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Functional Python Programming

Functional Python Programming

3.7 (3)
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Functional Python Programming

Functional Python Programming

3.7 (3)

Overview of this book

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. You’ll learn FP concepts such as lazy evaluation using Python’s generator functions and expressions. Moving forward, you’ll learn to design and implement decorators to create composite functions. You'll also explore data preparation techniques and data exploration in depth, and see how the Python standard library fits the functional programming model. Finally, to top off your journey into the world of functional Python, you’ll at look at the PyMonad project and some larger examples to put everything into perspective.
Table of Contents (22 chapters)
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Title Page
Packt Upsell
Contributors
Preface
Index

Summary


In this chapter, we looked at a number of functions in the itertools module. This library module provides a number of functions that help us work with iterators in sophisticated ways.

We looked at the product() function that will compute all the possible combinations of the elements chosen from two or more collections. The permutations() function gives us different ways to reorder a given set of values. The combinations() function returns all the possible subsets of the original set.

We also looked at ways in which the product() and permutations() functions can be used naively to create extremely large result sets. This is an important cautionary note. A succinct and expressive algorithm can also involve a vast amount of computation. We must perform basic complexity analysis to be sure that the code will finish in a reasonable amount of time.

In the next chapter, we'll look at the functools module. This module includes some tools to work with functions as first-class objects. This builds...

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