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Concurrent and Distributed Computing with Python [Video]

More Information
  • Create and manage threads, and overcome the infamous Python GIL (Global Interpreter Lock)
  • Synchronize your processes and create process pools
  • Implement concurrent futures module through asynchronous programming
  • Practice AsyncResult and Celery backends through examples
  • See how you can implement concurrency using Celery
  • Execute client-server applications using Pyro as an alternative to Celery
  • Create a Python SQS distributed background worker

Facing difficulty in implementing concurrent and multithreaded programs in your Python applications? Is this preventing you from implementing efficient code in your apps and benefiting from multiprocessing?

This course will help you resolve these difficulties. You will start by exploring the basic concepts of concurrency and distributed computing, and you'll learn which Python libraries are relevant to these. You will not only learn to see Celery as a way to build-in concurrency into your apps, but also Pyro as an alternative to Celery. You will create processes and manage processes along with interprocess communication; combine coroutines with threads and processes; practice the management of process pools; implement asynchronous tasks/job queues using AsyncResult and Celery backends; invoke remote methods in your Python-based code, and use these skills and concepts when working with AWS for Python.

All the code and supporting files for this course are available at https://github.com/PacktPublishing/Concurrent-and-Distributed-Computing-with-Python

Style and Approach

A comprehensive course, packed with executable instructions, and working examples. You will learn about all the libraries, techniques, and tools needed to exploit concurrent and distributed programming with Python.

  • See what concurrent and distributed computing can do for your code
  • Build efficient multi-task and multi-process frameworks for your apps
  • Implement threading, multiprocessing, and asynchronous programming in your apps
Course Length 1 hour 48 minutes
Date Of Publication 30 Dec 2018


Harish Garg

Harish Garg is a Co-Founder and Software professional with more than 18 years of Software Industry experience. He currently runs a software consultancy that specializes in Data Analytics and Data Science domain. He has been programming in Python for more than 12 years now and has been using Python for Data Analytics and Data science for 6 years. He has developed numerous courses in Data Science domain and has also published a book involving Data Science with Python, including Matplotlib.

Mithun Lakshmanaswamy

Mithun Lakshmanaswamy of BignumWorks Software LLP has been developing applications in Python for 9+ years. He has written enterprise-level distributed applications that are deployed on scores of servers and have the ability to support thousands of users simultaneously. Some of the applications he has developed are related to parsing millions of virus definitions, analyzing network packets from an enterprise setup, and so on. He is also quite proficient in teaching technical concepts and is quite involved with his current organization’s training programmes. He has worked on multiple projects working with Python, AWS and so on, implementing the concepts of concurrent and distributed computing.