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

Building named tuples with functional constructors

There are three ways we can build NamedTuple instances. The choice of technique we use is generally based on how much additional information is available at the time of object construction.

We've shown two of the three techniques in the examples in the previous section. We'll emphasize the design considerations here. It includes the following choices:

  • We can provide the parameter values according to their positions. This works out well when there are one or more expressions that we were evaluating. We used it when applying the haversine() function to the start and end points to create a Leg object:
Leg(start, end, round(haversine(start, end), 4))
  • We can use the * argument notation to assign parameters according to their positions in a tuple. This works out well when we're getting the arguments from another iterable or an existing tuple. We used it when using map() to apply the float() function to the latitude and longitude values: