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.

fp_in_python.tar.gz

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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

# Existing libraries supporting composition

There are quite a few open-source libraries that provide functional programming support, including a *compose* function. 

> `funcy` and `fn.py` are two such libraries that can be found on github.com or installed with pip.

## PyMonad

We will concentrate on `PyMonad` in this section. It provides composition of curried functions (see the [`PyMonad` `@curry` decorator](https://www.educative.io/courses/learn-functional-programming-in-python/currying) described earlier in this chapter).

Rather than using a *compose* function, PyMonad uses a *compose operator*, `*`. 

Here is how it works. 

### Example one
Assume that our task is to create an iterator that counts down. We start by creating curried versions of the built-in `reversed` and `range` functions as shown below, from `line 3` to `line 9`. Once these functions are defined, composing them is quite neat (`line 11`).

Learn to compose curried functions using the * operator in PyMonad.

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

Libraries Supporting Composition

Existing libraries supporting composition