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Functional Python Programming

Functional Python Programming

3.7 (3)
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Functional Python Programming

Functional Python Programming

3.7 (3)

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)
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Title Page
Packt Upsell
Contributors
Preface
Index

Using tuples and named tuples


Since Python tuples are immutable objects, they're another excellent example of objects suitable for functional programming. A Python tuple has very few method functions, so almost everything is done using prefix syntax. There are a number of use cases for tuples, particularly when working with list-of-tuple, tuple-of-tuple, and generator-of-tuple constructs.

The namedtuple class adds an essential feature to a tuple: a name that we can use instead of an index. We can exploit named tuples to create objects that are accretions of data. This allows us to write pure functions based on stateless objects, yet keep data bound into tidy object-like packages.

We'll almost always use tuples (and named tuples) in the context of a collection of values. If we're working with single values, or a tidy group of exactly two values, we'll usually use named parameters to a function. When working with collections, however, we may need to have iterable-of-tuples or iterable of the...

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