Book Image

Functional Python Programming. - Second Edition

Book Image

Functional Python Programming. - Second Edition

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

Writing generator functions


Many functions can be expressed neatly as generator expressions. Indeed, we've seen that almost any kind of mapping or filtering can be done as a generator expression. They can also be done with a built-in higher-order function, such as map() or filter(), or as a generator function. When considering multiple statement generator functions, we need to be cautious that we don't stray from the guiding principles of functional programming: stateless function evaluation.

Using Python for functional programming means walking on a knife edge between purely functional programming and imperative programming. We need to identify and isolate the places where we must resort to imperative Python code because there isn't a purely functional alternative available.

We're obligated to write generator functions when we need statement features of Python. Features, such as the following, aren't available in generator expressions:

  • A with context to work with external resources. We'll...