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.
Follow the project’s progress, get involved, submit ideas and ask for help via our Google Group, firstname.lastname@example.org.
Alphabetical, by last name:
- Dan Blanchard (@dsblanch)
- Keith Bourgoin (@kbourgoin)
- Arturo Filastò (@hellais)
- Jeffrey Godwyll (@rey12rey)
- Daniel Hodges (@hodgesds)
- Wieland Hoffmann (@mineo)
- Tim Hopper (@tdhopper)
- Omer Katz (@thedrow)
- Aiyesha Ma (@Aiyesha)
- Andrew Montalenti (@amontalenti)
- Rohit Sankaran (@roadhead)
- Viktor Shlapakov (@vshlapakov)
- Mike Sukmanowsky (@msukmanowsky)
- Cody Wilbourn (@codywilbourn)
- Curtis Vogt (@omus)
See the releases page on GitHub.
See the Roadmap.
Release history Release notifications
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size & hash SHA256 hash help||File type||Python version||Upload date|
|streamparse-3.16.0-py2.py3-none-any.whl (80.4 kB) Copy SHA256 hash SHA256||Wheel||py2.py3|
|streamparse-3.16.0.tar.gz (54.9 kB) Copy SHA256 hash SHA256||Source||None|