Gain insights into functional programming in Python, learn about functions as objects, recursion, closures, and generators, and discover how to confidently apply these concepts to your projects.

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The functional programming paradigm can be a powerful tool, especially as it can be integrated seamlessly with procedural and object-oriented code in Python. 

In this course, you’ll learn what functional programming is, how it’s used, and the features of Python that support it. To start, you’ll learn how functions act as objects, the role of mutability, and how to perform recursion. 

In the latter half of the course, you’ll focus on closures, iterables & iterators, generators, and more. Throughout the course will be three exams which will test your understanding and really drive home what you’ve learned.  

By the end, you’ll have a new programming paradigm to add under your belt and have the confidence to start using functional programming in your own projects.

Learn Functional Programming in Python

# Anonymous functions
 
Now we will look at various ways that closures can be used, starting with using closures to create anonymous functions. 

## A simple introduction to `map`

The `map` function is a built-in Python function. In its simplest form, it accepts a function object and a sequence (e.g., a list). It applies the function to each element of the list. 

a = [2.2, 5.6, 1.9, 0.1] 
b = map(round, a) 
# print(b)
print(list(b)) # [2, 6, 2, 0] 

In this example, we apply the `round` function to every element in `a`. The `round` function rounds a value to the nearest integer. This gives the result shown above. (Note that `map` uses lazy iteration, so we will use the `list` function to turn the result into a list that we can print). 


Learn how to use closures to create anonymous functions.

Introduction

Functions as Objects

Mutability

Recursion

Functional Programming in Python - Exam 1

Closures

Iterators

Transforming Iterables

Reducing Iterables

Functional Programming in Python - Exam 2

Comprehensions

Generators

Partial Application and Currying

Functors and Monads

Functional Programming in Python - Exam 3

Useful Libraries

Conclusion

Creating Anonymous Functions

Anonymous functions

A simple introduction to `map`