#### 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.
Title Page
Packt Upsell
Contributors
Preface
Free Chapter
Understanding Functional Programming
Introducing Essential Functional Concepts
Functions, Iterators, and Generators
Working with Collections
Recursions and Reductions
The Itertools Module
More Itertools Techniques
The Functools Module
Decorator Design Techniques
Conditional Expressions and the Operator Module
A Functional Approach to Web Services
Optimizations and Improvements
Other Books You May Enjoy
Index

## Using the map() function to apply a function to a collection

A scalar function maps values from a domain to a range. When we look at the `math.sqrt()` function, as an example, we're looking at a mapping from the `float` value, `x`, to another `float` value, `y = sqrt(x)`, such that

. The domain is limited to positive values. The mapping can be done via a calculation or table interpolation.

The `map()` function expresses a similar concept; it maps values from one collection to create another collection. It assures that the given function is used to map each individual item from the domain collection to the range collection-the ideal way to apply a built-in function to a collection of data.

Our first example involves parsing a block of text to get the sequence of numbers. Let's say we have the following chunk of text:

```>>> text= """\
...   2   3    5    7   11   13   17   19   23   29
...  31  37   41   43   47   53   59   61   67   71
...  73  79   83   89   97  101  103  107  109  113
... 127...```