First off, thank you for considering contributing to SocioSell! It's people like you that make SocioSell such a great tool for transforming social media content into product listings.
- Code of Conduct
- Getting Started
- How Can I Contribute?
- Project Roadmap
- Priority Areas For Contribution
- Style Guidelines
- Pull Request Process
- Community
By participating in this project, you are expected to uphold our Code of Conduct. Please report unacceptable behavior to [email protected].
I. Clone the repository
git clone https://github.com/Varsha-1605/SocioSell.git cd SocioSell
II. Set up a virtual environment
python -m venv venv source venv/bin/activate # Windows: > venv\Scripts\activate
III. Install dependencies
pip install -r requirements.txt
IV. Create a .env
file
cat > .env << EOL GOOGLE_API_KEY=your_google_api_key MONGODB_URL=your_mongodb_connection_string EOL
V. Initialize the database
python database_setup.py
VII. Start the development server
uvicorn main:app --reload
VIII. Access the application
- Open your browser and go to
http://localhost:8000
.
I. Create a new branch for your feature or bugfix:
git checkout -b feature/your-feature-name # or git checkout -b fix/your-bugfix-name
II. Make your changes and commit them using conventional commits:
git add . git commit -m "feat: description of your feature" # or git commit -m "fix: description of your bugfix"
III. Push your changes:
git push origin your-branch-name
- Look for issues labeled with
good-first-issue
orhelp-wanted
- Check our project board for planned features
- If you don't see an issue for your contribution, create one first
- ✅ Basic image and video processing
- ✅ Initial API setup
- ✅ Database integration
- 🔄 Enhanced error handling
- 📋 User authentication
- 📋 Batch processing capabilities
- 📋 Advanced AI features
- 📋 Social media platform integration
- 📋 Analytics dashboard
With the MongoDB setup completed, further enhancements should focus on:
- Data Pooling: Implement connection pooling using pymongo's built-in pooling feature to improve performance by reusing database connections and reducing overhead.
- Error Handling:
- Implement robust error-handling mechanisms for processing failures.
- Log errors to allow debugging and tracking.
- Connect Processors: Integrate image_processor.py and video_processor.py with main.py.
- Error Handling:
- Implement robust error-handling mechanisms for processing failures.
- Log errors to allow debugging and tracking.
- Input Validation:
- Validate media file formats, sizes, and dimensions before processing.
- Reject unsupported formats with clear error messages.
- Progress Indicators:
- Show real-time status updates during image and video processing.
- Responsive Design:
- Ensure a seamless user experience across devices, especially mobile.
- Test and optimize for different screen sizes and resolutions.
- Follow PEP 8
- Use type hints
- Include docstrings for all functions and classes
- Maximum line length: 88 characters
- Use Markdown for documentation
- Include code examples where applicable
- Keep language clear and concise
- Update README.md if adding new features
- Write unit tests for new features
- Ensure all tests pass before submitting PR
- Aim for good test coverage
python -m pytest
- Update the README.md with details of changes if needed
- Update the requirements.txt if you add dependencies
- Fill out the pull request template completely
- Link the PR to any related issues
- Request review from maintainers
- Wait for approval and address any feedback
- Code follows style guidelines
- Tests added/updated and passing
- Documentation updated
- Conventional commit messages used
- No conflicts with main branch
- 💬 Join our Discord Server
- 🔗 Connect on LinkedIn
- 🐦 Follow us on Twitter
If you need help, you can:
- Join our Discord server for real-time discussion
- Open a Discussion on GitHub
- Email the maintainers at [email protected]
All contributors will be added to our Contributors page and the README.md.
Remember that this is an open-source project and we love to receive contributions from our community! Thanks for helping make SocioSell better 🚀