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

In this chapter, we have learned that:

- List comprehensions provide a simple, idiomatic way to create a list based on an existing iterable, such as a range, another list, or any other iterable.

- List comprehension allows a conditional filter to be applied and then calculates an expression based on the original sequence.

- Although a list comprehension is procedural in style, it has limitations in the processing that can be applied, which makes it far more declarative than an equivalent `for` loop.


> In the next [chapter](https://www.educative.io/courses/learn-functional-programming-in-python/generator-comprehensions), we will meet generator comprehensions, which are similar to list comprehensions but create a lazy iterator rather than a list as output.

Here's a quick summary of list comprehensions in Python.

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

Summary: Comprehensions