Python Docker Testing & Debugging

The project is a Docker-containerised Python application that normally spins up without errors, yet two stubborn trouble-spots remain: it runs slower than expected under load and a few features misbehave despite passing earlier checks. I already have a suite of unit and integration tests; they will be at your disposal to reproduce—and ultimately validate—the fixes.

What I need you to do is pull the repo, build the container, fire up the existing tests, then dig into both performance bottlenecks (CPU spikes, I/O waits, sluggish endpoints) and the functional glitches that still slip through. I’m happy for you to profile with tools such as cProfile, PySpy or similar, and to step through code inside the container with your preferred debugger.

Deliverables
• Detailed report pinpointing the root causes of the performance and functional bugs
• Code-level fixes (PRs or patches) that resolve those issues
• Updated or additional tests where current coverage is insufficient
• Brief “how to reproduce & verify” notes so I can confirm the solution on my end

Acceptance criteria: all supplied tests plus any new coverage must pass in the clean build; application response times should meet or beat baseline targets we will agree upon once you have initial metrics.

If you thrive on methodical debugging and have a good nose for Python performance tuning inside Docker, let’s get this sorted.