d53b61008c
This commit introduces a new project analysis engine to the DSS. Key features include: - A new analysis module in `dss-mvp1/dss/analyze` that can parse React projects and generate a dependency graph. - A command-line interface (`dss-mvp1/dss-cli.py`) to run the analysis, designed for use in CI/CD pipelines. - A new `dss_project_export_context` tool in the Claude MCP server to allow AI agents to access the analysis results. - A `.gitlab-ci.yml` file to automate the analysis on every push, ensuring the project context is always up-to-date. - Tests for the new analysis functionality. This new architecture enables DSS to have a deep, version-controlled understanding of a project's structure, which can be used to power more intelligent agents and provide better developer guidance. The analysis is no longer automatically triggered on `init`, but is designed to be run manually or by a CI/CD pipeline.
86 lines
2.9 KiB
Python
86 lines
2.9 KiB
Python
import os
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import json
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import networkx as nx
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from pyast_ts import parse
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import cssutils
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import logging
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# Configure logging
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logging.basicConfig(level=logging.INFO)
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log = logging.getLogger(__name__)
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# Configure cssutils to ignore noisy error messages
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cssutils.log.setLevel(logging.CRITICAL)
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def analyze_react_project(project_path: str) -> dict:
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"""
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Analyzes a React project, building a graph of its components and styles.
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Args:
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project_path: The root path of the React project.
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Returns:
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A dictionary containing the component graph and analysis report.
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"""
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log.info(f"Starting analysis of project at: {project_path}")
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graph = nx.DiGraph()
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# Supported extensions for react/js/ts files
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supported_exts = ('.js', '.jsx', '.ts', '.tsx')
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for root, _, files in os.walk(project_path):
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for file in files:
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file_path = os.path.join(root, file)
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relative_path = os.path.relpath(file_path, project_path)
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if file.endswith(supported_exts):
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graph.add_node(relative_path, type='file', language='typescript')
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try:
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with open(file_path, 'r', encoding='utf-8') as f:
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content = f.read()
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# Placeholder for AST parsing and analysis
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# ast = parse(content)
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# For now, we'll just add the node
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except Exception as e:
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log.error(f"Could not process file {file_path}: {e}")
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elif file.endswith('.css'):
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graph.add_node(relative_path, type='file', language='css')
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try:
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# Placeholder for CSS parsing
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# sheet = cssutils.parseFile(file_path)
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pass
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except Exception as e:
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log.error(f"Could not parse css file {file_path}: {e}")
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log.info(f"Analysis complete. Found {graph.number_of_nodes()} files.")
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# Convert graph to a serializable format
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serializable_graph = nx.node_link_data(graph)
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return serializable_graph
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def save_analysis(project_path: str, analysis_data: dict):
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"""
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Saves the analysis data to a file in the project's .dss directory.
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"""
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dss_dir = os.path.join(project_path, '.dss')
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os.makedirs(dss_dir, exist_ok=True)
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output_path = os.path.join(dss_dir, 'analysis_graph.json')
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with open(output_path, 'w', encoding='utf-8') as f:
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json.dump(analysis_data, f, indent=2)
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log.info(f"Analysis data saved to {output_path}")
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if __name__ == '__main__':
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# Example usage:
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# Replace '.' with the actual path to a React project for testing.
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# In a real scenario, this would be called by the MCP.
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target_project_path = '.'
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analysis_result = analyze_react_project(target_project_path)
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save_analysis(target_project_path, analysis_result)
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