notifyme-cli 1.0.0

A command-line tool to send Telegram notifications when long-running commands complete

notifyme-cli

A command-line tool that sends Telegram notifications when long-running commands complete. Never miss when your builds, tests, or data processing jobs finish!

✨ Features

• 🔔 Get notified via Telegram when commands finish
• ⏱️ Shows command duration and exit status
• 📝 Add custom messages to notifications
• 🛠️ Easy setup with interactive configuration
• 🎯 Works with any command-line program
• 💾 Secure local configuration storage

📦 Installation

From PyPI (Recommended)

pip install notifyme-cli

From Source

git clone https://github.com/judeosbert/notifyme-cli.git
cd notifyme-cli
pip install -e .

Development Installation

git clone https://github.com/judeosbert/notifyme-cli.git
cd notifyme-cli
pip install -e ".[dev]"

Setup

1. Create a Telegram Bot

1. Open Telegram and message @BotFather
2. Send /newbot and follow the instructions
3. Save the bot token you receive

2. Get Your Chat ID

1. Message @userinfobot on Telegram
2. It will reply with your user information including your chat ID
3. Save the chat ID (it's a number like 123456789)

3. Configure notify-me

Run the setup command and enter your bot token and chat ID:

notifyme setup

The setup will test the connection and confirm everything works.

📱 Usage

Basic Usage (Recommended)

Run commands and then notify when complete:

# Send default "Task complete" message
python train_model.py && notifyme

# Send custom message
make build && notifyme -m "Build finished"

# Chain multiple commands
npm test && npm build && notifyme -m "CI pipeline complete"

Direct Message Sending

Send a message directly:

notifyme                                    # Send "Task complete"
notifyme -m "Hello from the command line!"  # Send custom message

Command Wrapper (Alternative)

Execute commands with notification wrapper:

notifyme --exec python train_model.py
notifyme --exec -m "Training complete!" python train_model.py

Test Configuration

Test your setup:

notifyme test

Command Examples

# Long-running build with notification (recommended)
docker build -t myapp . && notifyme -m "Docker build complete"

# Database backup with notification
pg_dump mydatabase > backup.sql && notifyme -m "Backup finished"

# Machine learning training
python train.py --epochs 100 && notifyme -m "Model training done"

# Run tests and get notified
pytest tests/ && notifyme

# Complex pipeline
bash ./process_data.sh && notifyme -m "Data processing complete"

# Using the wrapper (alternative method)
notifyme --exec pytest tests/
notifyme --exec -m "Training complete!" python train.py

Configuration

Configuration is stored in ~/.notify-me/config.json. The file contains:

{
  "bot_token": "your-bot-token-here",
  "chat_id": "your-chat-id-here"
}

Security

• Your bot token and chat ID are stored locally on your machine
• No data is sent to external servers except Telegram's API
• Configuration file has restricted permissions (600)

Notification Format

Notifications include:

• ✅/❌ Success or failure status
• Command that was executed
• Execution time
• Timestamp
• Custom message (if provided)
• Exit code (if command failed)

Example notification:

✅ Command completed successfully

Message: Training finished!

Command: python train_model.py
Duration: 2.3 hours
Time: 2024-11-17 14:30:22

Troubleshooting

"Bot not configured" Error

Run notifyme setup to configure your bot token and chat ID.

"Connection error" or timeout

• Check your internet connection
• Verify your bot token is correct
• Make sure your bot hasn't been deleted

"Telegram API error"

• Verify your chat ID is correct
• Make sure you've sent at least one message to your bot
• Check that your bot token is valid

Permission errors

The configuration directory ~/.notify-me/ should be writable by your user.

Development

Running Tests

python -m pytest tests/

Installing for Development

pip install -e ".[dev]"

License

MIT License - see LICENSE file for details.

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if needed
5. Submit a pull request

🤝 Contributing

We welcome contributions! Please see our Contributing Guide for details.

Quick Start for Contributors

1. Fork the repository
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Make your changes and add tests
4. Run tests: make test
5. Submit a pull request

📝 Changelog

See CHANGELOG.md for a detailed history of changes.

📄 License

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

⭐ Support

If you find this project helpful, please consider:

• Giving it a star on GitHub ⭐
• Reporting bugs or requesting features through issues
• Contributing to the codebase
• Sharing it with others who might find it useful

🤖 Built with AI

This project was created with the assistance of AI (GitHub Copilot) to demonstrate modern Python development practices and open-source project structure. The AI helped with:

• Code architecture and implementation
• Comprehensive documentation and examples
• GitHub workflows and community templates
• Testing and quality assurance setup
• Open-source best practices

🔗 Links

• PyPI Package
• GitHub Repository
• Documentation
• Issue Tracker
• Discussions