py_code_improver 0.2.1

utility to suggest code refactoring

Code Improver Tool

Overview

The Code Improver Tool is a Python application that leverages OpenAI's language models to enhance code quality.

It can perform various actions such as cleaning code, adding docstrings, generating tests, and creating README files based on the provided source code. This tool is designed for developers who want to automate the improvement of their codebases efficiently.

Features

• Code Cleaning: Automatically refines the code for better readability and performance.
• Docstring Generation: Adds meaningful docstrings to functions and classes for improved documentation.
• Test Generation: Creates unit tests to ensure code reliability.
• README Generation: Generates a README file to provide an overview of the project.

Requirements

• Python 3.11 or higher
• langchain_core
• langchain_openai
• Access to OpenAI API

Installation

1. Clone the repository:

   git clone <repository-url>
   cd <repository-directory>
   

2. Install the required packages:

   pip3 install -r requirements.txt
   

3. Set your OpenAI API key in your environment variables:

   export OPEN_AI_API_KEY='your_openai_api_key'
   

Usage

To use the Code Improver Tool, run the script from the command line with the required arguments:

python3 cli.py --file <path_to_your_code_file> --action <action_type>

Arguments

• --file or -f: The path to the code file that you want to process (required).
• --action or -a: The action you want to perform. Options include:
  • clean: Clean the code.
  • docstrings: Add docstrings to the code.
  • tests: Generate tests for the code.
  • readme: Create a README file for the project.
• --openai-api-key or -k: OpenAI API key to use

Example

To clean a Python file named example.py, you would run:

python3 cli.py --file example.py --action clean

CLI

It is possible to install:

pip3 install py_code_improver

and run as cli:

py_code_improver --file example.py --action docstrings

poetry run py_code_improver --file example.py --action readme

Output

The tool generates a new file with the same name as the input file, appended with a timestamp and the extension .llm. For example, if you process example.py, the output file will be named example.py.llm<timestamp>.

Logging

The application logs its activities to the console. You can adjust the logging level in the code if you want more or less verbosity.

Error Handling

The tool includes error handling for the following scenarios:

• If the specified file exceeds the character limit (9999 characters).
• If an unrecognized action is provided.

Contributing

Contributions are welcome! Feel free to submit a pull request or open an issue for any bugs or feature requests.

License

This project is licensed under the MIT License. See the LICENSE file for more details.

Contact

For questions or feedback, please reach out to [[e-mail]].