I have a mid-sized Flask 2.x web app that has slowly turned into a tangle of long views, duplicated helpers, and the occasional performance hiccup. I want the codebase streamlined so it is both faster and far easier to maintain. My priorities are clear: • Performance optimisation – measurable gains in response time and memory usage after you profile, pinpoint, and fix bottlenecks. • Code readability & structure – sensible Blueprints, smaller modules, consistent naming, and up-to-date docstrings so new contributors can find their way around quickly. The stack also includes Jinja templates, SQLAlchemy, Celery for background jobs, and a growing (but incomplete) pytest suite. Everything sits in a private GitHub repo; I’ll grant access once we agree on the collaboration details. Deliverables • A refactored, fully working codebase pushed to a feature branch • Profiling report outlining the issues found and the improvements achieved • Updated or new tests that push overall coverage to at least 85 % and pass in CI • Linting/formatting setup (flake8 or pylint + black) with zero errors • A short migration/README note explaining the new layout and any breaking changes If you have tackled similar Flask clean-ups, especially where performance mattered, I’d love to hear how you approached them and what tools you favour (e.g., cProfile, line_profiler, async tweaks, caching). I’m ready to start as soon as I find the right fit.