After you have tested it, and are sure that it does what you intended, the next step is often to get it to do that quickly and efficiently. Profiling is a way to assess the performance of your code, on a function-by-function, or even line-by-line basis. You might want to assess different aspects of code performance, and the two major ones are how long it takes for your code to run and (not unrelated) how much memory the code uses.
We will look at an assessment of the speed of performing different parts of your code and the assessment of memory consumption of different parts of your code.
We will use the python
line_profiler library for this. It
can be installed from the command line using:
pip install line_profiler
Fire up the notebook 001-line-profiler to see how to use it in the context of
an ipython session.
Memory profiler can be installed with:
pip install memory_profiler
Please also install psutil, which makes memory_profiler work faster:
pip install psutil
Head over to the notebook 002-mem-profiler to see how it's done.