How to do “performance-based” (benchmark) unit testing in Python

Question

Let\'s say that I\'ve got my code base to as high a degree of unit test coverage as makes sense. (Beyond a certain point, increasing coverage doesn\'t have a good ROI.)

Answer 1

When I do performance testing, I generally have a test suite of data inputs, and measure how long it takes the program to process each one.

You can log the performance on a daily or weekly basis, but I don't find it particularly useful to worry about performance until all the functionality is implemented.

If performance is too poor, then I break out cProfile, run it with the same data inputs, and try to see where the bottlenecks are.