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.

• uv installed
• Python 3.12 or higher. You can use uv to install Python if it's not already installed:

  uv python install 3.12

1. Clone the repository:

   git clone https://github.com/codellm-devkit/codeanalyzer-python cd codeanalyzer-python

2. Install dependencies using uv:

   uv sync --all-groups

   This will install all dependencies including development and test dependencies.

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

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

To view the available options and commands, run uv run codeanalyzer --help. You should see output similar to the following:

❯ uv run codeanalyzer --help Usage: codeanalyzer [OPTIONS] COMMAND [ARGS]... Static Analysis on Python source code using Jedi, CodeQL and Tree sitter. ╭─ Options ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮ │ * --input -i PATH Path to the project root directory. [default: None] [required] │ │ --output -o PATH Output directory for artifacts. [default: None] │ │ --analysis-level -a INTEGER 1: symbol table, 2: call graph. [default: 1] │ │ --codeql --no-codeql Enable CodeQL-based analysis. [default: no-codeql] │ │ --eager --lazy Enable eager or lazy analysis. Eager will rebuild the analysis cache at every run and lazy will use the cache if available. Defaults to lazy. [default: lazy] │ │ --cache-dir -c PATH Directory to store analysis cache. If not specified, the cache will be stored in the current working directory under `.codeanalyzer`. Defaults to None. [default: None] │ │ --clear-cache --keep-cache Clear cache after analysis. [default: clear-cache] │ │ --verbose -v --quiet -q Enable verbose output. [default: v] │ │ --help Show this message and exit. │ ╰──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯

1. Basic analysis with symbol table:

   uv run 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.

   uv run 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:

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

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

   uv run 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:

   uv run 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:

   uv run 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):

   uv run 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