Concurrent and Distributed Computing with Python [Video]

Concurrent and Distributed Computing with Python

Concurrent and Distributed Computing with Python [Video]

English | MP4 | AVC 1920×1080 | AAC 48KHz 2ch | 1h 48m | 265 MB
eLearning | Skill level: All Levels

Concurrent and Distributed Computing with Python [Video]: Implement concurrency in your apps using Celery, and Pyro, and make your Python apps distributed with AWS

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.

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.

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