Skip to content

Latest commit

 

History

History
112 lines (86 loc) · 3.69 KB

CONTRIBUTING.md

File metadata and controls

112 lines (86 loc) · 3.69 KB
Raw

Contributing to Scrape-ML

Thank you for considering contributing to Scrape-ML! We welcome all types of contributions—bug reports, feature suggestions, documentation improvements, and code contributions. To make the process smooth, please follow the guidelines below.

Table of Contents

  1. Code of Conduct
  2. How to Contribute
  3. Pull Request Process
  4. Development Environment Setup

Code of Conduct

By participating in this project, you agree to uphold our Code of Conduct. Please ensure that your contributions are respectful and considerate of others.

How to Contribute

Reporting Bugs

If you find a bug, please open an issue in our repository. When reporting a bug, provide as much detail as possible, including:

  • The version of Python you’re using.
  • Steps to reproduce the issue.
  • Screenshots or error logs, if available.

Suggesting Enhancements

We are open to feature suggestions and improvements! If you have an idea for enhancing the project, please open an issue with:

  • A clear and concise description of the suggested feature.
  • How it would be beneficial to the project.
  • Any potential implementation details you have in mind.

Submitting Code Changes

  1. Fork the repository:

    • Click the "Fork" button in the top right corner of the repository page on GitHub.

  2. Clone the forked repository locally:

   git clone https://github.com/your-username/Scrape-ML.git
   cd scrape-ml
  1. Create a new branch for your changes:
git checkout -b your-feature-branch
  1. Make your changes:
  • Ensure code quality and update documentation as necessary.
  1. Test your changes thoroughly:
  • Run existing tests and verify that everything works as expected.
  1. Commit your changes with a descriptive message:
git add .
git commit -m "Add a brief description of the changes made"
  1. Push to your fork and submit a pull request:
git push origin your-feature-branch
  1. Go to the original repository on GitHub and click on "New Pull Request."
  • Select your branch from the dropdown and create the pull request.

Pull Request Process

  • Ensure your code follows the existing code style.
  • Update documentation as needed.
  • Verify that all existing tests pass and write new tests for new features.
  • Mention the issue your pull request addresses (if applicable).

Development Environment Setup

To contribute to Scrape-ML, follow these steps to set up your development environment:

Prerequisites

Setup Instructions

  1. Clone the repository: 
    git clone https://github.com/your-username/scrape-ml.git
  2. Create and activate a virtual environment: 
    python -m venv env
source env/bin/activate  # For Linux/macOS
.\env\Scripts\activate  # For Windows
  3. Install the dependencies: 
    pip install -r requirements.txt
  4. Launch Jupyter Notebook to start contributing: 
    jupyter notebook

Additional Guidelines

  • Make sure to follow clean coding practices.
  • Add comments wherever necessary for better code understanding.
  • If you are adding new functionality, update the documentation in the README.

We are excited to see your contributions and collaborate with you!