WeMatchSports

Overview

WeMatchSports is a Django-based monolithic application designed to connect sports enthusiasts by enabling them to find nearby players, match based on skills, and communicate seamlessly. This platform allows users to:

• Discover and join sport-specific public rooms for updates and discussions.
• Match with players of similar skill levels.
• Securely chat with connected partners to coordinate games.

The application is built for scalability, user privacy, and ease of use, with data security measures like encryption for sensitive information.

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Architecture

WeMatchSports follows a modular, monolithic architecture with distinct Django apps for key functionalities:

• Authentication: Handles user sign-up, login, session management, and CSRF protection.
• General: Manages the user dashboard, profile settings, notifications, and public rooms.
• Matchmaking: Matches users based on skill similarity using algorithms like cosine similarity.
• Messaging: Provides an encrypted chat interface for secure communication.

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Setup and Deployment

Run with Docker

1. Build the Docker image:

   docker build .

2. Run the container:

   docker run -p 8000:8000 <image_id>

3. Start Kafka services:

   docker compose up

Run without Docker

1. Start the Django development server:

   python manage.py runserver

2. Start Kafka services (ensure Kafka is installed and added to the PATH):

   bin/zookeeper-server-start.sh config/zookeeper.properties
   bin/kafka-server-start.sh config/server.properties

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Core Features by App

1. Authentication

• User sign-up, login, and logout functionalities.
• Session management for temporary user data.
• CSRF protection via Django's built-in mechanism.

2. General

• Personalized user dashboard and profile management.
• Notification and connection management.
• Sport-specific public rooms for discussions and updates.

3. Matchmaking

• Suggests players with similar skills using cosine similarity algorithms.
• Easy connect requests for matched players.

4. Messaging

• Secure, encrypted chat functionality.
• Messages stored in the database with chat history retrieval.

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Technology Stack

• Backend: Django, Django REST Framework
• Database: SQLite (development), PostgreSQL (production-ready configuration)
• Messaging: Apache Kafka
• Containerization: Docker, Docker Compose

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Contributing

Contributions are welcome. To contribute:

1. Fork the repository.
2. Create a new branch for your feature or fix.
3. Submit a pull request with detailed changes.