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Build graphs to process streams. Now with Celery!
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docs
emit
examples
tests
.gitignore
.travis.yml
LICENSE.md
MANIFEST.in
README.rst
requirements.txt
setup.cfg
setup.py
tox.ini

README.rst

Emit

Emit is a Python library for realtime data processing. It can distribute work with Celery or RQ, coordinate execution in other languages, and let you swing from the trees of your graph with Tarzan-like precision.

A taste:

from emit import router

router = Router()

@router.node(['word'], entry_point=True)
def parse_document(msg):
    for word in msg.document.strip().split(' '):
        yield word

@router.node(['word', 'count'], 'parse_document')
def count_word(msg):
    return msg.word, redis.zincrby('word_counts', msg.word, 1)

import random
document = 'the words in this document will be counted and emitted by count_word'.split(' ')
router(document=' '.join(random.choice(document) for i in range(20)))

So how do you get it? On PyPI!

pip install emit

Some Links:

Supported Pythons:

  • CPython 2.6
  • CPython 2.7
  • CPython 3.2
  • CPython 3.3 (except for Celery, currently)
  • PyPy 1.9

Installing from source/development branch:

Emit's releases are fairly frequent, so you should be good to use a released version. However, if you need something currently not in a version, try the develop branch:

pip install git+git://github.com/BrianHicks/emit.git@develop

Just do be warned that things will break. And be sure to check Travis to see if the platform you want is currently passing. It should be, but maybe not.

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