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

Using the finite iterators

The itertools module provides a number of functions that we can use to produce finite sequences of values. We'll look at 10 functions in this module, plus some related built-in functions:

  • enumerate(): This function is actually part of the __builtins__ package, but it works with an iterator and is very similar to other functions in the itertools module.
  • accumulate(): This function returns a sequence of reductions of the input iterable. It's a higher-order function and can do a variety of clever calculations.
  • chain(): This function combines multiple iterables serially.
  • groupby(): This function uses a function to decompose a single iterable into a sequence of iterables over subsets of the input data.
  • zip_longest(): This function combines elements from multiple iterables. The built-in zip() function truncates the sequence at the length of the shortest iterable. The zip_longest() function pads the shorter iterables with the given fill value.
  • compress(): This function filters...