Sat Trajectory Project

Overview

• Satellite-focused workload that fuses Two-Line Element (TLE) catalogues, waypoint requests and service definitions to plan communication windows.

• Highlights multiprocessing and caching strategies for large orbital datasets while keeping Streamlit interaction smooth.

• Complements the Explore 3D cartography and network views by providing satellite-centric outputs.

Manager (sat_trajectory.sat_trajectory)

• Loads and caches TLE files, computes orbital parameters and seeds WorkDispatcher with dataset metadata.

• Normalises paths for managed machines, resets dataframe output directories and exposes from_toml / to_toml helpers for Execute snippets.

• Uses helper functions to pre-process satellite catalogues (mean motion, semi-major axis) so workers can focus on heavy computation.

Args (sat_trajectory.app_args)

• Rich Pydantic model that captures all required artefacts: data root, satellite catalogue folders, service definitions, heatmaps and output formats.

• Provides merge/dump utilities so configuration updates flow seamlessly between Streamlit forms and app_settings.toml.

Worker (sat_trajectory_worker.sat_trajectory_worker)

• Distributes satellites across workers, generates visibility windows and aggregates results into exportable dataframes.

• Makes use of thread pools and shared-memory caches to accelerate orbit propagation.

• Includes Cython extensions and post-install scripts so heavy dependencies are prepared ahead of time.

Assets & Tests

• app_test.py validates install/distribute/run for the satellite scenario.

• test/_test_* modules cover TLE parsing, worker orchestration and helper utilities.

• src/app_settings.toml enables the cartography views that make use of the generated satellite telemetry.

API Reference