PrintWe have experimented with some very simple code profiling by introducing the time() function into our code in previous examples using it to record the start and end times of our code and check the overall performance.
While that gives us a high level view of the performance of our code, we do not know where specific bottlenecks might exist within that code. For example what is the slowest part of our algorithm, is it the file reading or writing or the calculations in between? When we know where these bottlenecks are we can investigate ways of removing them or at least using faster techniques to speed up our code.
In this section, we will focus on basic profiling that looks at how long each function call takes – not each individual line of code. This basic type of code profiling is built into Spyder (and most IDEs). However, we also provide some complementary materials that explain how to visualize profiling results and on how to profile each line of code individually but these parts will be entirely optional because they are quite a bit more complex and require the installation of additional software and packages. It is possible that you will run into some technical/installation issues, so our recommendation is that you only come back and try to run the described steps in these optional subsections yourself if you are done with lesson and homework assignment and still have time left.