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

Defining classes with total ordering


The total_ordering decorator is helpful for creating new class definitions that implement a rich set of comparison operators. This might apply to numeric classes that subclass numbers.Number. It may also apply to semi-numeric classes.

As an example of a semi-numeric class, consider a playing card. It has a numeric rank and a symbolic suit. The rank matters only when doing simulations of some games. This is particularly important when simulating casino blackjack. Like numbers, cards have an ordering. We often sum the point values of each card, making them number-like. However, multiplication of card × card doesn't really make any sense; a card isn't quite like a number.

We can almost emulate a playing card with a NamedTuple base class as follows:

from typing import NamedTuple
class Card1(NamedTuple):
    rank: int
    suit: str

This is almost a good emulation. It suffers from a profound limitation: all comparisons include both the rank and the suit by default...