It seems that the day is near when LLM SEO spam bots will be having meaningful conversations with each other on some theoretical physics mailing lists, casually discovering some previously unknown properties of matter in the process. This one fell a little short… a good try though! :-/
On 4. Mar 2025, at 18:40, Jamima Tariqa via pypy-dev <pypy-dev@python.org> wrote:
Hey Miro,
I completely understand your frustration with tests that run but don’t actually fail the build—it’s like checking a burger’s freshness by looking at it but never taking a bite. I recently decided to put PyPy to the test on my own website, https://costcofoodcourtmenu.com/, to see if it could improve performance, reduce execution times, and handle caching more efficiently.
How I Tested PyPy on My Website Setup & Configuration:
Installed PyPy 3.10 alongside my standard CPython environment. Configured it to work with my WordPress backend, focusing on caching plugins (LiteSpeed Cache, Perfmatters) and the JSON-LD schema generation. Used benchmarking tools to measure request handling speed and memory usage. Benchmarking & Load Testing:
Ran multiple performance tests on key scripts that power my website’s real-time food court menu updates. Used ApacheBench (ab) and wrk to simulate high traffic loads. Compared execution time for my custom scripts under both CPython and PyPy. The Results ✅ The Good:
PyPy drastically improved execution time on long-running scripts. JSON-LD schema generation, which took ~1.8s under CPython, dropped to ~0.9s under PyPy—almost 2x faster! Reduced memory footprint when handling large datasets, especially for scraping competitor menus. WordPress REST API responses showed a 20-25% speed increase on backend queries. ❌ The Issues:
Some third-party WordPress plugins had compatibility issues with PyPy (likely due to C extensions). Certain Django-based admin panel scripts crashed due to failed test cases similar to what you observed—notably with test_getsitepackages. Build process didn’t halt on test failures, which made debugging harder. Some errors only surfaced in logs. What This Means for PyPy Testing in Fedora Your concern is 100% valid—if test failures don’t fail the build, we’re flying blind. In my case, some tests silently failed, leading to unexpected behavior in production. Here’s what I think should be done:
Make test failures break the build—otherwise, we risk shipping unstable packages. Classify and document expected failures (e.g., known compatibility issues). Automate reporting for failures that need upstream fixes instead of ignoring them. Testing should be a safety net, not an afterthought. I’d love to hear how you plan to tackle this on Fedora. If there’s a structured way to report or debug failures, I’m happy to contribute my findings! _______________________________________________ pypy-dev mailing list -- pypy-dev@python.org To unsubscribe send an email to pypy-dev-leave@python.org https://mail.python.org/mailman3/lists/pypy-dev.python.org/ Member address: yury@shurup.com