Flight Analysis

A Python package for scraping flight data from Google Flights and analyzing flight prices.

Features

• Scrape flight data from Google Flights (round-trip, one-way, multi-city)
• Store in SQLite database for historical analysis
• CLI interface for agents and automation
• Price history tracking and analysis
• Scheduled scraping via GitHub Actions

Installation

pip install google-flight-analysis

Or for development:

git clone https://github.com/celebi-pkg/flight-analysis
cd flight-analysis
pip install -e .

Requirements

• Python 3.8+
• Chrome/Chromium browser
• ChromeDriver (auto-installed)

Quick Start

CLI Usage

# Get current price for a route
flight-cli price JFK LAX -d 2026-06-01

# Scrape and store flight data
flight-cli scrape JFK LAX -d 2026-06-01

# Database operations
flight-cli db init
flight-cli db routes
flight-cli db history JFK LAX --days 30

Python API

from google_flight_analysis import scrape, get_db

# Scrape flights
result = scrape("JFK", "LAX", "2026-06-01")
print(result.data)  # pandas DataFrame

# Save to database
result.save_to_db()

# Query price history
db = get_db()
history = db.get_price_history("JFK", "LAX", days=30)

Available Commands

Command	Description
price	Get current flight prices
scrape	Scrape and store flight data
db	Database operations (init, info, routes, history)
analyze	Analyze prices, find best buy day
recommend	Recommend best flight option

Options

• --json - JSON output for agents
• --date, -d - Departure date (YYYY-MM-DD)
• --return-date, -r - Return date for round-trip
• --trip-type - one-way or round-trip

Configuration

Configuration is managed via environment variables or Python:

from google_flight_analysis import config

config.chrome.wait = 15  # seconds
config.db.path = "/path/to/flights.db"

Environment variables:

• FLIGHT_DB_PATH - Database path
• FLIGHT_CACHE_DIR - Cache directory

Architecture

google_flight_analysis/
├── scrape/          # Scraping logic
│   ├── driver.py    # ChromeDriver wrapper
│   └── scrape.py   # Scrape class
├── db/             # Database
│   ├── models.py   # SQLAlchemy models
│   └── database.py # Database class
├── cli/             # CLI interface
├── legacy/          # Legacy components (fallback)
└── config.py       # Configuration

Testing

pytest tests/ -v

Contributing

1. Fork the repository
2. Create a feature branch
3. Make changes and add tests
4. Submit a PR

License

MIT License - see LICENSE file.