The devguide doesn't have anything on performance testing that I could find. We do have a number of relatively useful resources in this space though, like pybench and (eventually) speed.python.org. I'd like to add a page to the devguide on performance testing, including an explanation of our performance goals, how to test for them, and what tools are available. Tools I'm aware of: * pybench (relatively limited in real-world usefulness) * timeit module (for quick comparisions) * benchmarks repo (real-world performance test suite) * speed.python.org (would omit for now) Things to test: * speed * memory (tools? tests?) Critically sensitive performance subjects * interpreter start-up time * module import overhead * attribute lookup overhead (including MRO traversal) * function call overhead * instance creation overhead * dict performance (the underlying namespace type) * tuple performance (packing/unpacking, integral container type) * string performance What would be important to say in the devguide regarding Python performance and testing it? What would you add/subtract from the above? How important is testing memory performance? How do we avoid performance regressions? Thanks! -eric
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