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Concurrent Programming in Python

  • Development
  • May 09, 2025
SynopsisConcurrent Programming in Python, available at $27.99, has an...
Concurrent Programming in Python  No.1

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 Pythons threading module Familiarize yourself with Pythons 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 Pythons threading module
  • Familiarize yourself with Pythons 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

  • Concurrent Programming in Python  No.2
    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

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