Chapter 4. Profiling and Optimization

In this chapter, we will cover the following topics:

• Evaluating the time taken by a command in IPython

• Profiling your code easily with cProfile and IPython

• Profiling your code line-by-line with line_profiler

• Profiling the memory usage of your code with memory_profiler

• Understanding the internals of NumPy to avoid unnecessary array copying

• Using stride tricks with NumPy

• Implementing an efficient rolling average algorithm with stride tricks

• Processing large NumPy arrays with memory mapping

• Manipulating large arrays with HDF5