Flight Project

Overview

• End-to-end reference project that ingests aeronautical telemetry, cleans it with Polars and pushes curated artefacts back into the AGILab export directory.

• Demonstrates how to orchestrate file-based distributions, run inside the cluster pool and keep the Streamlit user interface responsive while the worker pipeline operates asynchronously.

• Bundles Streamlit lab material (lab_steps.toml) and prompt examples to help you reproduce the workflow showcased in AGILab live demos.

Manager (flight.flight)

• Wraps the runnable application. Converts user-supplied arguments into a validated FlightArgs model, normalises data URIs, and initialises cluster dispatch by seeding WorkDispatcher.

• Provides from_toml / to_toml helpers so snippets on the Execute page can reload configuration and persist overrides.

• Handles managed-PC specifics (path remapping, data directory resets) and keeps the dataframe export folder clean between runs.

Args (flight.flight_args)

• Pydantic models that capture the full surface area of the project’s configuration, including dataset location, slicing parameters and cluster toggles.

• Ships conversion utilities for reading/writing app_settings.toml and merging overrides that are injected by the Execute page.

Worker (flight_worker.flight_worker)

• Extends PolarsWorker to preprocess raw telemetry, compute geodesic distances between samples, and partition files across the cluster.

• Contains Cython hooks (flight_worker.pyx) and pre/post-install scripts so you can see how compiled extensions are integrated into a distribution.

• Demonstrates Windows-friendly path handling and data staging for managed environments.

Assets & Tests

• app_test.py exercises the full install → distribute → run flow.

• test/_test_* modules focus on unit-level behaviour for manager, worker and orchestration glue.

• Modules and lab_steps.toml contain the Streamlit lab material used by the Experiment page.

API Reference