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 Python lambda forms

In many cases, the definition of a helper function seems to requires too much code. Often, we can digest the key function to a single expression. It can seem wasteful to have to write both def and return statements to wrap a single expression.

Python offers the lambda form as a way to simplify using higher-order functions. A lambda form allows us to define a small, anonymous function. The function's body is limited to a single expression.

The following is an example of using a simple lambda expression as the key:

long = max(trip, key=lambda leg: leg[2])
short = min(trip, key=lambda leg: leg[2])  

The lambda we've used will be given an item from the sequence; in this case, each leg three tuple will be given to the lambda. The lambda argument variable, leg, is assigned and the expression, leg[2], is evaluated, plucking the distance from the three tuple.

In cases where a lambda is used exactly once, this form is ideal. When reusing a lambda, it's important to avoid copy...