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

Familiar territory


One of the ideas that emerged from the previous list of topics is that most functional programming is already present in Python. Indeed, most functional programming is already a very typical and common part of OOP.

As a very specific example, a fluent Application Program Interface (API) is a very clear example of functional programming. If we take time to create a class with return self() in each method function, we can use it as follows:

some_object.foo().bar().yet_more()

We can just as easily write several closely related functions that work as follows:

yet_more(bar(foo(some_object)))

We've switched the syntax from traditional object-oriented suffix notation to a more functional prefix notation. Python uses both notations freely, often using a prefix version of a special method name. For example, the len() function is generally implemented by the __len__()class special method.

Of course, the implementation of the preceding class might involve a highly stateful object. Even...