Concurrent Programming in Python

Concurrent Programming in Python, available at $27.99, has an average rating of 3.5, with 25 lectures, based on 11 reviews, and has 83 subscribers.

You will learn about Increase your awareness of concurrency in Python Distinguish between parallel programming and concurrent programming Explore Python's threading module Familiarize yourself with Python's Global Interpreter Lock (GIL) Master the similarities between thread and process management Practice with open source Libraries Learn process synchronization and inter-process communication Work with best practices and caveats This course is ideal for individuals who are Python developers who want to learn how to write concurrent applications to speed up the execution of their programs, and to provide interactivity for users, will greatly benefit from this course. It is particularly useful for Python developers who want to learn how to write concurrent applications to speed up the execution of their programs, and to provide interactivity for users, will greatly benefit from this course.

Enroll now: Concurrent Programming in Python

Summary

Title: Concurrent Programming in Python

Price: $27.99

Average Rating: 3.5

Number of Lectures: 25

Number of Published Lectures: 25

Number of Curriculum Items: 25

Number of Published Curriculum Objects: 25

Original Price: $109.99

Quality Status: approved

Status: Live

What You Will Learn

Increase your awareness of concurrency in Python
Distinguish between parallel programming and concurrent programming
Explore Python's threading module
Familiarize yourself with Python's Global Interpreter Lock (GIL)
Master the similarities between thread and process management
Practice with open source Libraries
Learn process synchronization and inter-process communication
Work with best practices and caveats

Who Should Attend

Python developers who want to learn how to write concurrent applications to speed up the execution of their programs, and to provide interactivity for users, will greatly benefit from this course.

Target Audiences

Python developers who want to learn how to write concurrent applications to speed up the execution of their programs, and to provide interactivity for users, will greatly benefit from this course.

In this course, you will skill-up with techniques related to various aspects of concurrent programming in Python, including common thread programming techniques and approaches to parallel processing.

Filled with examples, this course will show you all you need to know to start using concurrency in Python. You will learn about the principal approaches to concurrency that Python has to offer, including libraries and tools needed to exploit the performance of your processor. Learn the basic theory and history of parallelism and choose the best approach when it comes to parallel processing.

After taking this course you will have gained an in-depth knowledge of using threads and processes with the help of real-world examples.

About the Author

BignumWorks Software LLP is an India-based software consultancy that provides consultancy services in the area of software development and technical training. Our domain expertise includes web, mobile, cloud app development, data science projects, in-house software training services, and up-skilling services

Course Curriculum

Chapter 1: Introduction to Concurrent Programming

Lecture 1: The Course Overview

Lecture 2: Advanced OSes and Programming Environments

Lecture 3: Concurrency Versus Parallelism with Examples

Lecture 4: Operating System’s Building Blocks of Parallel Execution

Lecture 5: Libraries in Python Used to Achieve Concurrency and Parallelism

Lecture 6: Python’s Global Interpreter Lock (GIL)

Chapter 2: Creating and Managing Threads

Lecture 1: Overview of Threading Module

Lecture 2: Creating Threads

Lecture 3: Managing Threads

Chapter 3: Thread Synchronization Primitives

Lecture 1: Synchronization in Python

Lecture 2: Using Synchronization Primitives

Lecture 3: Producer–Consumer Pattern

Lecture 4: Using Python Queue Module

Lecture 5: Multithreading in GUI Programming

Chapter 4: Creating and Managing Processes

Lecture 1: Limitations Imposed by GIL

Lecture 2: Multiprocessing

Lecture 3: Similarities Between Thread and Process Management

Lecture 4: Difference Between Thread and Process Management

Lecture 5: Libraries for Practice

Chapter 5: Synchronization and Inter-Process Communication

Lecture 1: Process Synchronization

Lecture 2: Inter-Process Communication

Lecture 3: Best Practices and Anti-Patterns

Chapter 6: Using a Pool of Workers

Lecture 1: Pool of Workers for Maximizing Usage of the Hardware

Lecture 2: When and How to Use a Pool of Workers

Lecture 3: Best Practices and Anti-Patterns

Instructors

Packt Publishing
Tech Knowledge in Motion

Rating Distribution

1 stars: 1 votes
2 stars: 1 votes
3 stars: 3 votes
4 stars: 5 votes
5 stars: 1 votes

Frequently Asked Questions

How long do I have access to the course materials?

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

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

Menu