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

Chapter 11. Decorator Design Techniques

Python offers us many ways to create higher-order functions. In Chapter 5Higher-Order Functions, we looked at two techniques: defining a function that accepts a function as an argument, and defining a subclass of Callable, which is either initialized with a function or called with a function as an argument.

One of the benefits of decorated functions is that we can create composite functions. These are single functions that embody functionality from several sources. A composite function,

, can be somewhat more expressive of a complex algorithm than 

. It's often helpful to have a number of syntax alternatives for expressing complex processing.

In this chapter, we'll look at the following topics:

  • Using a decorator to build a function based on another function
  • The wraps()function in the functools module; this can help us build decorators
  • The update_wrapper() function, which may be helpful