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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 have seen two reductions that are higher-order functions: max() and min(). We also looked at the two central higher-order functions, map() and filter(). We also looked at sorted().

We also looked at how to use a higher-order function to also transform the structure of data. We can perform several common transformations, including wrapping, unwrapping, flattening, and structure sequences of different kinds.

We looked at three ways to define our own higher-order functions, which are as follows:

  • The def statement. Similar to a lambda form that we assign to a variable.
  • Defining a callable class as a kind of function that emits composite functions.
  • We can also use decorators to emit composite functions. We'll return to this in Chapter 11, Decorator Design Techniques.

In the next chapter, we'll look at the idea of purely functional iteration via recursion. We'll use Pythonic structures to make several common improvements over purely functional techniques. We'll also look...

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