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

Working with iterables


As noted in the previous chapters, Python's for loop works with collections. When working with materialized collections such as tuples, lists, maps, and sets, the for loop involves the explicit management of states. While this strays from purely functional programming, it reflects a necessary optimization for Python. If we assume that state management is localized to an iterator object that's created as a part of the for statement evaluation, we can leverage this feature without straying too far from pure, functional programming. If, for example, we use the for loop variable outside the indented body of the loop, we've strayed from purely functional programming by leveraging this state control variable.

We'll return to this in Chapter 6, Recursions and Reductions. It's an important topic, and we'll just scratch the surface here with a quick example of working with generators.

One common application of for loop iterable processing is the unwrap(process(wrap(iterable)...