October 17, 2026
Dear [Hiring manager's name],
I own a FastAPI rate-quoting service at Fernwright Logistics Software that answers about 8 million requests a day with a median response under 40 milliseconds, and six years into Python I care more about the 92% test coverage behind that number than the framework it's written in. I'm applying to your Python Developer opening because it's scoped around a real production service under real load, not a greenfield rewrite.
Rewriting a nightly pandas ETL job with chunked reads and vectorized transforms shrank its runtime from 4 hours to 35 minutes and cut its memory footprint by about 70%, and splitting a shared utilities repo into five versioned internal packages on a private PyPI index ended the copy-paste drift behind three earlier production defects. Driving the codebase to 92% pytest coverage with strict mypy compliance as a merge gate has blocked more than 60 regressions since we adopted it.
I write async Python against FastAPI and SQLAlchemy, use Redis for anything latency-sensitive, and manage dependencies with Poetry across versioned internal packages. I've contributed nine merged pull requests upstream to two open-source libraries our platform depends on, including a connection-handling fix that made it into the release notes, because a bug I only patch locally is a bug I'll patch again next upgrade.
I'd welcome a conversation about the performance or reliability problem [Company name] most needs a Python developer's attention on right now. Thank you for your consideration.
Sincerely,
Morgan Wilson
