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

## Use a dictionary

The basic problem in the Fibonacci [example](https://www.educative.io/courses/learn-functional-programming-in-python/inefficient-recursion-fibonacci-numbers) is that we are calling `fibonacci` multiple times, with the same argument. So, each time we are calculating the same value all over again. 



Now, we know that `fibonacci` is a pure function. It has no side effects, and every time you call it with a particular value, you will always get the same result.

What we need is some way to remember all the times it has been called before, remember the result, and only calculate it if it's called with a value that has never been seen before. We can do this using a dictionary to store all the previous calls. The dictionary key is the argument, and the dictionary value is the result. Here is the code: 

Learn how to tackle the inefficiency of repeated function calls introduced by recursion.

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

Memoization

Use a dictionary