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streamparse 3.5.0

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

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.

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.

 
File Type Py Version Uploaded on Size
streamparse-3.5.0-py2.py3-none-any.whl (md5) Python Wheel py2.py3 2017-05-19 276KB
streamparse-3.5.0.tar.gz (md5) Source 2017-05-19 150KB