Book Image

Functional Python Programming. - Second Edition

Book Image

Functional Python Programming. - Second Edition

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
Contributors
Preface
Index

Functional composition and currying


Some functional languages work by transforming a multiargument function syntax into a collection of single argument functions. This process is called currying: it's named after logician Haskell Curry, who developed the theory from earlier concepts.

Currying is a technique for transforming a multiargument function into higher-order single argument functions. In a simple case, consider a function

; given two arguments x and y; this will return some resulting value, z. We can curry

into into two functions:

and

. Given the first argument value, x, evaluating the function

 returns a new one-argument function,

. This second function can be given the second argument value, y, and it returns the desired result, z.

We can evaluate a curried function in Python as follows: f_c(2)(3). We apply the curried function to the first argument value of 2, creating a new function. Then, we apply that new function to the second argument value of 3.

This applies to functions...