Class 8 - profiling

Python code at the end of class: class8.zip.

We covered usage of several tools to profile Python code:

1. Using timeit module to time execution of simple code.
2. Profiling with standard library tools: cProfile module for profiling, pstats module for analyzing profiler output, with addition of the snakeviz package for visualization.
3. Using line_profiler package for line-by-line profiling.
4. Using memory_profiler or profile memory usage by using decorators and injecting the profiler into your code and by sampling memory usage without slowing down the code.
5. Using pyinstrument statistical profiler to quickly identify slow code paths and visualize them. Pyinstrument is a very good place to start when profiling your own code and only later use more specialized tools to hone in and time slow code parts.