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

Review of some design patterns

The max(), min(), and sorted() functions have a default behavior without a key= function. They can be customized by providing a function that defines how to compute a key from the available data. For many of our examples, the key() function has been a simple extraction of available data. This isn't a requirement; the key() function can do anything.

Imagine the following method: max(trip, key=random.randint()). Generally, we try not to have have key() functions that do something obscure like this.

The use of a key= function is a common design pattern. Functions we design can easily follow this pattern.

We've also looked at lambda forms that we can use to simplify using higher-order functions. One significant advantage of using lambda forms is that it follows the functional paradigm very closely. When writing more conventional functions, we can create imperative programs that might clutter an otherwise succinct and expressive functional design.

We've looked at several...