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

# Variable vs. function initialization and usage 

When you look at the way a variable is initialized and used in Python and compare it to the way a function is declared and used, you might easily assume that variables and functions are completely different things. 

a = 10 

def square(x): 
   return x*x 

b = square(a)
print(a)
print(b)  # prints 100 


Looking at the code, variables `a` and `b` are initialized by assigning a value to them and are used by directly referencing them, as in `print(b)`. In comparison, the function, `square`, is created by the `def` keyword and invoked using round brackets, `()`. 

In fact, `a`, `b`, and `square` are all just variables. The `def` block is just special syntax for defining a function object and assigning it to a variable (square in this case). The round brackets are a syntax that can be used with any callable object (which includes functions) to call it with parameters. 

# Function as an object

To further illustrate this, the following code treats square as an object and prints out its type, id and string representation, just like you can do with any other object: 
 

Learn how to store the reference to a function in a variable. Also, observe how functions are treated as objects 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

Storing Function Reference in a Variable

Variable vs. function initialization and usage