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

Functors and applicative functors


The idea of a functor is a functional representation of a piece of simple data. A functor version of the number 3.14 is a function of zero arguments that returns this value. Consider the following example:

>>> pi = lambda: 3.14
>>> pi()
3.14

We created a zero-argument lambda object that returns a simple value.

When we apply a curried function to a functor, we're creating a new curried functor. This generalizes the idea of applying a function to an argument to get a value by using functions to represent the arguments, the values, and the functions themselves.

Once everything in our program is a function, then all processing is simply a variation of the theme of functional composition. The arguments and results of curried functions can be functors. At some point, we'll apply a getValue() method to a functor object to get a Python-friendly, simple type that we can use in uncurried code.

Since the programming is based on functional composition,...