Concurrent Programming in Python

Concurrent Programming in Python

Harness the power of modern code structures with Python to improve performance and flexibility

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15.87 9.52

About 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.

Other Information

  • Certificate will provided in this course on Completion
  • Full lifetime access
  • Available on Mobile & Laptop

What Students Will Learn In Your Course?

  • 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

Are There Any Course Requirements Or Prerequisites?

Knowledge about Python.

Who Are Your Target Students?

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.

Course Content

  • 25 lectures
  • 02:20:44
  • The Course Overview
    00:06:26
  • Advanced OSes and Programming Environments
    00:08:19
  • Concurrency Versus Parallelism with Examples
    00:02:24
  • Operating System s Building Blocks of Parallel Execution
    00:02:54
  • Libraries in Python Used to Achieve Concurrency and Parallelism
    00:02:20
  • Python s Global Interpreter Lock (GIL)
    00:06:28
  • Overview of Threading Module
    00:02:44
  • Creating Threads
    00:10:19
  • Managing Threads
    00:07:05
  • Synchronization in Python
    00:05:56
  • Using Synchronization Primitives
    00:05:14
  • Producer Consumer Pattern
    00:06:09
  • Using Python Queue Module
    00:04:30
  • Multithreading in GUI Programming
    00:03:29
  • Limitations Imposed by GIL
    00:04:49
  • Multiprocessing
    00:11:31
  • Similarities Between Thread and Process Management
    00:03:20
  • Difference Between Thread and Process Management
    00:08:15
  • Libraries for Practice
    00:04:21
  • Process Synchronization
    00:07:11
  • Inter-Process Communication
    00:06:53
  • Best Practices and Anti-Patterns
    00:03:53
  • Pool of Workers for Maximizing Usage of the Hardware
    00:05:06
  • When and How to Use a Pool of Workers
    00:05:04
  • Best Practices and Anti-Patterns
    00:06:04
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Packt Publication

  • 4.48 (13)
  • 13 Reviews
  • 13 Students
  • 935 Courses