Jug 1.0.1

A Python framework for implementing distributed computing software, Python code that runs in parallel on multiple machines and processes
Jug is a Python implementation of the MapReduce framework (now a standard part of Hadoop), allowing developers to write code that can run in different forms of parallelization.

This means code that can run in parallel on the same machine, or across a computing cluster (multiple machines).

Jug enables developers to organize code into smaller pieces, and selecting where, how and when to run it.

While this may be over the top for small websites and apps, this behavior can be very useful in applications with a high traffic load or that handle large amounts of data.

Jug can work and store data locally via the hard-drive, or it can use remote storage. For the later case, the Redis database is supported.

Main features:

  • Persistent data storage support
  • Reuses partial results
  • Concurrency support
  • Local data storage
  • Remote data storage
  • Operation status checker

last updated on:
June 17th, 2014, 1:06 GMT
license type:

MIT License

developed by:
Luis Pedro Coelho
operating system(s):
Windows / Linux / Mac OS / BSD / Solaris
C: \ Development Tools \ Complete applications
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What's New in version 0.9.7
  • Fix use of numpy subclasses
  • Fix redis URL parsing
  • Fix ``shell`` for newer versions of IPython
  • Correctly fall back on non-sqlite ``status``
read full changelog

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