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Build graphs to process streams. Now with Celery!

Project description

# Emit

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

A taste:

```python
from emit import router

router = Router()

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

@router.task(['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:

- [Project Documentation][docs]
- [Travis][travis] ([![Build Status](https://travis-ci.org/BrianHicks/emit.png?branch=master)][travis])
- [Github][github]
- [Apache License][license]

Supported Pythons:

- CPython 2.7.2
- CPython 3.2
- PyPy 1.9

Be sure to check [Travis][travis] to see if the platform you want is currently
passing. It may not be.

[celery-docs]: https://emit.readthedocs.org/en/latest/celery.html "Celery Documentation"
[multilang-docs]: https://emit.readthedocs.org/en/latest/multilang.html "Multilang Documentation"
[docs]: http://emit.readthedocs.org/en/latest/ "Emit Documentation"
[travis]: https://travis-ci.org/BrianHicks/emit "Emit on Travis CI"
[github]: https://github.com/BrianHicks/emit "Emit on Github"
[license]: https://github.com/BrianHicks/emit/blob/master/LICENSE.md "Apache License"

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