Concurrent and Distributed Computing with Python

Concurrent and Distributed Computing with Python
MP4 | Video: AVC 1280×720 | Audio: AAC 44KHz 2ch | Duration: 1 Hour 48M | 263 MB
Genre: eLearning | Language: English


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

github.com/PacktPublishing/Concurrent-and-Distributed-Computing-with-Python

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