Watch Functional Programming in Python

2017
1 Season

Functional Programming in Python, from Packt Publishing, is a comprehensive guide to functional programming in Python. This show aims to teach developers the core concepts of functional programming, how they can be applied in Python, and how to use them effectively to write clean, readable, and maintainable code.

The show covers all the key concepts of functional programming: immutability, higher-order functions, pure functions, recursion, and more. It then goes on to show how to apply these concepts in the context of Python. This includes using Python's built-in functions, working with lambda functions and closures, and using Python's functional programming libraries such as functools and itertools.

Throughout the show, viewers are introduced to a variety of functional programming techniques and best practices, and given the opportunity to practice these techniques through hands-on coding exercises. The show also covers some of the common pitfalls of functional programming and how to avoid them.

The first part of the show covers the basics of functional programming, starting with an introduction to what functional programming is and its benefits. Viewers are then introduced to the core concepts of functional programming and shown how they can be applied in Python. This includes topics such as higher-order functions, recursion, and map, filter, and reduce.

The show then moves on to cover some more advanced topics, such as using closures and decorators in Python, working with generators, and handling errors and exceptions in functional programming.

One of the key benefits of functional programming is its ability to make code more modular and easier to read and maintain. The show explores this in detail, showing viewers how to write clean, concise, and reusable code using functional programming techniques. It covers topics such as abstraction, data hiding, and functional composition.

The show also covers some of the most commonly used libraries and frameworks for functional programming in Python. This includes libraries such as functools and itertools, which provide useful tools for functional programming, and frameworks such as Flask, which make it easier to build functional programming applications in Python.

One of the unique features of the show is its focus on real-world applications of functional programming in Python. Throughout the show, viewers are shown how functional programming can be used to solve real-world problems and build real-world applications. This includes topics such as data analysis, web development, and system administration.

Overall, Functional Programming in Python, from Packt Publishing, is a comprehensive and practical guide to functional programming in Python. Whether you are a beginner or an experienced Python developer, this show provides a valuable resource for learning how to write clean, readable, and maintainable code using functional programming techniques.

Functional Programming in Python is a series that ran for 1 seasons (44 episodes) between July 28, 2017 and on Packt Publishing

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Seasons

22. Example - A Fully Functional, Interactive Calculator

July 28, 2017

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.

22. Example - A Fully Functional, Interactive Calculator

July 28, 2017

21. Handling Errors in Lambda Expressions

July 28, 2017

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.

21. Handling Errors in Lambda Expressions

July 28, 2017

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.

20. You Cannot Catch Exceptions in Lambda Expressions

July 28, 2017

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

20. You Cannot Catch Exceptions in Lambda Expressions

July 28, 2017

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

19. Memoization - Remembering Results

July 28, 2017

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

19. Memoization - Remembering Results

July 28, 2017

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

18. Monads - Variables That Decide How They Should Be Treated

July 28, 2017

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.

18. Monads - Variables That Decide How They Should Be Treated

July 28, 2017

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.

17. Currying - One Argument per Function

July 28, 2017

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.

17. Currying - One Argument per Function

July 28, 2017

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.

16. Decorators with Arguments

July 28, 2017

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

16. Decorators with Arguments

July 28, 2017

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

15. Decorators - The @ Prefix

July 28, 2017

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

15. Decorators - The @ Prefix

July 28, 2017

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

14. The Operator Module - Operators as Regular Functions

July 28, 2017

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.

14. The Operator Module - Operators as Regular Functions

July 28, 2017

13. Returning a Function from Another Function

July 28, 2017

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

13. Returning a Function from Another Function

July 28, 2017

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

12. Nesting a Function in Another Function

July 28, 2017

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.

12. Nesting a Function in Another Function

July 28, 2017

11. Passing a Function as an Argument to Another Function

July 28, 2017

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.

11. Passing a Function as an Argument to Another Function

July 28, 2017

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.

10. Diving into Inline 'if' Expressions

July 28, 2017

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

10. Diving into Inline 'if' Expressions

July 28, 2017

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

9. Understanding 'and' and 'or'

July 28, 2017

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

9. Understanding 'and' and 'or'

July 28, 2017

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

8. Diving into Lambda Expressions

July 28, 2017

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.

8. Diving into Lambda Expressions

July 28, 2017

7. The Difference Between Statements and Expressions

July 28, 2017

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.

7. The Difference Between Statements and Expressions

July 28, 2017

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.

6. Con - Functional Programming Can Be Unintuitive

July 28, 2017

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

6. Con - Functional Programming Can Be Unintuitive

July 28, 2017

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

5. Con - Complexity and Overly Deep Recursion

July 28, 2017

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

5. Con - Complexity and Overly Deep Recursion

July 28, 2017

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

4. Pro - You Can Prove That Code Is Correct at Least in Theory

July 28, 2017

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

4. Pro - You Can Prove That Code Is Correct at Least in Theory

July 28, 2017

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

3. Pro - Stateless, Referentially Transparent Functions Produce the Same Result

July 28, 2017

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

3. Pro - Stateless, Referentially Transparent Functions Produce the Same Result

July 28, 2017

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

2. Example - A Functional, Interactive Calculator

July 28, 2017

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.

2. Example - A Functional, Interactive Calculator

July 28, 2017

1. The Course Overview

July 28, 2017

This video gives an overview of entire course.

1. The Course Overview

July 28, 2017

This video gives an overview of entire course.

Description

Where to Watch Functional Programming in Python

Functional Programming in Python is available for streaming on the Packt Publishing website, both individual episodes and full seasons. You can also watch Functional Programming in Python on demand at Amazon.