From simple timers and benchmarking modules to sophisticated stats-based frameworks, look to these tools for insight into the performance of your Python program.

The code is on GitHub and he also links to the generators available in SciPy. We’ve seen SciPy in some Hackaday contest entries before. You can think of it like Matlab for Python.

Here’s one that exists in about 150 lines of Python code. You might wonder what the value is. After all, there are plenty of well-done simulators including Quirk that we have looked at in the past.

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