Skip to content

CONTRIBUTING.md

Latest commit

 

History

History
140 lines (101 loc) · 3.46 KB

CONTRIBUTING.md

File metadata and controls

140 lines (101 loc) · 3.46 KB
Raw

Contributing to Data Skew Intelligence Engine

Thank you for your interest in contributing! This document provides guidelines for contributing to this project.

🚀 Getting Started

Development Setup

# Clone the repository
git clone https://github.com/SanyogSingh07/data-skew-intelligence.git
cd data-skew-intelligence

# Create and activate virtual environment
python -m venv .venv
.venv\Scripts\activate        # Windows
source .venv/bin/activate     # macOS/Linux

# Install all dependencies (including dev tools)
pip install -r requirements-dev.txt

Prerequisites

Tool Version Purpose
Python 3.11+ Runtime
Java JDK 17+ PySpark dependency
Git Latest Version control

📋 How to Contribute

Reporting Bugs

  1. Check existing Issues to avoid duplicates
  2. Use the bug report template (if available)
  3. Include: Python version, Java version, OS, error output, and reproduction steps

Suggesting Features

  1. Open a Discussion or Issue
  2. Describe the use case and expected behavior
  3. Include code examples or mockups if possible

Pull Requests

  1. Fork the repository
  2. Create a feature branch from main: 
    git checkout -b feature/your-feature-name
  3. Make your changes following the code style guidelines below
  4. Run the test suite and linter: 
    ruff check .
pytest -q --cov=.
  5. Commit with a descriptive message: 
    git commit -m "feat: add XYZ capability to mitigation engine"
  6. Push and open a Pull Request against main

🎨 Code Style

This project uses Ruff for linting and formatting:

  • Line length: 120 characters
  • Selected rules: E (pycodestyle), F (pyflakes), I (isort), B (bugbear)
  • Ignored rules: E402 (module-level imports), E501 (line length handled by formatter)
# Check for issues
ruff check .

# Auto-fix
ruff check --fix .

Commit Message Convention

Use Conventional Commits:

Prefix Use Case
feat: New feature
fix: Bug fix
docs: Documentation changes
test: Adding or modifying tests
refactor: Code restructuring (no behavior change)
perf: Performance improvements
ci: CI/CD changes

🧪 Testing

All contributions must pass the existing test suite:

# Full suite
pytest

# With coverage
pytest -q --cov=. --cov-report=term-missing

# Specific module
pytest tests/test_mitigation.py -v

Writing Tests

  • Place tests in the tests/ directory
  • Follow the naming convention test_<module>.py
  • Use fixtures from tests/conftest.py
  • Aim for meaningful assertions, not just coverage

📂 Project Structure Guidelines

Directory Purpose
spark/ PySpark computation — sessions, metrics, mitigation
ml/ scikit-learn training, evaluation, prediction
cli/ Terminal interface (Typer + Rich)
visualization/ Charts (Matplotlib), theme, site export
core/ Pipeline orchestration & configuration
tests/ All pytest tests
docs/ Architecture documents & screenshots

📜 License

By contributing, you agree that your contributions will be licensed under the MIT License.