infobus 0.1.0

A Python client library and CLI tools for accessing Infobús external APIs and integrating transit data into research workflows

Infobús Python Client

A Python client library and CLI tools for accessing Infobús external APIs and integrating transit data into research workflows.

Overview

The infobus package provides a simple and efficient way to interact with Infobús APIs, enabling researchers and developers to:

• Access real-time transit data from public transportation systems
• Retrieve historical transit information for analysis
• Integrate GTFS Realtime feeds into research workflows
• Query screen and display information
• Access weather and alert data associated with transit stops

Installation

# Install from PyPI (when available)
pip install infobus

# Install from source
pip install git+https://github.com/simovilab/infobus-py.git

# Development installation
git clone https://github.com/simovilab/infobus-py.git
cd infobus-py
pip install -e ".[dev]"

Quick Start

Python Library

from infobus import InfobusClient

# Initialize client
client = InfobusClient(base_url="https://your-infobus-instance.com")

# Get real-time transit data
transit_data = client.get_realtime_data()

# Query specific routes
route_info = client.get_route(route_id="route_123")

# Get screen information
screens = client.get_screens()

Command Line Interface

# Get help
infobus --help

# List available routes
infobus routes list

# Get real-time data for a specific route
infobus realtime --route-id route_123

# Export data to CSV
infobus export --format csv --output data.csv

Features

Core API Client

• RESTful API Integration: Clean interface to Infobús REST endpoints
• Authentication Support: Token-based authentication handling
• Error Handling: Comprehensive error handling with meaningful messages
• Rate Limiting: Built-in rate limiting and retry logic

Data Models

• Pydantic Models: Type-safe data models for all API responses
• GTFS Compatibility: Models aligned with GTFS and GTFS Realtime specifications
• Validation: Automatic data validation and serialization

CLI Tools

• Interactive Commands: Easy-to-use command-line interface
• Data Export: Export data in multiple formats (JSON, CSV, XML)
• Batch Operations: Process multiple requests efficiently
• Configuration Management: Store and manage API credentials

Research Integration

• Pandas Integration: Easy conversion to pandas DataFrames
• Time Series Support: Built-in support for time-based analysis
• Geospatial Data: Integration with geospatial libraries

Configuration

Create a configuration file at ~/.infobus/config.yaml:

api:
  base_url: "https://your-infobus-instance.com"
  token: "your-api-token"
  timeout: 30

logging:
  level: "INFO"
  format: "%(asctime)s - %(name)s - %(levelname)s - %(message)s"

Development

Setup Development Environment

# Clone repository
git clone https://github.com/simovilab/infobus-py.git
cd infobus-py

# Install development dependencies
pip install -e ".[dev]"

# Install pre-commit hooks
pre-commit install

Running Tests

# Run all tests
pytest

# Run with coverage
pytest --cov=infobus

# Run specific test file
pytest tests/test_client.py

Code Quality

# Format code
black src/ tests/
isort src/ tests/

# Type checking
mypy src/

# Run pre-commit checks
pre-commit run --all-files

API Reference

InfobusClient

The main client class for interacting with Infobús APIs.

class InfobusClient:
    def __init__(self, base_url: str, token: str = None, timeout: int = 30)
    def get_realtime_data(self, **filters) -> List[RealtimeData]
    def get_routes(self) -> List[Route]
    def get_route(self, route_id: str) -> Route
    def get_screens(self) -> List[Screen]
    def get_alerts(self) -> List[Alert]

Data Models

• RealtimeData: Real-time transit information
• Route: Transit route information
• Screen: Display screen information
• Alert: Service alerts and notifications
• Weather: Weather data for transit locations

Contributing

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

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

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

Support

• Documentation: GitHub README
• Issues: GitHub Issues
• Discussions: GitHub Discussions

Related Projects

• Infobús Server - The main Infobús Django application
• django-app-gtfs - GTFS data models for Django