Functional Programming in Python

This video gives an overview of entire course.

In this video, we will see how a basic calculator application can be implement using two different programming styles, procedural and functional. By doing so, we will get a first taste of functional programming.

In this video, we will see what statelessness, side-effects, and referential transparency are.

In this video, we will consider two ways of testing code, unit testing and through formal proofs.

In this video, we will consider recursion (functions that call themselves), which is often used in functional programming instead of loops.

In this video, we will consider how functional programming doesn't always match how humans think of the world as consisting of objects.

Functional programming relies heavily on expressions, and eschews statements. But what is the difference between the two? In this video, we will learn exactly how statements and expressions differ.

In this video, we will look at lambda expressions. This is the purest form of functional programming that Python offers. Lambda expressions are functions that consist of a single expression and which do not need to have a name.

In this video, we will take a closer look at 'and' and 'or'.

In this video, we will consider 'if' expressions. These are the functional alternatives to the far more commonly used 'if' statements.

In this video, we will consider how you can pass a function as an argument to another function. The receiving function is by definition a higher-order function.

In this video, we will look at nested functions, that is, functions that are defined inside other functions. We will also consider variable scope, that is, from which functions variables are accessible. These are important concepts for higher order functions.

In this video, we will see how a higher-order function can return functions as return values.

Because operators (+, -, /, and so on) are syntax and not objects, you cannot pass them as arguments or return values. To bypass this problem, the Python operator module offers all operators also as functions.

In this video, we will consider decorators. Decorators are an elegant and Pythonic syntax to implement specific kinds of higher-level functions.

In this video, we will consider decorators that accept arguments. This makes the decorator design pattern even more flexible.

In this video, we will look at currying, a technique for turning a function that takes multiple arguments into a chain of function that each take one argument.

In this video, we will look at monads. Most discussions of monads are complicated, and use lots of mathematical terminology. But, as we will see in this video, the idea of monads is really simple.

In this video, we will look at memoization, which is a technique to optimize code by storing return values of functions.

In this video, we will look at exceptions, which are the standard Python approach to error handling.

In this video, we will look at an alternative approach to error handling, using a Maybe-like decorator. This resembles the Maybe monad, but takes a more Pythonic approach.

In this video, we will take everything that we've learned, and use this newly acquired knowledge to polish the interactive calculator that we developed at the start of this section with the help of all using a functional programming style.