streamparse lets you run Python code against real-time streams of data. It also integrates Python smoothly with Apache Storm.
It 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.
http://streamparse.readthedocs.org/en/latest/
Follow the project's progress, get involved, submit ideas and ask for help via our Google Group, [email protected].
Alphabetical, by last name:
- Chris Abiad (@cabiad)
- Dan Blanchard (@dsblanch)
- Keith Bourgoin (@kbourgoin)
- Jeffrey Godwyll (@rey12rey)
- Tim Hopper (@tdhopper)
- Andrew Montalenti (@amontalenti)
- Rohit Sankaran (@roadhead)
- Mike Sukmanowsky (@msukmanowsky)
- Curtis Vogt (@omus)
See the Roadmap.
