Skip to main content

stream and pipeline processing service

Project description

Documentation Status Open Issues

Service and framework for creating and running processing pipelines for data streams, events and chunks. Pipelines of pypelined are composed from individual elements using the chainlet library. They are built in Python configuration files, from custom objects or pre-defined plugins.

import chainlet
from pypelined.conf import pipelines

@chainlet.funclet
def add_time(chunk):
    chunk['tme'] = time.time()
    return chunk

process_chain = Socket(10331) >> decode_json() >> stop_if(lambda value: value.get('rcode') == 0) >> \
    add_time() >> Telegraf(address=('localhost', 10332), name='chunky')
pipelines.append(process_chain)

Once running, pypelined drives all its processing pipelines in an event driven fashion.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for pypelined, version 0.1.3
Filename, size File type Python version Upload date Hashes
Filename, size pypelined-0.1.3-py2.py3-none-any.whl (21.6 kB) File type Wheel Python version 2.7 Upload date Hashes View
Filename, size pypelined-0.1.3.tar.gz (14.0 kB) File type Source Python version None Upload date Hashes View

Supported by

Pingdom Pingdom Monitoring Google Google Object Storage and Download Analytics Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page