Testing
9 posts
mutmut-mcp: Tests, CI, and Survivor Prioritization
mutmut-mcp gets 23 tests, CI, and a refresher on how to use mutation testing to systematically find gaps in your test suite.
Where Did All the RAM Go? Memory Profiling with Memray
High CPU isn''t the only performance issue. Learn how Memray helps track memory leaks and excessive allocation in your Python library to optimize usage.
TRL 4-5: Laboratory and Relevant Environment Validation
Deep dive into TRL 4-5. Understand laboratory validation (TRL 4) and the crucial transition to relevant environment testing (TRL 5) for tech maturity.
Finding the Slowdown: Profiling Python Code with Pyinstrument
Your benchmark says a function is slow, but why? Profilers like Pyinstrument help you pinpoint exactly where your Python code is spending its time.
How Fast Is It? Benchmarking Your Code with Pytest-Benchmark
Performance matters! Easily measure Python library speed with pytest-benchmark. Track performance, find regressions, and optimize effectively with benchmarks.
Mastering Mocking in Python with pytest-mock
A practical guide to mocking in Python testing - from basic concepts to advanced techniques with pytest-mock and other helpful libraries
Will It Blend? Testing Across Environments with Tox
Works on your machine? Great, but what about Python 3.9 or 3.12? Tox ensures library compatibility across different Python versions and dependency sets easily.
Are Your Tests Enough? Measuring Coverage with Coverage.py
Writing tests is step one. Step two is knowing what parts of your library code those tests actually exercise. Enter Coverage.py.
Why Your Library Needs Pytest (And How to Get Started)
Testing is vital for Python libraries. Explore why it''s crucial and how Pytest simplifies writing powerful tests with less boilerplate and better assertions.