Python MariaDB Tkinter

EVA geolocation analysis tool

NASA Johnson Space Center, 2025

Problem

Flight controllers needed to figure out which spacewalks (EVAs) could happen at the same time based on where astronauts would physically be on the ISS exterior. They were doing this manually. Separately, the EVA branch was running 500+ queries on a legacy MediaWiki system that was slow and fragile.

Approach

Built a Python tool with a Tkinter GUI that parses YAML files of astronaut coordinate data, speed metrics, and time constraints. It runs proximity analysis and distance calculations, then spits out Excel reports showing which EVAs can run concurrently. Flight controllers just load the file and get the answer.

For the database migration: rewrote 500+ semantic MediaWiki queries into optimized Cargo database queries (MariaDB underneath). Added proper indexing. The queries now power mission-critical workflows like personnel scheduling and tool failure tracking.

Tech stack

Python Tkinter YAML parsing MariaDB Cargo DB MediaWiki Excel automation

Status

Deployed and in use by EVA flight controllers. Database migration complete.

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