This is a Python library and CLI toolkit for processing, analyzing, and visualizing air traffic data. It provides core classes (`Flight`, `Traffic`, `Airspace`) for handling ADS-B trajectories, along with a rich set of algorithms for trajectory filtering, smoothing, navigation event detection (landing, takeoff, go-around, holding patterns), performance estimation (fuel burn, emissions via OpenAP), clustering (DBSCAN, GMM), closest-point-of-approach, trajectory generation, and simplification. Data can be ingested from multiple sources: the OpenSky Network (REST and Trino), Eurocontrol (AIXM, DDR), FAA, FlightRadar24, METAR, and embedded sample datasets. Visualizations are supported via matplotlib, Altair, Plotly, and Leaflet. A CLI subcommands (`show`, `data`, `cache`, `config`, `opensky`) provides interactive data access and caching. The architecture is a standard Python library with an optional web plugin (Tangram) for real-time landing alignment visualization. Although the primary character is an application/library, it also has strong research-oriented features, including published papers, gallery notebooks, and pre-trained ONNX models for holding pattern detection. The codebase is well-structured, modular, and includes a comprehensive test suite and CI/CD pipelines.