Profiling Python code with memory_profiler
When your Python program uses more memory than expected, you can use memory_profiler to find out where memory is allocated.
Profiling
Profiling for performance
Profiling Python code with py-spy
You can use py-spy to profile already running Python code without restarting your process or modifying the source code.
Profiling Python code with line_profiler
Once we have debugged, working, readable (and hopefully testable) code, it may become important to examine it more closely and try to improve the code’s performance. Before we can make any progress in determining if our changes are an improvement, we need to measure the current performance and see where it is spending its time. …
Profiling Python with cProfile, and a speedup tip
We would love for our Python programs to run as fast as possible, but figuring out how to speed things up requires gathering information about the current state of our code and knowing techniques to speed things up. First and foremost, we need to know where our program is spending its time, and what is …
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