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Aug 13, 2015 · Mertz describes ways to avoid Python’s imperative-style flow control, the nuances of callable functions, how to work lazily with iterators, and the use of higher-order functions. He also lists several third-party Python libraries useful for functional programming.
procedural way, using object-oriented programming or applying a functional approach. In this chapter, we explain the core concepts of functional programming in Python and how we develop our applications using this technique. 3.1 Python Functions
In this quiz, you'll test your understanding of functional programming in Python. You'll revisit concepts such as functions being first-class citizens in Python, the use of the lambda keyword, and the implementation of functional code using map (), filter (), and reduce ().
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This is the code repository for Functional Python Programming - Third Edition, published by Packt. It contains all the supporting project files necessary to work through the book from start to finish.
If you’re a Python developer who wants to discover how to take the power of functional programming (FP) and bring it into your own programs, then this book is essential for you, even if you know next to nothing about the paradigm.
Starting with a general overview of functional concepts, you’ll explore common functional features such as first-class and higher-order functions, pure functions, and more. You’ll see how these are accomplished in Python 3.6 to give you the core foundations you’ll build upon. After that, you’ll discover common functional optimizations for Python to help your apps reach even higher speeds.
All of the code is organized into folders. Each folder starts with a number followed by the application name. For example, Chapter02.
The code will look like the following:
This book presumes some familiarity with Python 3 and general concepts of application development. We won’t look deeply at subtle or complex features of Python; we’ll avoid much consideration of the internals of the language.
We’ll presume some familiarity with functional programming. Since Python is not a functional programming language, we can’t dig deeply into functional concepts. We’ll pick and choose the aspects of functional programming that fit well with Python and leverage just those that seem useful.
Some of the examples use exploratory data analysis (EDA) as a problem domain to show the value of functional programming. Some familiarity with basic probability and statistics will help with this. There are only a few examples that move into more serious data science.
You’ll need to have Python 3.11 installed and running. For more information on Python, visit http://www.python.org/.
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If you have already purchased a print or Kindle version of this book, you can get a DRM-free PDF version at no cost. Simply click on the link to claim your free PDF. https://packt.link/free-ebook/9781803232577
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Although users usually think of Python as a procedural and object-oriented language, it actually contains everything you need for a completely functional approach to programming. This article discusses general concepts of functional programming, and illustrates ways of implementing functional techniques in Python. View more content in this series
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