.name == 'variant' and p.options),
None
)
if variant_prop:
for variant in variant_prop.options:
story_name = variant.title().replace('-', '').replace('_', '')
lines.extend([
"",
f"export const {story_name} = Template.bind({{}});",
f"{story_name}.args = {{",
f" ...Default.args,",
f" variant: '{variant}',",
"};",
])
return "\n".join(lines)
def _generate_mdx(self, meta: ComponentMeta, include_variants: bool) -> str:
"""Generate MDX format story."""
lines = [
f"import {{ Meta, Story, Canvas, ArgsTable }} from '@storybook/blocks';",
f"import {{ {meta.name} }} from './{meta.name}';",
"",
f"<Meta title=\"Components/{meta.name}\" component={{{meta.name}}} />",
"",
f"# {meta.name}",
"",
]
if meta.description:
lines.extend([meta.description, ""])
lines.extend([
"## Default",
"",
"<Canvas>",
f" <Story name=\"Default\">",
f" <{meta.name}",
])
default_args = self._get_default_args(meta)
for key, value in default_args.items():
lines.append(f" {key}={value}")
lines.extend([
f" />",
" </Story>",
"</Canvas>",
"",
"## Props",
"",
f"<ArgsTable of={{{meta.name}}} />",
])
return "\n".join(lines)
def _get_default_args(self, meta: ComponentMeta) -> Dict[str, str]:
"""Get default args for a component."""
args = {}
for prop in meta.props:
if prop.name == 'children' and meta.has_children:
args['children'] = f"'{meta.name}'"
elif prop.name == 'variant' and prop.options:
args['variant'] = f"'{prop.options[0]}'"
elif prop.name == 'size' and prop.options:
args['size'] = f"'{prop.options[0]}'"
elif prop.name == 'disabled':
args['disabled'] = 'false'
elif prop.name == 'onClick':
args['onClick'] = '() => console.log("clicked")'
elif prop.required and prop.default_value:
args[prop.name] = prop.default_value
# Ensure children for button-like components
if meta.has_children and 'children' not in args:
args['children'] = f"'{meta.name}'"
return args
async def generate_stories_for_directory(
self,
directory: str,
template: StoryTemplate = StoryTemplate.CSF3,
dry_run: bool = True,
) -> List[Dict[str, str]]:
"""
Generate stories for all components in a directory.
Args:
directory: Path to component directory
template: Story template format
dry_run: If True, only return what would be generated
Returns:
List of dicts with component path and generated story
"""
results = []
dir_path = self.root / directory
if not dir_path.exists():
return results
# Find component files
for pattern in ['*.tsx', '*.jsx']:
for comp_path in dir_path.glob(pattern):
# Skip story files, test files, index files
if any(x in comp_path.name.lower() for x in ['.stories.', '.test.', '.spec.', 'index.']):
continue
# Skip non-component files (not PascalCase)
if not comp_path.stem[0].isupper():
continue
try:
rel_path = str(comp_path.relative_to(self.root))
story = await self.generate_story(rel_path, template)
# Determine story output path
story_path = comp_path.with_suffix('.stories.tsx')
result = {
'component': rel_path,
'story_path': str(story_path.relative_to(self.root)),
'story': story,
}
if not dry_run:
story_path.write_text(story)
result['written'] = True
results.append(result)
except Exception as e:
results.append({
'component': str(comp_path),
'error': str(e),
})
return results

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"""
Storybook Scanner
Discovers and analyzes existing Storybook stories in a project.
"""
import re
import json
from pathlib import Path
from typing import List, Dict, Any, Optional, Set
from dataclasses import dataclass, field
@dataclass
class StoryInfo:
"""Information about a Storybook story."""
name: str # Story name (e.g., "Primary")
title: str # Story title (e.g., "Components/Button")
component: str # Component name
file_path: str # Path to story file
args: Dict[str, Any] = field(default_factory=dict) # Default args
parameters: Dict[str, Any] = field(default_factory=dict)
decorators: List[str] = field(default_factory=list)
tags: List[str] = field(default_factory=list)
def to_dict(self) -> Dict[str, Any]:
return {
"name": self.name,
"title": self.title,
"component": self.component,
"file_path": self.file_path,
"args": self.args,
"parameters": self.parameters,
"decorators": self.decorators,
"tags": self.tags,
}
@dataclass
class StorybookConfig:
"""Storybook configuration details."""
version: str = ""
framework: str = "" # react, vue, angular, etc.
builder: str = "" # vite, webpack5, etc.
addons: List[str] = field(default_factory=list)
stories_patterns: List[str] = field(default_factory=list)
static_dirs: List[str] = field(default_factory=list)
config_path: str = ""
def to_dict(self) -> Dict[str, Any]:
return {
"version": self.version,
"framework": self.framework,
"builder": self.builder,
"addons": self.addons,
"stories_patterns": self.stories_patterns,
"static_dirs": self.static_dirs,
"config_path": self.config_path,
}
class StorybookScanner:
"""
Scans a project for Storybook configuration and stories.
"""
# Common story file patterns
STORY_PATTERNS = [
'*.stories.tsx',
'*.stories.ts',
'*.stories.jsx',
'*.stories.js',
'*.stories.mdx',
]
def __init__(self, root_path: str):
self.root = Path(root_path).resolve()
async def scan(self) -> Dict[str, Any]:
"""
Perform full Storybook scan.
Returns:
Dict with configuration and story inventory
"""
config = await self._find_config()
stories = await self._find_stories()
# Group stories by component
by_component: Dict[str, List[StoryInfo]] = {}
for story in stories:
if story.component not in by_component:
by_component[story.component] = []
by_component[story.component].append(story)
return {
"config": config.to_dict() if config else None,
"stories_count": len(stories),
"components_with_stories": len(by_component),
"stories": [s.to_dict() for s in stories],
"by_component": {
comp: [s.to_dict() for s in stories_list]
for comp, stories_list in by_component.items()
},
}
async def _find_config(self) -> Optional[StorybookConfig]:
"""Find and parse Storybook configuration."""
# Look for .storybook directory
storybook_dir = self.root / ".storybook"
if not storybook_dir.exists():
# Try alternative locations
for alt in ["storybook", ".storybook"]:
alt_path = self.root / alt
if alt_path.exists():
storybook_dir = alt_path
break
else:
return None
config = StorybookConfig(config_path=str(storybook_dir))
# Parse main.js/ts
for main_file in ["main.ts", "main.js", "main.mjs"]:
main_path = storybook_dir / main_file
if main_path.exists():
await self._parse_main_config(main_path, config)
break
# Check package.json for Storybook version
pkg_json = self.root / "package.json"
if pkg_json.exists():
try:
pkg = json.loads(pkg_json.read_text())
deps = {**pkg.get("dependencies", {}), **pkg.get("devDependencies", {})}
# Get Storybook version
for pkg_name in ["@storybook/react", "@storybook/vue3", "@storybook/angular"]:
if pkg_name in deps:
config.version = deps[pkg_name].lstrip("^~")
config.framework = pkg_name.split("/")[1]
break
# Get builder
if "@storybook/builder-vite" in deps:
config.builder = "vite"
elif "@storybook/builder-webpack5" in deps:
config.builder = "webpack5"
# Get addons
config.addons = [
pkg for pkg in deps.keys()
if pkg.startswith("@storybook/addon-")
]
except (json.JSONDecodeError, KeyError):
pass
return config
async def _parse_main_config(self, main_path: Path, config: StorybookConfig) -> None:
"""Parse main.js/ts for configuration."""
try:
content = main_path.read_text(encoding="utf-8")
# Extract stories patterns
stories_match = re.search(
r'stories\s*:\s*\[([^\]]+)\]',
content,
re.DOTALL
)
if stories_match:
patterns_str = stories_match.group(1)
patterns = re.findall(r'["\']([^"\']+)["\']', patterns_str)
config.stories_patterns = patterns
# Extract static dirs
static_match = re.search(
r'staticDirs\s*:\s*\[([^\]]+)\]',
content,
re.DOTALL
)
if static_match:
dirs_str = static_match.group(1)
dirs = re.findall(r'["\']([^"\']+)["\']', dirs_str)
config.static_dirs = dirs
# Extract framework
framework_match = re.search(
r'framework\s*:\s*["\'](@storybook/[^"\']+)["\']',
content
)
if framework_match:
config.framework = framework_match.group(1)
except Exception:
pass
async def _find_stories(self) -> List[StoryInfo]:
"""Find all story files in the project."""
stories = []
skip_dirs = {'node_modules', '.git', 'dist', 'build'}
for pattern in self.STORY_PATTERNS:
for story_path in self.root.rglob(pattern):
if any(skip in story_path.parts for skip in skip_dirs):
continue
try:
file_stories = await self._parse_story_file(story_path)
stories.extend(file_stories)
except Exception:
continue
return stories
async def _parse_story_file(self, story_path: Path) -> List[StoryInfo]:
"""Parse a story file to extract story information."""
content = story_path.read_text(encoding="utf-8", errors="ignore")
rel_path = str(story_path.relative_to(self.root))
stories = []
# Extract meta/default export
title = ""
component = ""
# CSF3 format: const meta = { title: '...', component: ... }
meta_match = re.search(
r'(?:const\s+meta|export\s+default)\s*[=:]\s*\{([^}]+)\}',
content,
re.DOTALL
)
if meta_match:
meta_content = meta_match.group(1)
title_match = re.search(r'title\s*:\s*["\']([^"\']+)["\']', meta_content)
if title_match:
title = title_match.group(1)
comp_match = re.search(r'component\s*:\s*(\w+)', meta_content)
if comp_match:
component = comp_match.group(1)
# If no title, derive from file path
if not title:
# Convert path to title (e.g., src/components/Button.stories.tsx -> Components/Button)
parts = story_path.stem.replace('.stories', '').split('/')
title = '/'.join(p.title() for p in parts[-2:] if p)
if not component:
component = story_path.stem.replace('.stories', '')
# Find exported stories (CSF3 format)
# export const Primary: Story = { ... }
story_pattern = re.compile(
r'export\s+const\s+(\w+)\s*(?::\s*\w+)?\s*=\s*\{([^}]*)\}',
re.DOTALL
)
for match in story_pattern.finditer(content):
story_name = match.group(1)
story_content = match.group(2)
# Skip meta export
if story_name.lower() in ['meta', 'default']:
continue
# Parse args
args = {}
args_match = re.search(r'args\s*:\s*\{([^}]*)\}', story_content)
if args_match:
args_str = args_match.group(1)
# Simple key-value extraction
for kv_match in re.finditer(r'(\w+)\s*:\s*["\']?([^,\n"\']+)["\']?', args_str):
args[kv_match.group(1)] = kv_match.group(2).strip()
stories.append(StoryInfo(
name=story_name,
title=title,
component=component,
file_path=rel_path,
args=args,
))
# Also check for older CSF2 format
# export const Primary = Template.bind({})
csf2_pattern = re.compile(
r'export\s+const\s+(\w+)\s*=\s*Template\.bind\(\{\}\)'
)
for match in csf2_pattern.finditer(content):
story_name = match.group(1)
if not any(s.name == story_name for s in stories):
stories.append(StoryInfo(
name=story_name,
title=title,
component=component,
file_path=rel_path,
))
return stories
async def get_components_without_stories(
self,
component_files: List[str]
) -> List[str]:
"""
Find components that don't have Storybook stories.
Args:
component_files: List of component file paths
Returns:
List of component paths without stories
"""
# Get all components with stories
result = await self.scan()
components_with_stories = set(result.get("by_component", {}).keys())
# Find components without stories
without_stories = []
for comp_path in component_files:
# Extract component name from path
comp_name = Path(comp_path).stem
if comp_name not in components_with_stories:
without_stories.append(comp_path)
return without_stories
async def get_story_coverage(self) -> Dict[str, Any]:
"""
Calculate story coverage statistics.
Returns:
Coverage statistics including counts and percentages
"""
result = await self.scan()
stories_count = result.get("stories_count", 0)
components_count = result.get("components_with_stories", 0)
# Count stories per component
by_component = result.get("by_component", {})
stories_per_component = {
comp: len(stories) for comp, stories in by_component.items()
}
avg_stories = (
sum(stories_per_component.values()) / len(stories_per_component)
if stories_per_component else 0
)
return {
"total_stories": stories_count,
"components_covered": components_count,
"average_stories_per_component": round(avg_stories, 1),
"stories_per_component": stories_per_component,
}

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"""
Storybook Theme Generator
Generates Storybook theme configurations from design tokens.
"""
import json
from pathlib import Path
from typing import List, Dict, Any, Optional
from dataclasses import dataclass, field
@dataclass
class StorybookTheme:
"""Storybook theme configuration."""
name: str = "dss-theme"
base: str = "light" # 'light' or 'dark'
# Brand
brand_title: str = "Design System"
brand_url: str = ""
brand_image: str = ""
brand_target: str = "_self"
# Colors
color_primary: str = "#3B82F6"
color_secondary: str = "#10B981"
# UI Colors
app_bg: str = "#FFFFFF"
app_content_bg: str = "#FFFFFF"
app_border_color: str = "#E5E7EB"
# Text colors
text_color: str = "#1F2937"
text_inverse_color: str = "#FFFFFF"
text_muted_color: str = "#6B7280"
# Toolbar
bar_text_color: str = "#6B7280"
bar_selected_color: str = "#3B82F6"
bar_bg: str = "#FFFFFF"
# Form colors
input_bg: str = "#FFFFFF"
input_border: str = "#D1D5DB"
input_text_color: str = "#1F2937"
input_border_radius: int = 4
# Typography
font_base: str = '"Inter", -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, sans-serif'
font_code: str = '"Fira Code", "Monaco", monospace'
def to_dict(self) -> Dict[str, Any]:
return {
"base": self.base,
"brandTitle": self.brand_title,
"brandUrl": self.brand_url,
"brandImage": self.brand_image,
"brandTarget": self.brand_target,
"colorPrimary": self.color_primary,
"colorSecondary": self.color_secondary,
"appBg": self.app_bg,
"appContentBg": self.app_content_bg,
"appBorderColor": self.app_border_color,
"textColor": self.text_color,
"textInverseColor": self.text_inverse_color,
"textMutedColor": self.text_muted_color,
"barTextColor": self.bar_text_color,
"barSelectedColor": self.bar_selected_color,
"barBg": self.bar_bg,
"inputBg": self.input_bg,
"inputBorder": self.input_border,
"inputTextColor": self.input_text_color,
"inputBorderRadius": self.input_border_radius,
"fontBase": self.font_base,
"fontCode": self.font_code,
}
class ThemeGenerator:
"""
Generates Storybook theme configurations from design tokens.
"""
def __init__(self, root_path: Optional[str] = None):
"""
Initialize ThemeGenerator.
Args:
root_path: Optional project root path for finding tokens and writing output
"""
self.root = Path(root_path).resolve() if root_path else Path.cwd()
def generate(self, brand_title: str = "Design System", base: str = "light") -> Dict[str, Any]:
"""
Generate Storybook theme configuration from project tokens.
This is the main entry point for theme generation. It searches for design tokens
in the project and generates Storybook theme configuration files.
Args:
brand_title: Brand title for Storybook
base: Base theme ('light' or 'dark')
Returns:
Dict with generated theme configuration and files
"""
# Look for tokens in common locations
token_paths = [
self.root / 'tokens' / 'tokens.json',
self.root / 'design-tokens' / 'tokens.json',
self.root / 'src' / 'tokens' / 'tokens.json',
self.root / '.dss' / 'tokens.json',
self.root / 'dss_output' / 'tokens.json',
self.root / 'dss' / 'core_tokens' / 'tokens.json', # DSS core tokens
]
tokens = []
token_source = None
for token_path in token_paths:
if token_path.exists():
try:
token_data = json.loads(token_path.read_text())
if isinstance(token_data, list):
tokens = token_data
elif isinstance(token_data, dict):
# Flatten nested token structure
tokens = self._flatten_tokens(token_data)
token_source = str(token_path)
break
except (json.JSONDecodeError, IOError):
continue
# Generate theme from tokens (or use defaults if no tokens found)
theme = self.generate_from_tokens(tokens, brand_title, base)
# Determine output directory for Storybook config
storybook_dir = self.root / '.storybook'
output_dir = str(storybook_dir) if storybook_dir.exists() else None
# Generate configuration files
files = self.generate_full_config(tokens, brand_title, output_dir)
return {
"theme": theme.to_dict(),
"files_generated": list(files.keys()),
"token_source": token_source,
"tokens_found": len(tokens),
"output_directory": output_dir,
"written": output_dir is not None,
}
def _flatten_tokens(self, token_dict: Dict[str, Any], prefix: str = "") -> List[Dict[str, Any]]:
"""Flatten nested token dictionary to list of {name, value} dicts."""
tokens = []
for key, value in token_dict.items():
name = f"{prefix}.{key}" if prefix else key
if isinstance(value, dict):
if "value" in value:
# This is a token leaf
tokens.append({"name": name, "value": value["value"]})
else:
# Recurse into nested structure
tokens.extend(self._flatten_tokens(value, name))
elif isinstance(value, str):
tokens.append({"name": name, "value": value})
return tokens
# Token name mappings to Storybook theme properties
TOKEN_MAPPINGS = {
# Primary/Secondary
"color.primary.500": "color_primary",
"color.primary.600": "color_primary",
"color.secondary.500": "color_secondary",
"color.accent.500": "color_secondary",
# Backgrounds
"color.neutral.50": "app_bg",
"color.background": "app_bg",
"color.surface": "app_content_bg",
# Borders
"color.neutral.200": "app_border_color",
"color.border": "app_border_color",
# Text
"color.neutral.900": "text_color",
"color.neutral.800": "text_color",
"color.foreground": "text_color",
"color.neutral.500": "text_muted_color",
"color.muted": "text_muted_color",
# Input
"color.neutral.300": "input_border",
"radius.md": "input_border_radius",
}
def generate_from_tokens(
self,
tokens: List[Dict[str, Any]],
brand_title: str = "Design System",
base: str = "light",
) -> StorybookTheme:
"""
Generate Storybook theme from design tokens.
Args:
tokens: List of token dicts with 'name' and 'value'
brand_title: Brand title for Storybook
base: Base theme ('light' or 'dark')
Returns:
StorybookTheme configured from tokens
"""
theme = StorybookTheme(
name="dss-theme",
base=base,
brand_title=brand_title,
)
# Map tokens to theme properties
for token in tokens:
name = token.get("name", "")
value = token.get("value", "")
# Skip non-string values (complex tokens)
if not isinstance(value, str):
continue
# Check direct mappings
if name in self.TOKEN_MAPPINGS:
prop = self.TOKEN_MAPPINGS[name]
setattr(theme, prop, value)
continue
# Check partial matches
name_lower = name.lower()
if "primary" in name_lower and "500" in name_lower:
theme.color_primary = value
elif "secondary" in name_lower and "500" in name_lower:
theme.color_secondary = value
elif "background" in name_lower and self._is_light_color(value):
theme.app_bg = value
elif "foreground" in name_lower or ("text" in name_lower and "color" in name_lower):
theme.text_color = value
# Adjust for dark mode
if base == "dark":
theme = self._adjust_for_dark_mode(theme)
return theme
def _is_light_color(self, value: Any) -> bool:
"""Check if a color value is light (for background suitability)."""
# Handle non-string values (dicts, etc.)
if not isinstance(value, str):
return True # Assume light if not a string
if not value.startswith("#"):
return True # Assume light if not hex
# Parse hex color
hex_color = value.lstrip("#")
if len(hex_color) == 3:
hex_color = "".join(c * 2 for c in hex_color)
try:
r = int(hex_color[0:2], 16)
g = int(hex_color[2:4], 16)
b = int(hex_color[4:6], 16)
# Calculate luminance
luminance = (0.299 * r + 0.587 * g + 0.114 * b) / 255
return luminance > 0.5
except (ValueError, IndexError):
return True
def _adjust_for_dark_mode(self, theme: StorybookTheme) -> StorybookTheme:
"""Adjust theme for dark mode if colors aren't already dark."""
# Swap light/dark if needed
if self._is_light_color(theme.app_bg):
theme.app_bg = "#1F2937"
theme.app_content_bg = "#111827"
theme.app_border_color = "#374151"
theme.text_color = "#F9FAFB"
theme.text_muted_color = "#9CA3AF"
theme.bar_bg = "#1F2937"
theme.bar_text_color = "#9CA3AF"
theme.input_bg = "#374151"
theme.input_border = "#4B5563"
theme.input_text_color = "#F9FAFB"
return theme
def generate_theme_file(
self,
theme: StorybookTheme,
format: str = "ts",
) -> str:
"""
Generate Storybook theme file content.
Args:
theme: StorybookTheme to export
format: Output format ('ts', 'js', 'json')
Returns:
Theme file content as string
"""
if format == "json":
return json.dumps(theme.to_dict(), indent=2)
theme_dict = theme.to_dict()
if format == "ts":
lines = [
"import { create } from '@storybook/theming/create';",
"",
"export const dssTheme = create({",
]
else: # js
lines = [
"const { create } = require('@storybook/theming/create');",
"",
"module.exports = create({",
]
for key, value in theme_dict.items():
if isinstance(value, str):
lines.append(f" {key}: '{value}',")
else:
lines.append(f" {key}: {value},")
lines.extend([
"});",
"",
])
return "\n".join(lines)
def generate_manager_file(self, theme_import: str = "./dss-theme") -> str:
"""
Generate Storybook manager.ts file.
Args:
theme_import: Import path for theme
Returns:
Manager file content
"""
return f"""import {{ addons }} from '@storybook/manager-api';
import {{ dssTheme }} from '{theme_import}';
addons.setConfig({{
theme: dssTheme,
}});
"""
def generate_preview_file(
self,
tokens: List[Dict[str, Any]],
include_css_vars: bool = True,
) -> str:
"""
Generate Storybook preview.ts file with token CSS variables.
Args:
tokens: List of token dicts
include_css_vars: Include CSS variable injection
Returns:
Preview file content
"""
lines = [
"import type { Preview } from '@storybook/react';",
"",
]
if include_css_vars:
# Generate CSS variables from tokens
css_vars = []
for token in tokens:
name = token.get("name", "").replace(".", "-")
value = token.get("value", "")
css_vars.append(f" --{name}: {value};")
lines.extend([
"// Inject design tokens as CSS variables",
"const tokenStyles = `",
":root {",
])
lines.extend(css_vars)
lines.extend([
"}",
"`;",
"",
"// Add styles to document",
"const styleSheet = document.createElement('style');",
"styleSheet.textContent = tokenStyles;",
"document.head.appendChild(styleSheet);",
"",
])
lines.extend([
"const preview: Preview = {",
" parameters: {",
" controls: {",
" matchers: {",
" color: /(background|color)$/i,",
" date: /Date$/i,",
" },",
" },",
" backgrounds: {",
" default: 'light',",
" values: [",
" { name: 'light', value: '#FFFFFF' },",
" { name: 'dark', value: '#1F2937' },",
" ],",
" },",
" },",
"};",
"",
"export default preview;",
])
return "\n".join(lines)
def generate_full_config(
self,
tokens: List[Dict[str, Any]],
brand_title: str = "Design System",
output_dir: Optional[str] = None,
) -> Dict[str, str]:
"""
Generate complete Storybook configuration files.
Args:
tokens: List of token dicts
brand_title: Brand title
output_dir: Optional directory to write files
Returns:
Dict mapping filenames to content
"""
# Generate theme
theme = self.generate_from_tokens(tokens, brand_title)
files = {
"dss-theme.ts": self.generate_theme_file(theme, "ts"),
"manager.ts": self.generate_manager_file(),
"preview.ts": self.generate_preview_file(tokens),
}
# Write files if output_dir provided
if output_dir:
out_path = Path(output_dir)
out_path.mkdir(parents=True, exist_ok=True)
for filename, content in files.items():
(out_path / filename).write_text(content)
return files

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"""Default DSS themes (light & dark)"""
from .default_themes import get_default_light_theme, get_default_dark_theme
__all__ = ["get_default_light_theme", "get_default_dark_theme"]

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"""
Default DSS Light & Dark Themes
Perfect implementation showcasing the design system
"""
from dss.models.theme import Theme, DesignToken, TokenCategory
def get_default_light_theme() -> Theme:
"""
DSS Default Light Theme
Clean, modern light theme optimized for readability
"""
return Theme(
name="DSS Light",
version="1.0.0",
tokens={
# Colors
"background": DesignToken(
name="background",
value="oklch(0.99 0.005 285)",
type="color",
category=TokenCategory.COLOR,
description="Main background color"
),
"foreground": DesignToken(
name="foreground",
value="oklch(0.15 0.015 285)",
type="color",
category=TokenCategory.COLOR,
description="Main text color"
),
"primary": DesignToken(
name="primary",
value="oklch(0.65 0.18 250)",
type="color",
category=TokenCategory.COLOR,
description="Primary brand color - vibrant blue"
),
"secondary": DesignToken(
name="secondary",
value="oklch(0.55 0.05 285)",
type="color",
category=TokenCategory.COLOR,
description="Secondary color - subtle purple-gray"
),
"accent": DesignToken(
name="accent",
value="oklch(0.70 0.15 180)",
type="color",
category=TokenCategory.COLOR,
description="Accent color - cyan"
),
"destructive": DesignToken(
name="destructive",
value="oklch(0.55 0.22 25)",
type="color",
category=TokenCategory.COLOR,
description="Destructive actions - red"
),
"success": DesignToken(
name="success",
value="oklch(0.60 0.18 145)",
type="color",
category=TokenCategory.COLOR,
description="Success states - green"
),
"warning": DesignToken(
name="warning",
value="oklch(0.75 0.15 85)",
type="color",
category=TokenCategory.COLOR,
description="Warning states - yellow"
),
"muted": DesignToken(
name="muted",
value="oklch(0.95 0.01 285)",
type="color",
category=TokenCategory.COLOR,
description="Muted background"
),
"border": DesignToken(
name="border",
value="oklch(0.90 0.01 285)",
type="color",
category=TokenCategory.COLOR,
description="Border color"
),
# Spacing
"space-xs": DesignToken(
name="space-xs",
value="4px",
type="dimension",
category=TokenCategory.SPACING,
description="Extra small spacing"
),
"space-sm": DesignToken(
name="space-sm",
value="8px",
type="dimension",
category=TokenCategory.SPACING,
description="Small spacing"
),
"space-md": DesignToken(
name="space-md",
value="16px",
type="dimension",
category=TokenCategory.SPACING,
description="Medium spacing"
),
"space-lg": DesignToken(
name="space-lg",
value="24px",
type="dimension",
category=TokenCategory.SPACING,
description="Large spacing"
),
"space-xl": DesignToken(
name="space-xl",
value="32px",
type="dimension",
category=TokenCategory.SPACING,
description="Extra large spacing"
),
# Border Radius
"radius-sm": DesignToken(
name="radius-sm",
value="4px",
type="dimension",
category=TokenCategory.RADIUS,
description="Small border radius"
),
"radius-md": DesignToken(
name="radius-md",
value="8px",
type="dimension",
category=TokenCategory.RADIUS,
description="Medium border radius"
),
"radius-lg": DesignToken(
name="radius-lg",
value="12px",
type="dimension",
category=TokenCategory.RADIUS,
description="Large border radius"
),
# Typography
"text-xs": DesignToken(
name="text-xs",
value="0.75rem",
type="dimension",
category=TokenCategory.TYPOGRAPHY,
description="Extra small text"
),
"text-sm": DesignToken(
name="text-sm",
value="0.875rem",
type="dimension",
category=TokenCategory.TYPOGRAPHY,
description="Small text"
),
"text-base": DesignToken(
name="text-base",
value="1rem",
type="dimension",
category=TokenCategory.TYPOGRAPHY,
description="Base text size"
),
"text-lg": DesignToken(
name="text-lg",
value="1.125rem",
type="dimension",
category=TokenCategory.TYPOGRAPHY,
description="Large text"
),
"text-xl": DesignToken(
name="text-xl",
value="1.25rem",
type="dimension",
category=TokenCategory.TYPOGRAPHY,
description="Extra large text"
),
}
)
def get_default_dark_theme() -> Theme:
"""
DSS Default Dark Theme
Sleek dark theme optimized for low-light environments
"""
return Theme(
name="DSS Dark",
version="1.0.0",
tokens={
# Colors - Inverted for dark mode
"background": DesignToken(
name="background",
value="oklch(0.15 0.015 285)",
type="color",
category=TokenCategory.COLOR,
description="Main background color"
),
"foreground": DesignToken(
name="foreground",
value="oklch(0.95 0.01 285)",
type="color",
category=TokenCategory.COLOR,
description="Main text color"
),
"primary": DesignToken(
name="primary",
value="oklch(0.70 0.20 250)",
type="color",
category=TokenCategory.COLOR,
description="Primary brand color - brighter blue for dark mode"
),
"secondary": DesignToken(
name="secondary",
value="oklch(0.60 0.08 285)",
type="color",
category=TokenCategory.COLOR,
description="Secondary color - subtle purple-gray"
),
"accent": DesignToken(
name="accent",
value="oklch(0.75 0.18 180)",
type="color",
category=TokenCategory.COLOR,
description="Accent color - brighter cyan"
),
"destructive": DesignToken(
name="destructive",
value="oklch(0.60 0.24 25)",
type="color",
category=TokenCategory.COLOR,
description="Destructive actions - brighter red"
),
"success": DesignToken(
name="success",
value="oklch(0.65 0.20 145)",
type="color",
category=TokenCategory.COLOR,
description="Success states - brighter green"
),
"warning": DesignToken(
name="warning",
value="oklch(0.80 0.17 85)",
type="color",
category=TokenCategory.COLOR,
description="Warning states - brighter yellow"
),
"muted": DesignToken(
name="muted",
value="oklch(0.22 0.02 285)",
type="color",
category=TokenCategory.COLOR,
description="Muted background"
),
"border": DesignToken(
name="border",
value="oklch(0.30 0.02 285)",
type="color",
category=TokenCategory.COLOR,
description="Border color"
),
# Spacing - Same as light theme
"space-xs": DesignToken(
name="space-xs",
value="4px",
type="dimension",
category=TokenCategory.SPACING,
description="Extra small spacing"
),
"space-sm": DesignToken(
name="space-sm",
value="8px",
type="dimension",
category=TokenCategory.SPACING,
description="Small spacing"
),
"space-md": DesignToken(
name="space-md",
value="16px",
type="dimension",
category=TokenCategory.SPACING,
description="Medium spacing"
),
"space-lg": DesignToken(
name="space-lg",
value="24px",
type="dimension",
category=TokenCategory.SPACING,
description="Large spacing"
),
"space-xl": DesignToken(
name="space-xl",
value="32px",
type="dimension",
category=TokenCategory.SPACING,
description="Extra large spacing"
),
# Border Radius - Same as light theme
"radius-sm": DesignToken(
name="radius-sm",
value="4px",
type="dimension",
category=TokenCategory.RADIUS,
description="Small border radius"
),
"radius-md": DesignToken(
name="radius-md",
value="8px",
type="dimension",
category=TokenCategory.RADIUS,
description="Medium border radius"
),
"radius-lg": DesignToken(
name="radius-lg",
value="12px",
type="dimension",
category=TokenCategory.RADIUS,
description="Large border radius"
),
# Typography - Same as light theme
"text-xs": DesignToken(
name="text-xs",
value="0.75rem",
type="dimension",
category=TokenCategory.TYPOGRAPHY,
description="Extra small text"
),
"text-sm": DesignToken(
name="text-sm",
value="0.875rem",
type="dimension",
category=TokenCategory.TYPOGRAPHY,
description="Small text"
),
"text-base": DesignToken(
name="text-base",
value="1rem",
type="dimension",
category=TokenCategory.TYPOGRAPHY,
description="Base text size"
),
"text-lg": DesignToken(
name="text-lg",
value="1.125rem",
type="dimension",
category=TokenCategory.TYPOGRAPHY,
description="Large text"
),
"text-xl": DesignToken(
name="text-xl",
value="1.25rem",
type="dimension",
category=TokenCategory.TYPOGRAPHY,
description="Extra large text"
),
}
)

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"""
DSS Translation Dictionary Module
Provides translation between external design token formats and DSS canonical structure.
"""
from .canonical import (
DSS_CANONICAL_COMPONENTS,
DSS_CANONICAL_TOKENS,
DSS_COMPONENT_VARIANTS,
DSS_TOKEN_ALIASES,
get_canonical_token_categories,
is_valid_dss_token,
resolve_alias,
)
from .loader import TranslationDictionaryLoader
from .merger import ThemeMerger
from .models import (
ComponentMapping,
CustomProp,
MappingType,
PatternMapping,
ResolvedTheme,
ResolvedToken,
TokenMapping,
TranslationDictionary,
TranslationMappings,
TranslationRegistry,
TranslationSource,
)
from .resolver import TokenResolver
from .validator import TranslationValidator, ValidationError, ValidationResult
from .writer import TranslationDictionaryWriter
__all__ = [
# Models
"TranslationSource",
"MappingType",
"TokenMapping",
"ComponentMapping",
"PatternMapping",
"CustomProp",
"TranslationMappings",
"TranslationDictionary",
"TranslationRegistry",
"ResolvedToken",
"ResolvedTheme",
# Loader
"TranslationDictionaryLoader",
# Resolver
"TokenResolver",
# Merger
"ThemeMerger",
# Validator
"TranslationValidator",
"ValidationResult",
"ValidationError",
# Writer
"TranslationDictionaryWriter",
# Canonical Definitions
"DSS_CANONICAL_TOKENS",
"DSS_CANONICAL_COMPONENTS",
"DSS_TOKEN_ALIASES",
"DSS_COMPONENT_VARIANTS",
"is_valid_dss_token",
"resolve_alias",
"get_canonical_token_categories",
]

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"""
DSS Canonical Structure Definitions
Defines the immutable DSS canonical token and component structure.
These definitions are used for validation and auto-completion.
"""
from typing import Dict, List, Set
# DSS Canonical Token Paths
# These are the core tokens that DSS defines
DSS_CANONICAL_TOKENS: Set[str] = {
# Colors - Primary
"color.primary.50",
"color.primary.100",
"color.primary.200",
"color.primary.300",
"color.primary.400",
"color.primary.500",
"color.primary.600",
"color.primary.700",
"color.primary.800",
"color.primary.900",
# Colors - Secondary
"color.secondary.50",
"color.secondary.100",
"color.secondary.200",
"color.secondary.300",
"color.secondary.400",
"color.secondary.500",
"color.secondary.600",
"color.secondary.700",
"color.secondary.800",
"color.secondary.900",
# Colors - Neutral
"color.neutral.50",
"color.neutral.100",
"color.neutral.200",
"color.neutral.300",
"color.neutral.400",
"color.neutral.500",
"color.neutral.600",
"color.neutral.700",
"color.neutral.800",
"color.neutral.900",
# Colors - Semantic
"color.success.500",
"color.warning.500",
"color.danger.500",
"color.info.500",
"color.accent.500",
# Colors - Surface
"color.background",
"color.foreground",
"color.muted",
"color.border",
"color.ring",
# Spacing
"spacing.xs",
"spacing.sm",
"spacing.md",
"spacing.lg",
"spacing.xl",
"spacing.2xl",
"spacing.base",
# Typography - Size
"typography.size.xs",
"typography.size.sm",
"typography.size.base",
"typography.size.lg",
"typography.size.xl",
"typography.size.2xl",
"typography.size.3xl",
"typography.size.4xl",
# Typography - Weight
"typography.weight.light",
"typography.weight.normal",
"typography.weight.medium",
"typography.weight.semibold",
"typography.weight.bold",
# Typography - Line Height
"typography.lineHeight.tight",
"typography.lineHeight.normal",
"typography.lineHeight.relaxed",
# Typography - Font Family
"typography.family.sans",
"typography.family.serif",
"typography.family.mono",
# Border Radius
"border.radius.none",
"border.radius.sm",
"border.radius.md",
"border.radius.lg",
"border.radius.xl",
"border.radius.full",
# Border Width
"border.width.none",
"border.width.thin",
"border.width.default",
"border.width.thick",
# Shadows
"shadow.none",
"shadow.sm",
"shadow.md",
"shadow.lg",
"shadow.xl",
"shadow.inner",
# Motion - Duration
"motion.duration.instant",
"motion.duration.fast",
"motion.duration.normal",
"motion.duration.slow",
# Motion - Easing
"motion.easing.linear",
"motion.easing.ease",
"motion.easing.easeIn",
"motion.easing.easeOut",
"motion.easing.easeInOut",
# Z-Index
"zIndex.base",
"zIndex.dropdown",
"zIndex.sticky",
"zIndex.fixed",
"zIndex.modal",
"zIndex.popover",
"zIndex.tooltip",
# Opacity
"opacity.0",
"opacity.25",
"opacity.50",
"opacity.75",
"opacity.100",
# Breakpoints
"breakpoint.sm",
"breakpoint.md",
"breakpoint.lg",
"breakpoint.xl",
"breakpoint.2xl",
}
# Commonly used aliases for DSS tokens
DSS_TOKEN_ALIASES: Dict[str, str] = {
# Color aliases
"color.primary": "color.primary.500",
"color.secondary": "color.secondary.500",
"color.success": "color.success.500",
"color.warning": "color.warning.500",
"color.danger": "color.danger.500",
"color.destructive": "color.danger.500",
"color.error": "color.danger.500",
# Spacing aliases
"space.xs": "spacing.xs",
"space.sm": "spacing.sm",
"space.md": "spacing.md",
"space.lg": "spacing.lg",
"space.xl": "spacing.xl",
# Radius aliases
"radius.sm": "border.radius.sm",
"radius.md": "border.radius.md",
"radius.lg": "border.radius.lg",
# Typography aliases
"font.size.base": "typography.size.base",
"font.weight.bold": "typography.weight.bold",
"lineHeight.normal": "typography.lineHeight.normal",
}
# DSS Canonical Components
DSS_CANONICAL_COMPONENTS: Set[str] = {
# Primitives
"Button",
"Input",
"Textarea",
"Select",
"Checkbox",
"Radio",
"RadioGroup",
"Switch",
"Slider",
"Toggle",
# Layout
"Box",
"Flex",
"Grid",
"Container",
"Stack",
"Spacer",
"Divider",
# Data Display
"Card",
"Avatar",
"Badge",
"Chip",
"Tag",
"Icon",
"Image",
"Table",
"List",
"ListItem",
# Feedback
"Alert",
"Toast",
"Progress",
"Spinner",
"Skeleton",
"Tooltip",
# Overlay
"Modal",
"Dialog",
"Drawer",
"Popover",
"Dropdown",
"DropdownMenu",
"ContextMenu",
# Navigation
"Tabs",
"TabList",
"Tab",
"TabPanel",
"Breadcrumb",
"Pagination",
"Menu",
"MenuItem",
"NavLink",
"Link",
# Typography
"Text",
"Heading",
"Label",
"Code",
# Forms
"Form",
"FormControl",
"FormLabel",
"FormHelperText",
"FormErrorMessage",
}
# DSS Component Variants
DSS_COMPONENT_VARIANTS: Dict[str, List[str]] = {
"Button": ["variant", "size", "colorScheme", "isDisabled", "isLoading"],
"Input": ["variant", "size", "isDisabled", "isInvalid", "isReadOnly"],
"Card": ["variant", "size", "shadow"],
"Badge": ["variant", "colorScheme", "size"],
"Alert": ["status", "variant"],
"Modal": ["size", "isCentered", "scrollBehavior"],
}
# Valid variant values
DSS_VARIANT_VALUES: Dict[str, Dict[str, List[str]]] = {
"Button": {
"variant": ["solid", "outline", "ghost", "link", "unstyled"],
"size": ["xs", "sm", "md", "lg"],
"colorScheme": ["primary", "secondary", "success", "warning", "danger"],
},
"Input": {
"variant": ["outline", "filled", "flushed", "unstyled"],
"size": ["xs", "sm", "md", "lg"],
},
"Card": {
"variant": ["elevated", "outline", "filled", "unstyled"],
"size": ["sm", "md", "lg"],
},
}
def get_canonical_token_categories() -> Dict[str, List[str]]:
"""Get tokens organized by category."""
categories: Dict[str, List[str]] = {}
for token in DSS_CANONICAL_TOKENS:
parts = token.split(".")
category = parts[0]
if category not in categories:
categories[category] = []
categories[category].append(token)
return categories
def is_valid_dss_token(path: str) -> bool:
"""Check if token path is in canonical structure or valid custom namespace."""
if path in DSS_CANONICAL_TOKENS:
return True
# Check aliases
if path in DSS_TOKEN_ALIASES:
return True
# Check custom namespace
parts = path.split(".")
if len(parts) >= 3 and parts[1] in ("brand", "custom"):
return True
return False
def resolve_alias(path: str) -> str:
"""Resolve token alias to canonical path."""
return DSS_TOKEN_ALIASES.get(path, path)

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"""
Translation Dictionary Loader
Loads and parses translation dictionaries from project .dss directory.
"""
import json
from pathlib import Path
from typing import Dict, List, Optional, Union
from .models import TranslationDictionary, TranslationRegistry, TranslationSource
from .validator import TranslationValidator
class TranslationDictionaryLoader:
"""
Loads translation dictionaries from project .dss/translations/ directory.
Usage:
loader = TranslationDictionaryLoader("/path/to/project")
registry = await loader.load_all()
# Or load specific dictionary
figma_dict = await loader.load_dictionary("figma")
"""
DEFAULT_DIR = ".dss/translations"
def __init__(
self, project_path: Union[str, Path], translations_dir: Optional[str] = None, validate: bool = True
):
"""
Initialize loader.
Args:
project_path: Root path to project
translations_dir: Custom translations directory (default: .dss/translations)
validate: Whether to validate dictionaries on load
"""
self.project_path = Path(project_path).resolve()
translations_subdir = translations_dir or self.DEFAULT_DIR
self.translations_dir = self._validate_safe_path(self.project_path / translations_subdir)
self.validate = validate
self.validator = TranslationValidator() if validate else None
def _validate_safe_path(self, path: Path) -> Path:
"""
Validate that path is within project directory (prevent path traversal).
Args:
path: Path to validate
Returns:
Validated path
Raises:
ValueError: If path is outside project directory
"""
resolved = path.resolve()
try:
resolved.relative_to(self.project_path)
return resolved
except ValueError:
raise ValueError(f"Path {path} is outside project directory {self.project_path}")
async def load_all(self) -> TranslationRegistry:
"""
Load all translation dictionaries from project.
Returns:
TranslationRegistry with all loaded dictionaries
"""
registry = TranslationRegistry()
if not self.translations_dir.exists():
return registry
for json_file in self.translations_dir.glob("*.json"):
try:
dictionary = await self.load_dictionary_file(json_file)
if dictionary:
registry.dictionaries[dictionary.source.value] = dictionary
self._merge_to_registry(registry, dictionary)
except Exception as e:
# Log error but continue loading other dictionaries
registry.conflicts.append(
{"file": str(json_file), "error": str(e), "type": "load_error"}
)
return registry
async def load_dictionary(
self, source: Union[str, TranslationSource]
) -> Optional[TranslationDictionary]:
"""
Load a specific translation dictionary by source type.
Args:
source: Source type (e.g., "figma", "css", TranslationSource.FIGMA)
Returns:
TranslationDictionary or None if not found
"""
if isinstance(source, str):
source = TranslationSource(source)
file_path = self.translations_dir / f"{source.value}.json"
if not file_path.exists():
return None
return await self.load_dictionary_file(file_path)
async def load_dictionary_file(
self, file_path: Union[str, Path]
) -> Optional[TranslationDictionary]:
"""
Load a translation dictionary from a specific file.
Args:
file_path: Path to JSON file
Returns:
TranslationDictionary or None if invalid
"""
file_path = Path(file_path)
if not file_path.exists():
raise FileNotFoundError(f"Dictionary file not found: {file_path}")
with open(file_path, "r", encoding="utf-8") as f:
data = json.load(f)
# Validate if enabled
if self.validator:
validation_result = self.validator.validate_dictionary(data)
if not validation_result.is_valid:
raise ValueError(
f"Invalid dictionary {file_path}: "
f"{[str(e) for e in validation_result.errors]}"
)
return TranslationDictionary(**data)
def _merge_to_registry(self, registry: TranslationRegistry, dictionary: TranslationDictionary) -> None:
"""Merge dictionary mappings into registry."""
# Merge token mappings
for source_token, dss_token in dictionary.mappings.tokens.items():
if source_token in registry.combined_token_map:
existing = registry.combined_token_map[source_token]
if existing != dss_token:
registry.conflicts.append(
{
"type": "token_conflict",
"source_token": source_token,
"existing_mapping": existing,
"new_mapping": dss_token,
"source": dictionary.source.value,
}
)
continue
registry.combined_token_map[source_token] = dss_token
# Merge component mappings
for source_comp, dss_comp in dictionary.mappings.components.items():
if source_comp in registry.combined_component_map:
existing = registry.combined_component_map[source_comp]
if existing != dss_comp:
registry.conflicts.append(
{
"type": "component_conflict",
"source_component": source_comp,
"existing_mapping": existing,
"new_mapping": dss_comp,
"source": dictionary.source.value,
}
)
continue
registry.combined_component_map[source_comp] = dss_comp
# Merge custom props
for prop_name, prop_value in dictionary.custom_props.items():
if prop_name in registry.all_custom_props:
existing = registry.all_custom_props[prop_name]
if existing != prop_value:
registry.conflicts.append(
{
"type": "custom_prop_conflict",
"prop_name": prop_name,
"existing_value": existing,
"new_value": prop_value,
"source": dictionary.source.value,
}
)
continue
registry.all_custom_props[prop_name] = prop_value
def get_translations_dir(self) -> Path:
"""Get the translations directory path."""
return self.translations_dir
def has_translations(self) -> bool:
"""Check if project has any translation dictionaries."""
if not self.translations_dir.exists():
return False
return any(self.translations_dir.glob("*.json"))
def list_available_dictionaries(self) -> List[str]:
"""List available dictionary source types."""
if not self.translations_dir.exists():
return []
return [f.stem for f in self.translations_dir.glob("*.json")]

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"""
Theme Merger
Merges base DSS theme with translation mappings and custom props.
"""
from datetime import datetime, timezone
from typing import Any, Dict, Optional, Union
from dss.models.theme import DesignToken, Theme, TokenCategory
from dss.themes.default_themes import get_default_dark_theme, get_default_light_theme
from .models import ResolvedTheme, ResolvedToken, TranslationRegistry
from .resolver import TokenResolver
class ThemeMerger:
"""
Merges base DSS theme with project-specific customizations.
The merge hierarchy:
1. Base Theme (DSS Light or Dark)
2. Translation Mappings (external tokens -> DSS)
3. Custom Props (project-specific extensions)
Usage:
merger = ThemeMerger(registry)
resolved = await merger.merge(base_theme="light")
"""
def __init__(self, registry: TranslationRegistry):
"""
Initialize merger with translation registry.
Args:
registry: TranslationRegistry with loaded dictionaries
"""
self.registry = registry
self.resolver = TokenResolver(registry)
async def merge(
self, base_theme: str = "light", project_name: Optional[str] = None
) -> ResolvedTheme:
"""
Merge base theme with translations and custom props.
Args:
base_theme: Base theme name ("light" or "dark")
project_name: Project name for resolved theme
Returns:
ResolvedTheme with all tokens resolved
"""
# Get base theme
if base_theme == "light":
theme = get_default_light_theme()
elif base_theme == "dark":
theme = get_default_dark_theme()
else:
raise ValueError(f"Unknown base theme: {base_theme}")
# Convert theme tokens to dict for resolution
base_tokens = self._theme_to_dict(theme)
# Resolve all mapped tokens
resolved_tokens = self.resolver.resolve_all_mappings(base_tokens)
# Separate core tokens from custom props
core_tokens = {}
custom_props = {}
for dss_path, resolved in resolved_tokens.items():
if resolved.is_custom:
custom_props[dss_path] = resolved
else:
core_tokens[dss_path] = resolved
# Add base theme tokens that aren't in mappings
for token_name, token in theme.tokens.items():
# Normalize token name to DSS path
dss_path = self._normalize_to_dss_path(token_name)
if dss_path not in core_tokens:
core_tokens[dss_path] = ResolvedToken(
dss_path=dss_path,
value=token.value,
is_custom=False,
provenance=[f"base_theme: {base_theme}"],
)
return ResolvedTheme(
name=project_name or f"resolved-{base_theme}",
version="1.0.0",
base_theme=base_theme,
tokens=core_tokens,
custom_props=custom_props,
translations_applied=[dict_name for dict_name in self.registry.dictionaries.keys()],
resolved_at=datetime.now(timezone.utc),
)
def _theme_to_dict(self, theme: Theme) -> Dict[str, Any]:
"""Convert Theme object to nested dict for resolution."""
result = {}
for token_name, token in theme.tokens.items():
# Convert flat token names to nested structure
parts = self._normalize_to_dss_path(token_name).split(".")
current = result
for part in parts[:-1]:
if part not in current:
current[part] = {}
elif not isinstance(current[part], dict):
# Skip if this path is already set to a value
continue
current = current[part]
current[parts[-1]] = token.value
return result
def _normalize_to_dss_path(self, token_name: str) -> str:
"""Normalize token name to DSS canonical path."""
# Handle various formats
normalized = token_name.replace("-", ".").replace("_", ".")
# Map common prefixes
prefix_map = {
"space.": "spacing.",
"radius.": "border.radius.",
"text.": "typography.size.",
}
for old, new in prefix_map.items():
if normalized.startswith(old):
normalized = new + normalized[len(old) :]
break
return normalized
async def merge_custom_props(
self, resolved_theme: ResolvedTheme, additional_props: Dict[str, Any]
) -> ResolvedTheme:
"""
Add additional custom props to a resolved theme.
Args:
resolved_theme: Existing resolved theme
additional_props: Additional custom props to merge
Returns:
Updated ResolvedTheme
"""
for prop_name, prop_value in additional_props.items():
resolved_theme.custom_props[prop_name] = ResolvedToken(
dss_path=prop_name,
value=prop_value,
is_custom=True,
provenance=["additional_custom_prop"],
)
resolved_theme.resolved_at = datetime.now(timezone.utc)
return resolved_theme
def export_as_theme(self, resolved: ResolvedTheme) -> Theme:
"""
Convert ResolvedTheme back to Theme model.
Args:
resolved: ResolvedTheme to convert
Returns:
Theme model instance
"""
tokens = {}
# Add core tokens
for dss_path, resolved_token in resolved.tokens.items():
token_name = dss_path.replace(".", "-")
tokens[token_name] = DesignToken(
name=token_name,
value=resolved_token.value,
type=self._infer_type(dss_path, resolved_token.value),
category=self._infer_category(dss_path),
source=f"resolved:{resolved.base_theme}",
)
# Add custom props
for dss_path, resolved_token in resolved.custom_props.items():
token_name = dss_path.replace(".", "-")
tokens[token_name] = DesignToken(
name=token_name,
value=resolved_token.value,
type=self._infer_type(dss_path, resolved_token.value),
category=TokenCategory.OTHER,
source="custom_prop",
)
return Theme(name=resolved.name, version=resolved.version, tokens=tokens)
def _infer_type(self, path: str, value: Any) -> str:
"""Infer token type from path and value."""
if "color" in path:
return "color"
if "spacing" in path or "size" in path or "radius" in path:
return "dimension"
if "font" in path:
return "typography"
if "shadow" in path:
return "shadow"
return "string"
def _infer_category(self, path: str) -> TokenCategory:
"""Infer token category from DSS path."""
if path.startswith("color"):
return TokenCategory.COLOR
if path.startswith("spacing"):
return TokenCategory.SPACING
if path.startswith("typography") or path.startswith("font"):
return TokenCategory.TYPOGRAPHY
if path.startswith("border") or path.startswith("radius"):
return TokenCategory.RADIUS
if path.startswith("shadow"):
return TokenCategory.SHADOW
return TokenCategory.OTHER

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"""
Translation Dictionary Data Models
Pydantic models for translation dictionary system.
"""
from datetime import datetime, timezone
from enum import Enum
from typing import Any, Dict, List, Optional
from uuid import uuid4
from pydantic import BaseModel, Field, ConfigDict, field_validator
class TranslationSource(str, Enum):
"""Source types for translation dictionaries."""
FIGMA = "figma"
CSS = "css"
SCSS = "scss"
HEROUI = "heroui"
SHADCN = "shadcn"
TAILWIND = "tailwind"
JSON = "json"
CUSTOM = "custom"
class MappingType(str, Enum):
"""Types of mappings in a translation dictionary."""
TOKEN = "token"
COMPONENT = "component"
PATTERN = "pattern"
class TokenMapping(BaseModel):
"""Single token mapping from source to DSS canonical."""
model_config = ConfigDict(extra="forbid")
source_token: str = Field(
..., description="Source token name (e.g., '--brand-blue', '$primary-color')"
)
dss_token: str = Field(
..., description="DSS canonical token path (e.g., 'color.primary.500')"
)
source_value: Optional[str] = Field(None, description="Original value from source (for reference)")
notes: Optional[str] = Field(None, description="Human-readable notes about this mapping")
confidence: float = Field(
default=1.0, ge=0.0, le=1.0, description="Confidence score for auto-generated mappings"
)
auto_generated: bool = Field(default=False, description="Whether this mapping was auto-generated")
class ComponentMapping(BaseModel):
"""Single component mapping from source to DSS canonical."""
model_config = ConfigDict(extra="forbid")
source_component: str = Field(
..., description="Source component (e.g., '.btn-primary', 'HeroButton')"
)
dss_component: str = Field(
..., description="DSS canonical component (e.g., 'Button[variant=primary]')"
)
prop_mappings: Dict[str, str] = Field(default_factory=dict, description="Prop name mappings (source -> DSS)")
notes: Optional[str] = Field(None)
class PatternMapping(BaseModel):
"""Pattern mapping for structural translations."""
model_config = ConfigDict(extra="forbid")
source_pattern: str = Field(..., description="Source pattern (e.g., 'form-row', 'card-grid')")
dss_pattern: str = Field(..., description="DSS canonical pattern")
notes: Optional[str] = Field(None)
class CustomProp(BaseModel):
"""Custom property not in DSS core."""
model_config = ConfigDict(extra="forbid")
name: str = Field(..., description="Token name in DSS namespace (e.g., 'color.brand.acme.primary')")
value: Any = Field(..., description="Token value")
type: str = Field(default="string", description="Value type (color, dimension, string, etc.)")
description: Optional[str] = Field(None)
deprecated: bool = Field(default=False)
deprecated_message: Optional[str] = Field(None)
class TranslationMappings(BaseModel):
"""Container for all mapping types."""
model_config = ConfigDict(extra="forbid")
tokens: Dict[str, str] = Field(
default_factory=dict, description="Token mappings: source_token -> dss_token"
)
components: Dict[str, str] = Field(
default_factory=dict, description="Component mappings: source_component -> dss_component"
)
patterns: Dict[str, str] = Field(default_factory=dict, description="Pattern mappings: source_pattern -> dss_pattern")
class TranslationDictionary(BaseModel):
"""Complete translation dictionary for a project."""
model_config = ConfigDict(extra="forbid")
# Metadata
schema_version: str = Field(
default="dss-translation-v1", alias="$schema", description="Schema version identifier"
)
uuid: str = Field(default_factory=lambda: str(uuid4()), description="Unique identifier for this dictionary")
project: str = Field(..., description="Project identifier")
source: TranslationSource = Field(..., description="Source type for this dictionary")
version: str = Field(default="1.0.0", description="Dictionary version")
created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
updated_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
# Mappings
mappings: TranslationMappings = Field(
default_factory=TranslationMappings, description="All mappings from source to DSS"
)
# Custom extensions
custom_props: Dict[str, Any] = Field(default_factory=dict, description="Custom props not in DSS core (namespaced)")
# Tracking
unmapped: List[str] = Field(default_factory=list, description="Source tokens that couldn't be mapped")
notes: List[str] = Field(default_factory=list, description="Human-readable notes")
@field_validator("custom_props")
@classmethod
def validate_custom_props_namespace(cls, v: Dict[str, Any]) -> Dict[str, Any]:
"""Ensure custom props use proper namespacing."""
for key in v.keys():
# Custom props should be namespaced (e.g., color.brand.acme.primary)
if "." not in key:
raise ValueError(
f"Custom prop '{key}' must use dot-notation namespace "
"(e.g., 'color.brand.project.name')"
)
return v
class TranslationRegistry(BaseModel):
"""In-memory registry of all loaded translation dictionaries."""
model_config = ConfigDict(arbitrary_types_allowed=True)
dictionaries: Dict[str, TranslationDictionary] = Field(
default_factory=dict, description="Loaded dictionaries by source type"
)
combined_token_map: Dict[str, str] = Field(default_factory=dict, description="Combined source->DSS token mappings")
combined_component_map: Dict[str, str] = Field(
default_factory=dict, description="Combined source->DSS component mappings"
)
all_custom_props: Dict[str, Any] = Field(default_factory=dict, description="Merged custom props from all dictionaries")
conflicts: List[Dict[str, Any]] = Field(default_factory=list, description="Detected mapping conflicts")
class ResolvedToken(BaseModel):
"""A fully resolved token with provenance."""
model_config = ConfigDict(extra="forbid")
dss_path: str = Field(..., description="DSS canonical path (e.g., 'color.primary.500')")
value: Any = Field(..., description="Resolved value")
source_token: Optional[str] = Field(None, description="Original source token if translated")
source_type: Optional[TranslationSource] = Field(None, description="Source type if translated")
is_custom: bool = Field(default=False, description="Whether this is a custom prop")
provenance: List[str] = Field(default_factory=list, description="Resolution chain for debugging")
class ResolvedTheme(BaseModel):
"""Fully resolved theme with all translations applied."""
model_config = ConfigDict(arbitrary_types_allowed=True)
name: str
version: str = "1.0.0"
base_theme: str = Field(..., description="Base theme name (light/dark)")
tokens: Dict[str, ResolvedToken] = Field(default_factory=dict)
custom_props: Dict[str, ResolvedToken] = Field(default_factory=dict)
translations_applied: List[str] = Field(default_factory=list, description="List of translation dictionaries applied")
resolved_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))

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"""
Token Resolver
Resolves tokens between source formats and DSS canonical structure.
Supports bidirectional translation.
"""
from typing import Any, Dict, List, Optional, Union
from .canonical import DSS_CANONICAL_TOKENS
from .models import ResolvedToken, TranslationRegistry, TranslationSource
class TokenResolver:
"""
Resolves tokens between source and DSS canonical formats.
Supports:
- Source -> DSS translation (forward)
- DSS -> Source translation (reverse)
- Token path resolution with aliasing
- Reference chain resolution
Usage:
resolver = TokenResolver(registry)
# Forward translation
dss_token = resolver.resolve_to_dss("--brand-blue")
# -> "color.primary.500"
# Reverse translation
source_token = resolver.resolve_to_source("color.primary.500", "css")
# -> "--brand-blue"
"""
def __init__(self, registry: TranslationRegistry):
"""
Initialize resolver with translation registry.
Args:
registry: Loaded TranslationRegistry with mappings
"""
self.registry = registry
self._reverse_map: Dict[str, Dict[str, str]] = {}
self._build_reverse_maps()
def _build_reverse_maps(self) -> None:
"""Build reverse lookup maps (DSS -> source) for each source type."""
for source_type, dictionary in self.registry.dictionaries.items():
self._reverse_map[source_type] = {
dss: source for source, dss in dictionary.mappings.tokens.items()
}
def resolve_to_dss(
self, source_token: str, source_type: Optional[Union[str, TranslationSource]] = None
) -> Optional[str]:
"""
Resolve source token to DSS canonical path.
Args:
source_token: Source token (e.g., "--brand-blue", "$primary")
source_type: Optional source type hint (searches all if not provided)
Returns:
DSS canonical path or None if not found
"""
# Direct lookup in combined map
if source_token in self.registry.combined_token_map:
return self.registry.combined_token_map[source_token]
# If source type specified, look only there
if source_type:
if isinstance(source_type, str):
source_type = TranslationSource(source_type)
dictionary = self.registry.dictionaries.get(source_type.value)
if dictionary:
return dictionary.mappings.tokens.get(source_token)
# Try normalization patterns
normalized = self._normalize_token_name(source_token)
return self.registry.combined_token_map.get(normalized)
def resolve_to_source(self, dss_token: str, source_type: Union[str, TranslationSource]) -> Optional[str]:
"""
Resolve DSS token to source format (reverse translation).
Args:
dss_token: DSS canonical path (e.g., "color.primary.500")
source_type: Target source type
Returns:
Source token name or None if not mapped
"""
if isinstance(source_type, str):
source_type_str = source_type
else:
source_type_str = source_type.value
reverse_map = self._reverse_map.get(source_type_str, {})
return reverse_map.get(dss_token)
def resolve_token_value(
self,
source_token: str,
base_theme_tokens: Dict[str, Any],
source_type: Optional[Union[str, TranslationSource]] = None,
) -> Optional[ResolvedToken]:
"""
Fully resolve a source token to its DSS value.
Args:
source_token: Source token name
base_theme_tokens: Base theme token values
source_type: Optional source type hint
Returns:
ResolvedToken with full provenance or None
"""
# Get DSS path
dss_path = self.resolve_to_dss(source_token, source_type)
if not dss_path:
# Check if it's a custom prop
if source_token in self.registry.all_custom_props:
return ResolvedToken(
dss_path=source_token,
value=self.registry.all_custom_props[source_token],
source_token=source_token,
is_custom=True,
provenance=[f"custom_prop: {source_token}"],
)
return None
# Resolve value from base theme
value = self._get_token_value(dss_path, base_theme_tokens)
# Determine source type if not provided
resolved_source = source_type
if resolved_source is None:
for src_type, dictionary in self.registry.dictionaries.items():
if source_token in dictionary.mappings.tokens:
resolved_source = TranslationSource(src_type)
break
return ResolvedToken(
dss_path=dss_path,
value=value,
source_token=source_token,
source_type=resolved_source
if isinstance(resolved_source, TranslationSource)
else (TranslationSource(resolved_source) if resolved_source else None),
is_custom=False,
provenance=[
f"source: {source_token}",
f"mapped_to: {dss_path}",
f"value: {value}",
],
)
def resolve_all_mappings(self, base_theme_tokens: Dict[str, Any]) -> Dict[str, ResolvedToken]:
"""
Resolve all mapped tokens to their DSS values.
Args:
base_theme_tokens: Base theme token values
Returns:
Dict of DSS path -> ResolvedToken
"""
resolved = {}
# Resolve all mapped tokens
for source_token, dss_path in self.registry.combined_token_map.items():
value = self._get_token_value(dss_path, base_theme_tokens)
# Find source type
source_type = None
for src_type, dictionary in self.registry.dictionaries.items():
if source_token in dictionary.mappings.tokens:
source_type = TranslationSource(src_type)
break
resolved[dss_path] = ResolvedToken(
dss_path=dss_path,
value=value,
source_token=source_token,
source_type=source_type,
is_custom=False,
provenance=[f"source: {source_token}", f"mapped_to: {dss_path}"],
)
# Add custom props
for prop_name, prop_value in self.registry.all_custom_props.items():
resolved[prop_name] = ResolvedToken(
dss_path=prop_name,
value=prop_value,
is_custom=True,
provenance=[f"custom_prop: {prop_name}"],
)
return resolved
def _get_token_value(self, dss_path: str, base_tokens: Dict[str, Any]) -> Any:
"""Get token value from base theme using DSS path."""
# Handle nested paths (e.g., "color.primary.500")
parts = dss_path.split(".")
current = base_tokens
for part in parts:
if isinstance(current, dict):
current = current.get(part)
if current is None:
break
else:
return None
# If we got a DesignToken object, extract value
if hasattr(current, "value"):
return current.value
return current
def _normalize_token_name(self, token: str) -> str:
"""Normalize token name for lookup."""
# Remove common prefixes
normalized = token.lstrip("-$")
# Convert various formats to dot notation
normalized = normalized.replace("-", ".").replace("_", ".")
# Handle var() references
if normalized.startswith("var(") and normalized.endswith(")"):
normalized = normalized[4:-1].lstrip("-")
return normalized.lower()
def get_unmapped_tokens(self) -> List[str]:
"""Get list of tokens that couldn't be mapped."""
unmapped = []
for dictionary in self.registry.dictionaries.values():
unmapped.extend(dictionary.unmapped)
return list(set(unmapped))
def validate_dss_path(self, path: str) -> bool:
"""Validate that a path matches DSS canonical structure."""
return path in DSS_CANONICAL_TOKENS or self._is_valid_custom_namespace(path)
def _is_valid_custom_namespace(self, path: str) -> bool:
"""Check if path uses valid custom namespace."""
parts = path.split(".")
if len(parts) < 3:
return False
# Custom props should be like: color.brand.acme.primary
return parts[1] in ("brand", "custom")

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"""
Translation Dictionary Validator
Validates translation dictionary schema and semantic correctness.
"""
import json
import re
from pathlib import Path
from typing import Any, Dict, List, Optional
from pydantic import ValidationError as PydanticValidationError
from .canonical import DSS_CANONICAL_COMPONENTS, DSS_CANONICAL_TOKENS
from .models import TranslationDictionary, TranslationSource
class ValidationError:
"""Single validation error."""
def __init__(self, message: str, path: Optional[str] = None, severity: str = "error"):
self.message = message
self.path = path
self.severity = severity # error, warning, info
def __str__(self) -> str:
if self.path:
return f"[{self.severity}] {self.path}: {self.message}"
return f"[{self.severity}] {self.message}"
class ValidationResult:
"""Validation result container."""
def __init__(self):
self.is_valid = True
self.errors: List[ValidationError] = []
self.warnings: List[ValidationError] = []
self.info: List[ValidationError] = []
def add_error(self, message: str, path: Optional[str] = None) -> None:
self.errors.append(ValidationError(message, path, "error"))
self.is_valid = False
def add_warning(self, message: str, path: Optional[str] = None) -> None:
self.warnings.append(ValidationError(message, path, "warning"))
def add_info(self, message: str, path: Optional[str] = None) -> None:
self.info.append(ValidationError(message, path, "info"))
class TranslationValidator:
"""
Validates translation dictionaries.
Validation stages:
1. Schema validation - JSON structure matches Pydantic model
2. Token path validation - DSS paths are canonical
3. Component validation - Component mappings are valid
4. Custom prop validation - Namespacing is correct
5. Consistency validation - No conflicts or duplicates
"""
# Valid DSS path pattern - allows lowercase letters, numbers, and dots
DSS_PATH_PATTERN = re.compile(r"^[a-z][a-z0-9]*(\.[a-z0-9]+)*$")
def __init__(self, strict: bool = False, allow_unknown_tokens: bool = True):
"""
Initialize validator.
Args:
strict: If True, unknown DSS tokens are errors (not warnings)
allow_unknown_tokens: If False, all tokens must exist in canonical
"""
self.strict = strict
self.allow_unknown_tokens = allow_unknown_tokens
def validate_dictionary(self, data: Dict[str, Any]) -> ValidationResult:
"""
Validate a translation dictionary.
Args:
data: Dictionary data to validate
Returns:
ValidationResult with all errors/warnings
"""
result = ValidationResult()
# Stage 1: Schema validation
self._validate_schema(data, result)
if not result.is_valid:
return result
# Stage 2: Token path validation
self._validate_token_paths(data, result)
# Stage 3: Component validation
self._validate_components(data, result)
# Stage 4: Custom prop validation
self._validate_custom_props(data, result)
# Stage 5: Consistency validation
self._validate_consistency(data, result)
return result
def _validate_schema(self, data: Dict[str, Any], result: ValidationResult) -> None:
"""Stage 1: Validate JSON structure."""
try:
TranslationDictionary(**data)
except PydanticValidationError as e:
for error in e.errors():
path = ".".join(str(loc) for loc in error["loc"])
result.add_error(error["msg"], path)
except Exception as e:
result.add_error(f"Schema validation failed: {str(e)}")
def _validate_token_paths(self, data: Dict[str, Any], result: ValidationResult) -> None:
"""Stage 2: Validate DSS token paths."""
mappings = data.get("mappings", {})
tokens = mappings.get("tokens", {})
for source_token, dss_path in tokens.items():
# Validate path format
if not self.DSS_PATH_PATTERN.match(dss_path):
result.add_error(
f"Invalid DSS path format: '{dss_path}' "
"(must be dot-notation like 'color.primary.500')",
f"mappings.tokens.{source_token}",
)
continue
# Validate against canonical structure
if dss_path not in DSS_CANONICAL_TOKENS:
if self._is_custom_namespace(dss_path):
# Custom namespaces are allowed
result.add_info(
f"Custom namespace token: {dss_path}",
f"mappings.tokens.{source_token}",
)
elif self.allow_unknown_tokens:
result.add_warning(
f"DSS token not in canonical structure: {dss_path}",
f"mappings.tokens.{source_token}",
)
else:
result.add_error(
f"Unknown DSS token: {dss_path}",
f"mappings.tokens.{source_token}",
)
def _validate_components(self, data: Dict[str, Any], result: ValidationResult) -> None:
"""Stage 3: Validate component mappings."""
mappings = data.get("mappings", {})
components = mappings.get("components", {})
for source_comp, dss_comp in components.items():
# Extract base component name (before any variant specifiers)
base_comp = dss_comp.split("[")[0]
if base_comp not in DSS_CANONICAL_COMPONENTS:
result.add_warning(
f"Component not in DSS canonical set: {base_comp}",
f"mappings.components.{source_comp}",
)
# Validate variant syntax if present
if "[" in dss_comp:
if not self._validate_variant_syntax(dss_comp):
result.add_error(
f"Invalid variant syntax: {dss_comp}",
f"mappings.components.{source_comp}",
)
def _validate_custom_props(self, data: Dict[str, Any], result: ValidationResult) -> None:
"""Stage 4: Validate custom prop namespacing."""
custom_props = data.get("custom_props", {})
for prop_name, prop_value in custom_props.items():
# Must use dot notation
if "." not in prop_name:
result.add_error(
f"Custom prop must use dot-notation namespace: {prop_name}",
f"custom_props.{prop_name}",
)
continue
# Should use brand/custom namespace
parts = prop_name.split(".")
if len(parts) >= 2 and parts[1] not in ("brand", "custom"):
result.add_warning(
f"Custom prop should use 'brand' or 'custom' namespace: {prop_name}. "
f"Recommended: {parts[0]}.brand.{'.'.join(parts[1:])}",
f"custom_props.{prop_name}",
)
def _validate_consistency(self, data: Dict[str, Any], result: ValidationResult) -> None:
"""Stage 5: Validate internal consistency."""
mappings = data.get("mappings", {})
tokens = mappings.get("tokens", {})
custom_props = data.get("custom_props", {})
# Check for duplicate DSS targets
dss_targets = list(tokens.values())
seen = set()
for target in dss_targets:
if target in seen:
result.add_warning(
f"Multiple source tokens map to same DSS token: {target}",
"mappings.tokens",
)
seen.add(target)
# Check custom props don't conflict with mappings
for prop_name in custom_props.keys():
if prop_name in tokens.values():
result.add_error(
f"Custom prop conflicts with mapping target: {prop_name}",
f"custom_props.{prop_name}",
)
def _is_custom_namespace(self, path: str) -> bool:
"""Check if path uses custom namespace."""
parts = path.split(".")
if len(parts) >= 2:
return parts[1] in ("brand", "custom")
return False
def _validate_variant_syntax(self, comp: str) -> bool:
"""Validate component variant syntax like Button[variant=primary]."""
if "[" not in comp:
return True
# Check for matching brackets
if comp.count("[") != comp.count("]"):
return False
# Extract variant part
variant_match = re.search(r"\[([^\]]+)\]", comp)
if not variant_match:
return False
# Validate key=value format
variant_str = variant_match.group(1)
for pair in variant_str.split(","):
if "=" not in pair:
return False
key, value = pair.split("=", 1)
if not key.strip() or not value.strip():
return False
return True
def validate_file(self, file_path: str) -> ValidationResult:
"""
Validate a translation dictionary file.
Args:
file_path: Path to JSON file
Returns:
ValidationResult
"""
result = ValidationResult()
try:
with open(file_path, "r", encoding="utf-8") as f:
data = json.load(f)
except json.JSONDecodeError as e:
result.add_error(f"Invalid JSON: {str(e)}")
return result
except FileNotFoundError:
result.add_error(f"File not found: {file_path}")
return result
return self.validate_dictionary(data)

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"""
Translation Dictionary Writer
Writes and updates translation dictionary files.
"""
import json
from datetime import datetime, timezone
from pathlib import Path
from typing import Any, Dict, List, Optional, Union
from .models import TranslationDictionary, TranslationMappings, TranslationSource
class TranslationDictionaryWriter:
"""
Writes translation dictionaries to project .dss/translations/ directory.
Usage:
writer = TranslationDictionaryWriter("/path/to/project")
# Create new dictionary
await writer.create(
source=TranslationSource.CSS,
project="my-project",
token_mappings={"--brand-blue": "color.primary.500"}
)
# Add mapping to existing dictionary
await writer.add_mapping(
source=TranslationSource.CSS,
source_token="--brand-green",
dss_token="color.success.500"
)
"""
DEFAULT_DIR = ".dss/translations"
def __init__(
self,
project_path: Union[str, Path],
translations_dir: Optional[str] = None,
):
"""
Initialize writer.
Args:
project_path: Root path to project
translations_dir: Custom translations directory
"""
self.project_path = Path(project_path).resolve()
translations_subdir = translations_dir or self.DEFAULT_DIR
self.translations_dir = self._validate_safe_path(self.project_path / translations_subdir)
def _validate_safe_path(self, path: Path) -> Path:
"""
Validate that path is within project directory (prevent path traversal).
Args:
path: Path to validate
Returns:
Validated path
Raises:
ValueError: If path is outside project directory
"""
resolved = path.resolve()
try:
resolved.relative_to(self.project_path)
return resolved
except ValueError:
raise ValueError(f"Path {path} is outside project directory {self.project_path}")
async def create(
self,
source: Union[str, TranslationSource],
project: str,
token_mappings: Optional[Dict[str, str]] = None,
component_mappings: Optional[Dict[str, str]] = None,
custom_props: Optional[Dict[str, Any]] = None,
notes: Optional[List[str]] = None,
) -> TranslationDictionary:
"""
Create a new translation dictionary.
Args:
source: Source type
project: Project identifier
token_mappings: Initial token mappings
component_mappings: Initial component mappings
custom_props: Initial custom props
notes: Optional notes
Returns:
Created TranslationDictionary
"""
if isinstance(source, str):
source = TranslationSource(source)
# Ensure directory exists
self.translations_dir.mkdir(parents=True, exist_ok=True)
# Create dictionary
dictionary = TranslationDictionary(
project=project,
source=source,
mappings=TranslationMappings(
tokens=token_mappings or {},
components=component_mappings or {},
),
custom_props=custom_props or {},
notes=notes or [],
)
# Write to file
file_path = self.translations_dir / f"{source.value}.json"
await self._write_file(file_path, dictionary)
return dictionary
async def update(
self,
source: Union[str, TranslationSource],
token_mappings: Optional[Dict[str, str]] = None,
component_mappings: Optional[Dict[str, str]] = None,
custom_props: Optional[Dict[str, Any]] = None,
notes: Optional[List[str]] = None,
) -> TranslationDictionary:
"""
Update an existing translation dictionary.
Args:
source: Source type
token_mappings: Token mappings to add/update
component_mappings: Component mappings to add/update
custom_props: Custom props to add/update
notes: Notes to append
Returns:
Updated TranslationDictionary
"""
if isinstance(source, str):
source = TranslationSource(source)
file_path = self.translations_dir / f"{source.value}.json"
if not file_path.exists():
raise FileNotFoundError(f"Dictionary not found: {file_path}. Use create() first.")
# Load existing
with open(file_path, "r", encoding="utf-8") as f:
data = json.load(f)
dictionary = TranslationDictionary(**data)
# Update mappings
if token_mappings:
dictionary.mappings.tokens.update(token_mappings)
if component_mappings:
dictionary.mappings.components.update(component_mappings)
if custom_props:
dictionary.custom_props.update(custom_props)
if notes:
dictionary.notes.extend(notes)
dictionary.updated_at = datetime.now(timezone.utc)
# Write back
await self._write_file(file_path, dictionary)
return dictionary
async def add_mapping(
self, source: Union[str, TranslationSource], source_token: str, dss_token: str
) -> None:
"""
Add a single token mapping to a dictionary.
Args:
source: Source type
source_token: Source token name
dss_token: DSS canonical path
"""
await self.update(source=source, token_mappings={source_token: dss_token})
async def add_custom_prop(
self, source: Union[str, TranslationSource], prop_name: str, prop_value: Any
) -> None:
"""
Add a custom prop to a dictionary.
Args:
source: Source type
prop_name: Property name (must use DSS namespace)
prop_value: Property value
"""
# Validate namespace
if "." not in prop_name:
raise ValueError(f"Custom prop must use dot-notation namespace: {prop_name}")
await self.update(source=source, custom_props={prop_name: prop_value})
async def remove_mapping(self, source: Union[str, TranslationSource], source_token: str) -> None:
"""
Remove a token mapping from a dictionary.
Args:
source: Source type
source_token: Source token to remove
"""
if isinstance(source, str):
source = TranslationSource(source)
file_path = self.translations_dir / f"{source.value}.json"
if not file_path.exists():
return
with open(file_path, "r", encoding="utf-8") as f:
data = json.load(f)
dictionary = TranslationDictionary(**data)
if source_token in dictionary.mappings.tokens:
del dictionary.mappings.tokens[source_token]
dictionary.updated_at = datetime.now(timezone.utc)
await self._write_file(file_path, dictionary)
async def mark_unmapped(
self, source: Union[str, TranslationSource], unmapped_tokens: List[str]
) -> None:
"""
Add tokens to unmapped list.
Args:
source: Source type
unmapped_tokens: List of tokens that couldn't be mapped
"""
if isinstance(source, str):
source = TranslationSource(source)
file_path = self.translations_dir / f"{source.value}.json"
if not file_path.exists():
return
with open(file_path, "r", encoding="utf-8") as f:
data = json.load(f)
dictionary = TranslationDictionary(**data)
# Add unique unmapped tokens
existing = set(dictionary.unmapped)
for token in unmapped_tokens:
if token not in existing:
dictionary.unmapped.append(token)
dictionary.updated_at = datetime.now(timezone.utc)
await self._write_file(file_path, dictionary)
async def _write_file(self, file_path: Path, dictionary: TranslationDictionary) -> None:
"""Write dictionary to JSON file."""
data = dictionary.model_dump(by_alias=True, mode="json")
# Convert datetime to ISO format
data["created_at"] = dictionary.created_at.isoformat()
data["updated_at"] = dictionary.updated_at.isoformat()
with open(file_path, "w", encoding="utf-8") as f:
json.dump(data, f, indent=2, ensure_ascii=False)
def delete(self, source: Union[str, TranslationSource]) -> bool:
"""
Delete a translation dictionary file.
Args:
source: Source type
Returns:
True if deleted, False if not found
"""
if isinstance(source, str):
source = TranslationSource(source)
file_path = self.translations_dir / f"{source.value}.json"
if file_path.exists():
file_path.unlink()
return True
return False

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"""Validation logic for projects, components, and themes"""
from .schema import ProjectValidator, ValidationResult, ValidationError, ValidationStage
__all__ = ["ProjectValidator", "ValidationResult", "ValidationError", "ValidationStage"]

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"""
================================================================================
IMMUTABLE FILE - DO NOT MODIFY
================================================================================
This file is protected by git pre-commit hooks.
Reason: Core validation pipeline - ensures design system data integrity
Last Modified: 2025-12-09
To update: Use 'DSS_IMMUTABLE_BYPASS=1 git commit -m "[IMMUTABLE-UPDATE] reason"'
================================================================================
Project Validation Pipeline
A comprehensive 4-stage validation system ensuring design system data integrity.
This validator checks JSON structure, required fields, token references, and
component dependencies before processing.
Stages:
1. Schema validation - JSON structure validation using Pydantic models
2. Structure validation - Required fields and organizational structure
3. Token validation - Token value types, categories, and inter-token references
4. Component validation - Component properties, variants, and dependencies
"""
from enum import Enum
from typing import Any, Dict, List, Optional
from pydantic import BaseModel, Field, ConfigDict, ValidationError as PydanticValidationError
from dss.models.project import Project
from dss.models.theme import Theme, DesignToken, TokenCategory
from dss.models.component import Component
class ValidationStage(str, Enum):
"""Validation pipeline stages"""
SCHEMA = "schema"
STRUCTURE = "structure"
TOKEN_VALIDATION = "token_validation"
COMPONENT_VALIDATION = "component_validation"
COMPLETE = "complete"
class ValidationError(BaseModel):
"""Single validation error from the pipeline."""
model_config = ConfigDict(arbitrary_types_allowed=True)
stage: ValidationStage = Field(..., description="Validation stage where error occurred")
message: str = Field(..., description="Error description")
field: Optional[str] = Field(None, description="Field path where error occurred")
def __str__(self) -> str:
if self.field:
return f"[{self.stage.value}] {self.field}: {self.message}"
return f"[{self.stage.value}] {self.message}"
class ValidationResult(BaseModel):
"""Complete result from validation pipeline."""
model_config = ConfigDict(arbitrary_types_allowed=True)
is_valid: bool = Field(..., description="Whether validation passed without errors")
stage: ValidationStage = Field(..., description="Which validation stage completed")
errors: List[ValidationError] = Field(default_factory=list, description="All validation errors detected")
def add_error(self, stage: ValidationStage, message: str, field: Optional[str] = None):
"""Add validation error"""
self.errors.append(ValidationError(stage=stage, message=message, field=field))
self.is_valid = False
class ProjectValidator:
"""
4-stage validation pipeline for DSS projects
Stage 1: Schema validation (JSON structure)
Stage 2: Structure validation (required fields)
Stage 3: Token validation (types, references)
Stage 4: Component validation (props, variants, dependencies)
"""
def validate(self, data: Dict[str, Any]) -> ValidationResult:
"""
Run full immune system validation pipeline
The DSS immune system antibodies check the data through 4 stages,
detecting pathogens (invalid data) before they infect the organism.
Args:
data: Raw project data (incoming nutrition/nutrients)
Returns:
ValidationResult with health status and any detected infections
"""
result = ValidationResult(is_valid=True, stage=ValidationStage.SCHEMA, errors=[])
# Stage 1: Schema validation
if not self._validate_schema(data, result):
return result
result.stage = ValidationStage.STRUCTURE
# Stage 2: Structure validation
if not self._validate_structure(data, result):
return result
result.stage = ValidationStage.TOKEN_VALIDATION
# Stage 3: Token validation
if not self._validate_tokens(data, result):
return result
result.stage = ValidationStage.COMPONENT_VALIDATION
# Stage 4: Component validation
if not self._validate_components(data, result):
return result
result.stage = ValidationStage.COMPLETE
return result
def _validate_schema(self, data: Dict[str, Any], result: ValidationResult) -> bool:
"""
Stage 1: Schema Validation - Validate JSON structure using Pydantic models.
Returns:
True if JSON structure is valid, False otherwise
"""
try:
# Try to parse as Pydantic Project model
Project(**data)
return True
except PydanticValidationError as e:
# Extract Pydantic errors
for error in e.errors():
field = ".".join(str(loc) for loc in error["loc"])
message = error["msg"]
result.add_error(ValidationStage.SCHEMA, message, field)
return False
except Exception as e:
result.add_error(ValidationStage.SCHEMA, f"Schema validation failed: {str(e)}")
return False
def _validate_structure(self, data: Dict[str, Any], result: ValidationResult) -> bool:
"""
Stage 2: Structure Validation - Validate required fields and organizational structure.
Returns:
True if required structure is present, False if missing
"""
# Check required top-level fields
required_fields = ["id", "name", "theme"]
for field in required_fields:
if field not in data or not data[field]:
result.add_error(
ValidationStage.STRUCTURE,
f"Required field '{field}' is missing or empty",
field
)
# Check theme structure
if "theme" in data:
theme_data = data["theme"]
if not isinstance(theme_data, dict):
result.add_error(
ValidationStage.STRUCTURE,
"Theme must be an object",
"theme"
)
elif "name" not in theme_data:
result.add_error(
ValidationStage.STRUCTURE,
"Theme must have a name",
"theme.name"
)
return result.is_valid
def _validate_tokens(self, data: Dict[str, Any], result: ValidationResult) -> bool:
"""
Stage 3: Token Validation - Validate token values, types, and references.
Returns:
True if tokens are valid, False if errors found
"""
if "theme" not in data or "tokens" not in data["theme"]:
return True # No tokens to validate
tokens = data["theme"]["tokens"]
if not isinstance(tokens, dict):
result.add_error(
ValidationStage.TOKEN_VALIDATION,
"Tokens must be defined as an object",
"theme.tokens"
)
return False
# Validate each token
for token_name, token_data in tokens.items():
# Check token structure
if not isinstance(token_data, dict):
result.add_error(
ValidationStage.TOKEN_VALIDATION,
f"Token must be defined as an object",
f"theme.tokens.{token_name}"
)
continue
value = token_data.get("value", "")
if not value:
result.add_error(
ValidationStage.TOKEN_VALIDATION,
"Token value cannot be empty",
f"theme.tokens.{token_name}.value"
)
# Check token references (format: {token-name})
if isinstance(value, str) and value.startswith("{") and value.endswith("}"):
referenced_token = value[1:-1] # Remove { }
if referenced_token not in tokens:
result.add_error(
ValidationStage.TOKEN_VALIDATION,
f"Referenced token '{referenced_token}' does not exist",
f"theme.tokens.{token_name}.value"
)
# Validate category is a valid enum value
category = token_data.get("category")
if category:
try:
TokenCategory(category)
except ValueError:
valid_categories = [c.value for c in TokenCategory]
result.add_error(
ValidationStage.TOKEN_VALIDATION,
f"Category '{category}' is invalid. Valid options: {', '.join(valid_categories)}",
f"theme.tokens.{token_name}.category"
)
return result.is_valid
def _validate_components(self, data: Dict[str, Any], result: ValidationResult) -> bool:
"""
Stage 4: Component Validation - Validate component props, variants, and dependencies.
Returns:
True if components are valid, False if errors found
"""
if "components" not in data:
return True # No components to validate
components = data["components"]
if not isinstance(components, list):
result.add_error(
ValidationStage.COMPONENT_VALIDATION,
"Components must be defined as an array",
"components"
)
return False
# Build component name index
component_names = set()
for i, comp in enumerate(components):
if not isinstance(comp, dict):
result.add_error(
ValidationStage.COMPONENT_VALIDATION,
"Component must be defined as an object",
f"components[{i}]"
)
continue
comp_name = comp.get("name")
if comp_name:
component_names.add(comp_name)
# Validate component dependencies
for i, comp in enumerate(components):
if not isinstance(comp, dict):
continue
comp_name = comp.get("name", f"components[{i}]")
dependencies = comp.get("dependencies", [])
if not isinstance(dependencies, list):
result.add_error(
ValidationStage.COMPONENT_VALIDATION,
"Dependencies must be defined as an array",
f"{comp_name}.dependencies"
)
continue
# Check each dependency exists
for dep in dependencies:
if dep not in component_names:
result.add_error(
ValidationStage.COMPONENT_VALIDATION,
f"Dependency '{dep}' does not exist",
f"{comp_name}.dependencies"
)
return result.is_valid