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Mastering Python

You're reading from   Mastering Python Master the art of writing beautiful and powerful Python by using all of the features that Python 3.5 offers

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Product type Paperback
Published in Apr 2016
Publisher Packt
ISBN-13 9781785289729
Length 486 pages
Edition 1st Edition
Languages
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Author (1):
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Rick Hattem Rick Hattem
Author Profile Icon Rick Hattem
Rick Hattem
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Table of Contents (17) Chapters Close

Preface 1. Getting Started – One Environment per Project FREE CHAPTER 2. Pythonic Syntax, Common Pitfalls, and Style Guide 3. Containers and Collections – Storing Data the Right Way 4. Functional Programming – Readability Versus Brevity 5. Decorators – Enabling Code Reuse by Decorating 6. Generators and Coroutines – Infinity, One Step at a Time 7. Async IO – Multithreading without Threads 8. Metaclasses – Making Classes (Not Instances) Smarter 9. Documentation – How to Use Sphinx and reStructuredText 10. Testing and Logging – Preparing for Bugs 11. Debugging – Solving the Bugs 12. Performance – Tracking and Reducing Your Memory and CPU Usage 13. Multiprocessing – When a Single CPU Core Is Not Enough 14. Extensions in C/C++, System Calls, and C/C++ Libraries 15. Packaging – Creating Your Own Libraries or Applications Index

Functional programming


Functional programming is a paradigm that originates from the lambda calculus. Without diving too much into the lambda calculus (λ-calculus), this roughly means that computation is performed through the use of mathematical functions, which avoids mutable data and changing state of surroundings. The idea of a strictly functional language is that all function outputs are dependent only on the input and not on any external state. Since Python is not strictly a programming language, this doesn't necessarily hold true, but it is a good idea to adhere to this paradigm as mixing these can cause unforeseen bugs as discussed in Chapter 2, Pythonic Syntax, Common Pitfalls, and Style Guide.

Even outside of functional programming, this is a good idea. Keeping functions purely functional (relying only on the given input) makes code clearer, easier to understand, and better to test as there are less dependencies. Well-known examples can be found within the math module. These functions...

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