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        "classifiers": [
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        "description": "=========\n|Experta|  \n=========\n\n|pypi| |version| |tests| |docs| |coverage|\n\nExperta is a Python library for building expert systems strongly inspired\nby CLIPS_.\n\n.. code-block:: python\n\n   from random import choice\n   from experta import *\n\n\n   class Light(Fact):\n       \"\"\"Info about the traffic light.\"\"\"\n       pass\n\n\n   class RobotCrossStreet(KnowledgeEngine):\n       @Rule(Light(color='green'))\n       def green_light(self):\n           print(\"Walk\")\n\n       @Rule(Light(color='red'))\n       def red_light(self):\n           print(\"Don't walk\")\n\n       @Rule(AS.light << Light(color=L('yellow') | L('blinking-yellow')))\n       def cautious(self, light):\n           print(\"Be cautious because light is\", light[\"color\"])\n\n\n.. code-block:: python\n\n   >>> engine = RobotCrossStreet()\n   >>> engine.reset()\n   >>> engine.declare(Light(color=choice(['green', 'yellow', 'blinking-yellow', 'red'])))\n   >>> engine.run()\n   Be cautious because light is blinking-yellow\n\n\nMigrating from Pyknow\n---------------------\n\nExperta is a Pyknow fork. Just replace any `pyknow` references in your\ncode/examples to `experta` and everything should work the same.\n\n\nExamples\n--------\n\nYou can find some more examples on GitHub_.\n\n.. _CLIPS: http://clipsrules.sourceforge.net\n.. _GitHub: https://github.com/nilp0inter/experta/tree/develop/docs\n.. |Experta| image:: https://raw.githubusercontent.com/nilp0inter/experta/develop/docs/static/expertalogo_small.png\n.. |pypi| image:: https://img.shields.io/pypi/v/experta.svg\n    :target: https://pypi.python.org/pypi/experta\n\n.. |version| image:: https://img.shields.io/pypi/pyversions/experta.svg\n    :target: https://pypi.python.org/pypi/experta\n\n.. |tests| image:: https://travis-ci.org/nilp0inter/experta.svg?branch=master\n    :target: https://travis-ci.org/nilp0inter/experta\n\n.. |docs| image:: https://readthedocs.org/projects/experta/badge/?version=stable\n    :target: https://experta.readthedocs.io/en/stable/\n    :alt: Documentation Status\n\n.. |coverage| image:: https://codecov.io/gh/nilp0inter/experta/branch/develop/graph/badge.svg\n    :target: https://codecov.io/gh/nilp0inter/experta\n    :alt: codecov.io\n\n\nTODO\n----\n\n\nCHANGELOG\n---------\n\n1.9.2\n~~~~~\n\n* Resolved #7. In some situations last activation was removed right\n  after entering the agenda.\n\n\n1.9.1\n~~~~~\n\n* Resolved #3. Rules should not be called with already retracted facts.\n\n\n1.9.0\n~~~~~\n\n* Drop Python 3.4 support.\n* Use setup.cfg to save all package metadata.\n\n\n1.8.0-1.8.2\n~~~~~~~~~~~\n\n* Rebranded to Experta.\n\n\n1.7.0\n~~~~~\n\n* Implemented the template system.\n* Replaced warnings by watchers messages.\n* Fixed freeze() with frozen objects.\n* Fixed unfreeze() with unfrozen objects.\n* Parametrized DefFacts via reset() kwargs.\n\n\n1.6.0\n~~~~~\n\n* Improved overall performance.\n\n\n1.5.0\n~~~~~\n\n* Added Python version 3.7 to tox.ini.\n* Monkey and bananas example.\n* Fixed bug, numeric index args gets repeated in a weird way introduced in `1.4.0`.\n* Pass only the defined args in absence of kwargs.\n\n\n1.4.0\n~~~~~\n\n* Order integer facts keys after making a copy.\n* as_dict method for Fact.\n* freeze and unfreeze method documentation.\n* unfreeze method in pyknow.utils.\n* Zebra example from Clips.\n\n\n1.3.0\n~~~~~\n\n* `pyknow.operator` module.\n* Nested matching.\n* Added Talk 'Sistemas Expertos en Python con PyKnow - PyConES 2017' to docs\n  folder.\n\n\n1.2.0\n~~~~~\n\n* Freeze fact values as the default behavior to address Issue #9.\n* Added `pyknow.utils.anyof` to mitigate Issue #7.\n* Raise RuntimeError if a fact value is modified after declare().\n* Added MATCH and AS objects.\n\n\n1.1.1\n~~~~~\n\n* Removing the borg optimization for P field constraints.\n* Use the hash of the check in the sorting of the nodes to always\n  generate the same alpha part of the network.\n\n\n1.1.0\n~~~~~\n\n* Allow any kind of callable in Predicate Field Constraints (P()).\n\n\n1.0.1\n~~~~~\n\n* DNF of OR clause inside AND or Rule was implemented wrong.\n\n\n1.0.0\n~~~~~\n\n* RETE matching algorithm.\n* Better Rule decorator system.\n* Facts are dictionaries.\n* Documentation.\n\n\n<1.0.0\n~~~~~~\n\n* Unestable API.\n* Wrong matching algorithm.\n* Bad performance\n* PLEASE DON'T USE THIS.\n\n\n",
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