| ||Ask HN: How do you handle large Python projects?|
69 points by nthompson on May 28, 2016 | hide | past | web | favorite | 48 comments |
|In C++, I follow a playbook for keeping all hell from breaking loose:|
1) Write a googletest
2) Write a googlebenchmark
3) Run all unit tests under AddressSanitizer, ThreadSanitizer, and g++ UB sanitizer
4) Tidy up with clang-format
5) Run cppcheck
So I feel pretty confident I'm not doing something braindead if I can get this stuff through CI.
But for Python, I don't really have good idea when I'm doing something that'll cause me agonizing pain in the future. The only tool I use is flake8, which is awesome, but I can't see memory leaks or performance profiles.
What strategies do you adopt (and what tools do you use) to keep all hell from breaking loose in large Python projects?
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