The Risk
How Do You Handle Legacy Code When Refactoring for Performance?
Submitted by teenagerpatch » Thu 12-Jun-2025, 14:33Subject Area: General | 0 member ratings |
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Hey everyone,
I’m currently working on optimizing a large internal tool written in Python that’s been in production for over 7 years. The codebase is huge, with tons of legacy patterns, minimal documentation, and some outdated dependencies.
While some parts of the application are relatively stable, others are clearly slowing performance and eating up memory. My question is: what strategies or tools do you use when refactoring legacy code specifically to improve performance, without breaking the entire system?
I’ve tried using profiling tools like cProfile and line_profiler, which helped identify a few bottlenecks, but I’m still struggling with how to clean up the code efficiently without introducing regressions. Any advice on balancing performance improvements with code safety would be much appreciated.
golf hit
Would love to hear your practical approaches or battle-tested tips!
Thanks in advance!
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