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

Using the operator module instead of lambdas


When using the max(), min(), and sorted() functions, we have an optional key= parameter. The function provided as an argument value modifies the behavior of the higher-order function. In many cases, we used simple lambda forms to pick items from a tuple. Here are two examples we heavily relied on:

from typing import Callable, Sequence, TypeVar
T_ = TypeVar("T_")
fst: Callable[[Sequence[T_]], T_] = lambda x: x[0]
snd: Callable[[Sequence[T_]], T_] = lambda x: x[1]

These match built-in functions in some other functional programming languages that are used to pick the first or second item from a tuple. This includes type hints to assure that there's no other transformation going on—the type of items in the sequence is bound to the type variable, T_, which reflects the type of the result of the function.

We don't really need to write these functions. There's a version available in the operator module named itemgetter(). These are higher-order functions...