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    "info": {
        "author": "JJ Ben-Joseph",
        "author_email": "opensource@phrostbyte.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 2 - Pre-Alpha",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: Apache Software License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3 :: Only",
            "Topic :: Communications"
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        "description": "Qabal\n=====\n\nQabal is a simple and fast open source content-based message broker. Use\nQabal to organize all your multi-stage analytical workloads.\n\nQabal has no install dependencies outside of the default Python runtime.\nUse it on your Raspberry Pi, laptop, or 100 node Dask cluster. Routing\ndecisions in Qabal take constant time, so you can use it for complex\nmultistage analytics with thousands of steps. It\u2019s lightweight, simple\nto understand, easy to integrate with distributed task libraries (eg.\nDask) and fast to execute. It has configurable full pipeline data\nprovenance. In extended provenance mode, Qabal records when every data\nitem is added or updated by what analytic and at what time.\n\nQabal analytics need not be aware that they are part of a message broker\npipeline. They don\u2019t need to depend or import any Qabal library. The\ndata structure used in routing extends the standard Python dictionary.\nQabal comes with ready to use reflection-based content injection, giving\nusers flexibility on the API of their analytics.\n\nInstallation\n~~~~~~~~~~~~\n\n::\n\n    pip install qabal\n\nTry It For Yourself\n~~~~~~~~~~~~~~~~~~~\n\nQabal has a simple API that revolves around attaching functions to a\nSession object.\n\nYou define routes in Qabal using a query DSL that resembles Python\nconditional statements. These get \u201ccompiled\u201d into more traditional\nmessage broker routes.\n\n.. code:: python\n\n    from qabal import Session, Item\n\n    def foo(item):\n        item['foo'] = 'foo'\n        return item\n\n    def bar(item):\n        item['bar'] = 'bar'\n        return item\n\n    def baz(item):\n        item['baz'] = 'baz'\n        return item\n\n    def bar_baz(item):\n        item['bar'] = 'bar!'\n        item['baz'] = 'baz!'\n        return item\n\n    def parameters_are_okay_too(foo, bar):\n        return {'baz': foo+bar}\n\n    # If your trigger query doesn't use the Qabal query language, an analytic need not even depend on Qabal.\n    class AnalyticWithMetadata:\n        __trigger__ = Item['baz'] == 'baz!'\n        __inject__ = True\n        __creates__ = 'qux'\n\n        def __call__(self, baz):\n            return baz + '?'\n\n    example = AnalyticWithMetadata()\n    # Despite all the Qabal metadata, this analytic still maintains a normal API. \n    print(example('hello')) # Outputs: 'hello?'\n\n    sess = Session(provenance='extended') # Qabal records a ton of information in this mode.\n    sess.add(foo, Item['type'] == 'foo')\n    sess.add(bar, Item['foo'] == 'foo')\n    res = sess.feed({'type': 'foo'})\n    print(res)\n    print(res.provenance)\n\n    # The session is mutable at any time.\n    handle = sess.add(bar_baz, Item['bar'] == 'bar')\n    res = sess.feed({'type': 'foo'})\n    sess.remove(handle)\n    print(res)\n\n    sess.add(bar_baz, Item['bar'] == 'bar')\n    # Analytics with metadata don't need a route\n    sess.add(example)\n    res = sess.feed({'type': 'foo'})\n    print(res)",
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        "home_page": "https://www.phrostbyte.com/",
        "keywords": "broker routing content_based",
        "license": "Apache",
        "maintainer": "",
        "maintainer_email": "",
        "name": "qabal",
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        "requires_python": ">=3.6",
        "summary": "A fast and simple message broker with content-based routing.",
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