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IPython Interactive Computing and Visualization Cookbook

You're reading from   IPython Interactive Computing and Visualization Cookbook Over 100 hands-on recipes to sharpen your skills in high-performance numerical computing and data science in the Jupyter Notebook

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Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781785888632
Length 548 pages
Edition 2nd Edition
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Author (1):
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Cyrille Rossant Cyrille Rossant
Author Profile Icon Cyrille Rossant
Cyrille Rossant
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Table of Contents (17) Chapters Close

Preface 1. A Tour of Interactive Computing with Jupyter and IPython FREE CHAPTER 2. Best Practices in Interactive Computing 3. Mastering the Jupyter Notebook 4. Profiling and Optimization 5. High-Performance Computing 6. Data Visualization 7. Statistical Data Analysis 8. Machine Learning 9. Numerical Optimization 10. Signal Processing 11. Image and Audio Processing 12. Deterministic Dynamical Systems 13. Stochastic Dynamical Systems 14. Graphs, Geometry, and Geographic Information Systems 15. Symbolic and Numerical Mathematics Index

Profiling your code easily with cProfile and IPython

The %timeit magic command is often helpful, yet a bit limited when we need detailed information about what takes up most of the execution time. This magic command is meant for benchmarking (comparing the execution times of different versions of a function) rather than profiling (getting a detailed report of the execution time, function by function).

Python includes a profiler named cProfile that breaks down the execution time into the contributions of all called functions. IPython provides convenient ways to leverage this tool in an interactive session.

How to do it...

IPython offers the %prun line magic and the %%prun cell magic to easily profile one or multiple lines of code. The %run magic command also accepts a -p flag to run a Python script under the control of the profiler. These commands accept a lot of options as can be seen with %prun? and %run?.

In this example, we will profile a numerical simulation of random walks. We will cover...

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