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streamparse lets you run Python code against real-time streams of data. Integrates with Apache Storm.

Project Description

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Build Status

Streamparse lets you run Python code against real-time streams of data via Apache Storm. With streamparse you can create Storm bolts and spouts in Python without having to write a single line of Java. It also provides handy CLI utilities for managing Storm clusters and projects.

The Storm/streamparse combo can be viewed as a more robust alternative to Python worker-and-queue systems, as might be built atop frameworks like Celery and RQ. It offers a way to do “real-time map/reduce style computation” against live streams of data. It can also be a powerful way to scale long-running, highly parallel Python processes in production.

Demo

Documentation

User Group

Follow the project’s progress, get involved, submit ideas and ask for help via our Google Group, streamparse@googlegroups.com.

Contributors

Alphabetical, by last name:

Changelog

See the releases page on GitHub.

Roadmap

See the Roadmap.

Release history Release notifications

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3.13.1

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3.13.0

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3.12.0

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3.11.0

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3.10.0

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3.9.0

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3.8.0

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3.7.1

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3.7.0

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3.6.0

This version
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3.5.0

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3.4.0

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3.3.0

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3.2.0

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3.1.1

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3.1.0

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3.0.1

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3.0.0

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3.0.0.dev3

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3.0.0.dev2

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3.0.0.dev1

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3.0.0.dev0

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2.1.4

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2.1.3

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2.1.2

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2.1.1

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2.1.0

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2.0.2

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2.0.1

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2.0.0

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1.1.0

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1.0.1

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1.0.0

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0.0.13

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0.0.12

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0.0.11

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0.0.10

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0.0.9

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0.0.8

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0.0.7

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0.0.6

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0.0.5

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Filename, size & hash SHA256 hash help File type Python version Upload date
streamparse-3.5.0-py2.py3-none-any.whl (282.8 kB) Copy SHA256 hash SHA256 Wheel py2.py3 May 19, 2017
streamparse-3.5.0.tar.gz (154.4 kB) Copy SHA256 hash SHA256 Source None May 19, 2017

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