Book Image

Functional Python Programming - Second Edition

By : Steven F. Lott
Book Image

Functional Python Programming - Second Edition

By: Steven F. Lott

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)
Title Page
Packt Upsell
Contributors
Preface
Index

Summary


In this chapter, we've looked at two significant functional programming topics. We've looked at recursions in some detail. Many functional programming language compilers will optimize a recursive function to transform a call in the tail of the function to a loop. In Python, we must do the tail-call optimization manually by using an explicit for loop, instead of a purely function recursion.

We've also looked at reduction algorithms, including sum(), count(), max(), and min() functions. We looked at the collections.Counter() function and related groupby() reductions.

We've also looked at how parsing (and lexical scanning) are similar to reductions since they transform sequences of tokens (or sequences of characters) into higher-order collections with more complex properties. We've examined a design pattern that decomposes parsing into a lower level and tries to produce tuples of raw strings, and a higher level that creates more useful application objects.

In the next chapter, we'll look...