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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

Using Python to write faster code


The first way to make Python code run faster is to know all features of the language. Python brings many syntax features and modules in the standard library that run much faster than anything you could write by hand. Moreover, although Python may be slow if you write in Python like you would write in C or Java, it is often fast enough when you write Pythonic code.

In this section, we show how badly-written Python code can be significantly improved when using all the features of the language.

Note

Leveraging NumPy for efficient array operations is of course another possibility that we explored in the Introducing the multidimensional array in NumPy for fast array computations recipe in Chapter 1, A Tour of Interactive Computing with Jupyter and IPython. This recipe focuses on cases where, for one reason or another, depending on and using NumPy is not a possible or desirable option. For example, operations on dictionaries, graphs, or text may be easier to write...

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