April 2016
Intermediate to advanced
170 pages
3h 48m
English
Content preview from Distributed Computing with PythonBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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The tools
In Chapter 3, Parallelism in Python, we looked at a few standard library modules that can be used to introduce (single-node) parallelism in our applications. We experimented with both the threading and multiprocessing modules directly and via the higher-level concurrent.futures module.
We saw how, for non-distributed, parallel applications, Python offers a really robust foundation. The preceding three modules are complete and included in every modern Python distribution. They have no external dependencies, which makes them quite appealing.
We explored a few third-party Python modules for simple distributed computing in Chapter 4, Distributed Applications – with Celery. These included Celery, Python-RQ, and Pyro. We saw how to use them ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.