LEARNING PATH- Python- Functional Programming with Python

LEARNING PATH: Python: Functional Programming with Python, available at $79.99, has an average rating of 4.35, with 45 lectures, 2 quizzes, based on 239 reviews, and has 1993 subscribers.

You will learn about Higher-order functions and Lambda expressions (nameless functions) Error handling in Functional Programming Understand common functional design patterns, and how these apply to Python Understand what an iterator is in Python Iterators and iterator functions built into Python Create your own iterators Understand what a generator coroutine is Master list and dict comprehensions and generator expressions This course is ideal for individuals who are This Learning Path is intended for developers who have a basic understanding of Python and want to expand their developer toolbox with important new techniques. It is particularly useful for This Learning Path is intended for developers who have a basic understanding of Python and want to expand their developer toolbox with important new techniques.

Enroll now: LEARNING PATH: Python: Functional Programming with Python

Summary

Title: LEARNING PATH: Python: Functional Programming with Python

Price: $79.99

Average Rating: 4.35

Number of Lectures: 45

Number of Quizzes: 2

Number of Published Lectures: 45

Number of Published Quizzes: 2

Number of Curriculum Items: 47

Number of Published Curriculum Objects: 47

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Higher-order functions and Lambda expressions (nameless functions)

Error handling in Functional Programming

Understand common functional design patterns, and how these apply to Python

Understand what an iterator is in Python

Iterators and iterator functions built into Python

Create your own iterators

Understand what a generator coroutine is

Master list and dict comprehensions and generator expressions

Who Should Attend

This Learning Path is intended for developers who have a basic understanding of Python and want to expand their developer toolbox with important new techniques.

Target Audiences

This Learning Path is intended for developers who have a basic understanding of Python and want to expand their developer toolbox with important new techniques.

Python is not a functional programming language, but it is a multi-paradigm language that makes functional programming easy to perform, and easy to mix with other programming styles. Python is a high level language used in many development areas, like web development, data analysis, desktop UI and system administration. Functional programming is a style of programming that is characterized by short functions, lack of statements, and little reliance on variables. You will learn what functional programming is, and how you can apply functional programming in Python. If you’re interested to use Functional Programming as a powerful tool to solve many real-world problems by writing robust and bug-free code, then go for this Learning Path.

Packt’s Video Learning Paths are a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it.

The highlights of this Learning Path are:

Understand common functional design patterns, and how these apply to Python

Learn the important role that iterators play in functional programming

In this Learning Path, you’ll learn what functional programming is, and how it differs from other programming styles, such as procedural and object-oriented programming. Then you’ll go on to explore lambda expressions, which are short one-line functions, and are the purest form of functional programming that Python offers. Next, you’ll learn about higher-order functions: functions that accept other functions as an argument, or return other functions as return values. You’ll also encounter important concepts from functional programming, such as monads, currying, statelessness, side-effects, memorization, and referential transparency; these concepts may initially seem odd to Python programmers, but you’ll see how they are elegantly supported by the language.

Further, you’ll learn everything there is to know about iterators in Python and how crucial they are in functional programming, where they are used, among other things, to implement repetitive logic and coroutines. You’ll learn about all standard iterators and iterator functions that Python offers. You’ll also learn to implement your own iterators. Functional programming makes heavy use of iterators, and you’ll learn how you can use them in functional programming through an interactive calculator application.

By the end of this Learning Path, you will get a thorough understanding of iterators to solve many real-world problems by writing robust, testable, and bug-free code.

Meet Your Expert:

We have combined the best works of the following esteemed authors to ensure that your learning journey is smooth:

SebastiaanMath?tcurrently works as assistant professor at the University of Groningen in the Netherlands. He is the lead developer at OpenSesame, which is an open-source, Python-based program for implementing psychology and neuroscience experiments. Sebastiaan is also the designer of DataMatrix, a Python library for numeric computing that is focused on elegance and readability. Sebastiaan also gives regular workshops on using OpenSesame and Python for scientific purposes, and regularly publishes Python tutorials on his YouTube channel. As such, he has extensive experience in teaching Python and making advanced topics seem as easy as possible.

Course Curriculum

Chapter 1: Functional Programming in Python

Lecture 1: The Course Overview

Lecture 2: Example – A Functional, Interactive Calculator

Lecture 3: Pro – Stateless, Referentially Transparent Functions Produce the Same Result

Lecture 4: Pro – You Can Prove That Code Is Correct at Least in Theory

Lecture 5: Con – Complexity and Overly Deep Recursion

Lecture 6: Con – Functional Programming Can Be Unintuitive

Lecture 7: The Difference Between Statements and Expressions

Lecture 8: Diving into Lambda Expressions

Lecture 9: Understanding ‘and’ and ‘or’

Lecture 10: Diving into Inline ‘if’ Expressions

Lecture 11: Passing a Function as an Argument to Another Function

Lecture 12: Nesting a Function in Another Function

Lecture 13: Returning a Function from Another Function

Lecture 14: The Operator Module – Operators as Regular Functions

Lecture 15: Decorators – The @ Prefix

Lecture 16: Decorators with Arguments

Lecture 17: Currying – One Argument per Function

Lecture 18: Monads – Variables That Decide How They Should Be Treated

Lecture 19: Memoization – Remembering Results

Lecture 20: You Cannot Catch Exceptions in Lambda Expressions

Lecture 21: Handling Errors in Lambda Expressions

Lecture 22: Example – A Fully Functional, Interactive Calculator

Chapter 2: Iterators in Functional Programming with Python

Lecture 1: The Course Overview

Lecture 2: Using a List – Mutable Sequences of Elements with a Fixed Order

Lecture 3: Using a Tuple – Immutable Sequences of Elements with a Fixed Order

Lecture 4: Using a Dict – Mutable, Key-value Mappings Without a Fixed Order

Lecture 5: Using a Set – Immutable Collections of Unique Elements Without a Fixed Order

Lecture 6: Unpacking Iterators by Assigning to Multiple Variables

Lecture 7: What Is an Iterator?

Lecture 8: Creating Your Own Iterator

Lecture 9: Exploring Generators

Lecture 10: Lazy Evaluation

Lecture 11: Coroutines – Implementing Concurrency through Generators

Lecture 12: Convenience Iterators – The Collections Module

Lecture 13: List Comprehensions

Lecture 14: Dict Comprehensions

Lecture 15: Generator Expressions

Lecture 16: Nested Comprehensions

Lecture 17: Using Convenience Functions

Lecture 18: Using Numerical and Logical Functions

Lecture 19: The Itertools Module

Lecture 20: The Functools Module

Lecture 21: A Functional, Iterator-Based, Interactive Calculator

Lecture 22: Recognize the Most Suitable Programming Technique for the Job

Lecture 23: A Sensible Interactive Calculator Built with Various Programming Techniques

Instructors

Packt Publishing
Tech Knowledge in Motion

Rating Distribution

1 stars: 2 votes

2 stars: 6 votes

3 stars: 29 votes

4 stars: 81 votes

5 stars: 121 votes

Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

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