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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Summary
Writing and running small- or medium-sized distributed applications in Python is not hard. There are many high-quality frameworks that we can leverage among others, for example, Celery, Pyro, various job schedulers, Twisted, MPI bindings (not discussed in this book), or the multiprocessing module in the standard library.
The real difficulty, however, lies in monitoring and debugging our applications, especially because a large fraction of our code runs concurrently on many different, often remote, computers.
The most insidious bugs are those that end up producing incorrect results (for example, because of data becoming corrupted along the way) rather than raising an exception, which most frameworks are able to catch and bubble up.
The monitoring ...
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