Finding performance problems: profiling or logging?
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The best way to find performance bottlenecks: observing production
Invasive procedures: Python affordances for performance measurement
All Pythons are slow, but some are faster than others
How vectorization speeds up your Python code
Speeding up software with faster hardware: tradeoffs and alternatives
CI for performance: Reliable benchmarking in noisy environments
The hidden performance overhead of Python C extensions
The limits of Python vectorization as a performance technique
Creating a better flamegraph visualization
Python 和 C/C++ 拓展程序的性能优化
If your software is running slowly in production, do you need profiling or logging?