Python Static Analysis Backend for CLDK

A comprehensive static analysis tool for Python source code that provides symbol table generation, call graph analysis, and semantic analysis using Jedi, CodeQL, and Tree-sitter.

This project uses uv for dependency management.

• Python 3.12 or higher
• uv installed

1. Clone the repository:

   git clone <repository-url>
   cd codeanalyzer-python

2. Install dependencies using uv:

   uv sync --all-groups

   This will install all dependencies including development and test dependencies.

3. Install the package in development mode:

   uv pip install -e .

The codeanalyzer provides a command-line interface for performing static analysis on Python projects.

codeanalyzer --input /path/to/python/project

• -i, --input PATH: Required. Path to the project root directory to analyze.
• -o, --output PATH: Output directory for analysis artifacts. If specified, results will be saved to analysis.json in this directory.
• -a, --analysis-level INTEGER: Analysis depth level (default: 1)
  • 1: Symbol table generation
  • 2: Call graph analysis
• --codeql/--no-codeql: Enable or disable CodeQL-based analysis (default: disabled)
• --eager/--lazy: Analysis mode (default: lazy)
  • --eager: Rebuild analysis cache at every run
  • --lazy: Use existing cache if available
• -c, --cache-dir PATH: Directory to store analysis cache. Defaults to .cache/codeanalyzer in current working directory.
• --clear-cache/--keep-cache: Clear cache after analysis (default: clear)
• -v/-q, --verbose/--quiet: Enable or disable verbose output (default: verbose)

1. Basic analysis with symbol table:

   codeanalyzer --input ./my-python-project

   This will print the symbol table to stdout in JSON format to the standard output. If you want to save the output, you can use the --output option.

   codeanalyzer --input ./my-python-project --output /path/to/analysis-results

   Now, you can find the analysis results in analysis.json in the specified directory.

2. Toggle analysis levels with --analysis-level:

   codeanalyzer --input ./my-python-project --analysis-level 1 # Symbol table only

   Call graph analysis can be enabled by setting the level to 2:

   codeanalyzer --input ./my-python-project --analysis-level 2 # Symbol table + Call graph

   Note: The --analysis-level=2 is not yet implemented in this version.

3. Analysis with CodeQL enabled:

   codeanalyzer --input ./my-python-project --codeql

   This will perform CodeQL-based analysis in addition to the standard symbol table generation.

   Note: Not yet fully implemented. Please refrain from using this option until further notice.

4. Eager analysis with custom cache directory:

   codeanalyzer --input ./my-python-project --eager --cache-dir /path/to/custom-cache

   This will rebuild the analysis cache at every run and store it in /path/to/custom-cache/.codeanalyzer. The cache will be cleared by default after analysis unless you specify --keep-cache.

   If you provide --cache-dir, the cache will be stored in that directory. If not specified, it defaults to .codeanalyzer in the current working directory ($PWD).

5. Quiet mode (minimal output):

   codeanalyzer --input /path/to/my-python-project --quiet

By default, analysis results are printed to stdout in JSON format. When using the --output option, results are saved to analysis.json in the specified directory.

uv run pytest --pspec -s 

The project includes additional dependency groups for development:

• test: pytest and related testing tools
• dev: development tools like ipdb

Install all groups with:

uv sync --all-groups