{ "info": { "author": "Max Fischer", "author_email": "maxfischer2781@gmail.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 4 - Beta", "Intended Audience :: Developers", "Intended Audience :: System Administrators", "Programming Language :: Python :: 2", "Programming Language :: Python :: 2.6", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.3", "Programming Language :: Python :: 3.4", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", "Topic :: System :: Monitoring" ], "description": "++++++++++++++++++++++++++++++++++++++++++++++++++\npypelined - stream and pipeline processing service\n++++++++++++++++++++++++++++++++++++++++++++++++++\n\n.. image:: https://readthedocs.org/projects/pypelined/badge/?version=latest\n :target: http://pypelined.readthedocs.io/en/latest/?badge=latest\n :alt: Documentation Status\n\n.. image:: https://img.shields.io/github/issues-raw/maxfischer2781/pypelined.svg\n :target: https://github.com/maxfischer2781/pypelined/issues\n :alt: Open Issues\n\nService and framework for creating and running processing pipelines for data streams, events and chunks.\nPipelines of ``pypelined`` are composed from individual elements using the chainlet_ library.\nThey are built in Python configuration files, from custom objects or pre-defined plugins.\n\n.. code:: python\n\n import chainlet\n from pypelined.conf import pipelines\n\n @chainlet.funclet\n def add_time(chunk):\n chunk['tme'] = time.time()\n return chunk\n\n process_chain = Socket(10331) >> decode_json() >> stop_if(lambda value: value.get('rcode') == 0) >> \\\n add_time() >> Telegraf(address=('localhost', 10332), name='chunky')\n pipelines.append(process_chain)\n\nOnce running, ``pypelined`` drives all its processing pipelines in an event driven fashion.\n\n.. _chainlet: http://chainlet.readthedocs.io/en/stable/", 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