Concurrent and Distributed Computing with Python [Video]
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-PythonStyle 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.
|Course Length||1 hour 48 minutes|
|Date Of Publication||30 Dec 2018|
|Pyro – Remote Method Invocation|
|Client-Server Application Using Pyro|