CodeSage

CodeSage is an advanced code review assistant designed to enhance the software development process. It provides automated insights, best practice suggestions, and helps maintain code quality across projects.

Features

• Function length check
• Variable naming convention check
• Import style check
• Complexity check using McCabe metric
• Docstring presence check
• Line length check
• Class and function naming convention check
• Test coverage analysis
• Parallel processing for faster analysis
• Command-line interface for easy use
• Web interface for user-friendly interaction
• Multiple output formats (text, JSON, HTML)
• Git integration for automated pull request analysis

Installation

1. Clone the repository:

   git clone https://github.com/ascender1729/CodeSage.git
   

2. Navigate to the project directory:

   cd CodeSage
   

3. Create and activate a virtual environment:

python -m venv myenv
.\myenv\Scripts\Activate.ps1  # On Windows
source myenv/bin/activate  # On Unix or MacOS

4. Install the required dependencies:

   pip install -r requirements.txt
   

Usage

Command-line Usage

You can run CodeSage from the command line:

python src/main.py [path] [-c CONFIG] [-f {text,json,html}] [-o OUTPUT] [--check-coverage]

Arguments:

• path: Path to the file or directory to analyze (required)
• -c CONFIG, --config CONFIG: Path to the configuration file (optional, defaults to 'config.yaml')
• -f {text,json,html}, --format {text,json,html}: Output format (optional, defaults to 'text')
• -o OUTPUT, --output OUTPUT: Output file for JSON or HTML format (optional)
• --check-coverage: Check test coverage (optional)

Examples:

1. Analyze a single file with text output:

   python src/main.py path/to/your/file.py
   

2. Analyze an entire directory with JSON output and check test coverage:

   python src/main.py path/to/your/project/ -f json -o report.json --check-coverage
   

3. Use a custom configuration file and generate an HTML report:

   python src/main.py path/to/your/project/ -c path/to/custom_config.yaml -f html -o report.html
   

Web Interface Usage

To run the web interface:

python src/web_interface.py

Then open a web browser and navigate to http://localhost:5000.

Git Integration

To use CodeSage for automated pull request analysis, you need to set up the following environment variables:

• REPO_PATH: Path to the local repository
• BASE_BRANCH: Base branch of the pull request (default is 'main')
• HEAD_BRANCH: Head branch of the pull request
• GITHUB_TOKEN: Your GitHub personal access token
• REPO_NAME: Name of the repository in the format 'owner/repo'
• PR_NUMBER: Number of the pull request

Then run:

python src/git_integration.py

This will analyze the changes in the pull request and post the results as a comment on the pull request.

Configuration

You can modify the config.yaml file to adjust the behavior of CodeSage. The default configuration is:

max_function_length: 20
check_variable_naming: true
check_import_style: true
max_complexity: 10
check_docstrings: true
min_test_coverage: 80
max_line_length: 79

Running Tests

To run the unit tests:

python -m unittest discover tests

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE for more information.

Contact

Pavan Kumar - @the_complex_one - pavankumard.pg19.ma@nitp.ac.in

Project Link: https://github.com/ascender1729/CodeSage

Acknowledgements

• Python AST
• McCabe complexity
• Jinja2
• PyGithub
• Coverage.py
• Flask