🐈‍⬛ Bart Bot

🥛🍥🥟🍚🥓🍙🥖☕️🍣 <--- 🐈‍⬛

A delightful Telegram bot that behaves like your real pet! Send photos to build a collection, then feed your virtual pet with emoji food to receive random photos from your gallery.

✨ Features

🐾 Pet-like Behavior

• Unique Responses: Every interaction gets a different pre-defined message, just like a real pet
• Flexible Storage: Each participant has their own photo storage that can be shared with family members
• Unpredictable: Randomly selects images to reply after feeding, keeping interactions exciting

🏗️ Technical Excellence

• Asynchronous Architecture: Built with modern async/await patterns for optimal performance
• Persistent Storage: All chat history and photos stored in PostgreSQL database
• Custom Middleware System: Familiar middleware pattern similar to web frameworks
• Comprehensive Testing: Automated E2E tests running in Telegram's test environment

🚀 Quick Start

Prerequisites

• Python 3.10+
• PostgreSQL 13+
• Telegram Bot Token

Installation

1. Clone the repository

   git clone https://github.com/MishaVyb/bart-bot.git
   cd bart-bot

2. Set up virtual environment

   make venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies

   make install

4. Configure environment

   cp build.env.example build.env
   # Edit build.env with your configuration

5. Set up database

   make database

6. Run the bot

   python -m src.polling

Docker Deployment

For production deployment using Docker:

# Build and run with Docker Compose
make build_run

📖 Usage

Basic Interaction

1. Start the bot: Send /start to begin
2. Upload photos: Send any photo to build your pet's photo collection
3. Feed your pet: Use the emoji food buttons (🥛🍥🥟🍚🥓🍙🥖☕️🍣) to feed your virtual pet
4. Get responses: Your pet will reply with random photos from your collection

Family Sharing

• Forward messages from other users to share their photo storage
• Request permission from storage owners to join their family
• Collaborative feeding with family members

Admin Commands

• /admin_loaddata - Load data from dump file (admin only)
• /count - Check total media count in your storage

🛠️ Development

Project Structure

bart-bot/
├── src/
│   ├── application/          # Bot application logic
│   │   ├── handlers.py       # Message handlers
│   │   ├── middlewares.py    # Custom middleware
│   │   └── tasks.py          # Background tasks
│   ├── database/             # Database models and engine
│   ├── content.py            # Bot content and messages
│   └── configurations.py     # Configuration management
├── tests/                    # Test suite
├── alembic/                  # Database migrations
└── data/                     # Data storage

Code Quality

The project uses several tools to maintain code quality:

# Run all code quality checks
make ci

# Format code
black .
isort .

# Type checking
mypy .

# Linting
flake8 .

Testing

# Run tests
pytest

# Run with coverage
pytest --cov=src

Database Management

# Reset database and migrations
make database

# Create new migration
alembic revision --autogenerate

# Apply migrations
alembic upgrade head

🔧 Configuration

Key configuration options in build.env:

# Bot Configuration
BOT_TOKEN=your_telegram_bot_token
ADMIN_ID=your_telegram_user_id

# Database
DATABASE_URL=postgresql://user:password@localhost/bart_bot

# Content
CONTENT_FILEPATH=bart-bot.content.yaml

# Scheduling
SEND_FEED_ME_MESSAGE_CRONS=["0 9 * * *"]  # Daily at 9 AM

🐳 Docker

Production Deployment

# Build image
docker build -t vybornyy/bart-bot .

# Run with Docker Compose
docker-compose up -d

Services

• polling: Main bot application
• db: PostgreSQL database

📊 Monitoring

The bot includes comprehensive logging and monitoring:

• Structured logging with configurable levels
• Database query monitoring
• Error tracking and reporting
• Performance metrics

🤝 Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Development Guidelines

• Follow the existing code style (Black, isort, flake8)
• Add tests for new features
• Update documentation as needed
• Use type hints throughout

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Built with python-telegram-bot
• Database powered by SQLAlchemy
• Testing with pytest
• Containerized with Docker

---

Made with ❤️ for pet lovers everywhere 🐾