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 named tuples to collect data

The third technique for collecting data into a complex structure is the named tuple. The idea is to create an object that is a tuple as well as a structure with named attributes. There are two variations available:

  • The namedtuple function in the collections module.
  • The NamedTuple base class in the typing module. We'll use this almost exclusively because it allows explicit type hinting.

In the example from the previous section, we have nested namedtuple classes such as the following:

from typing import NamedTuple

class Point(NamedTuple):
    latitude: float
    longitude: float

class Leg(NamedTuple):
    start: Point
    end: Point
    distance: float

This changes the data structure from simple anonymous tuples to named tuples with type hints provided for each attribute. Here's an example:

>>> first_leg = Leg(
... Point(29.050501, -80.651169),
... Point(27.186001, -80.139503),
... 115.1751)
>>> first_leg.start.latitude

The first_leg...