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        "author": "Iv\u00e1n de Paz Centeno",
        "author_email": "ipazc@unileon.es",
        "bugtrack_url": null,
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            "Environment :: Console",
            "Intended Audience :: Developers",
            "Intended Audience :: Education",
            "Intended Audience :: Science/Research",
            "Natural Language :: English",
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            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
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        "description": "PyMDict\n#######\n\n.. image:: https://badge.fury.io/py/pymdict.svg\n    :target: https://badge.fury.io/py/pymdict\n.. image:: https://travis-ci.org/ipazc/pymdict.svg?branch=master\n    :target: https://travis-ci.org/ipazc/pymdict\n.. image:: https://coveralls.io/repos/github/ipazc/pymdict/badge.svg?branch=master\n    :target: https://coveralls.io/github/ipazc/pymdict?branch=master\n\n\nAdvanced Python Mongo Dict.\nA Python dictionary based on a MongoDB. It allows to treat a collection as a dictionary in Python, with extensive capabilities, like allowing basic queries, bulk operations and versioning (forks).\n\nINSTALLATION\n############\n\nCurrently it is only supported Python3.4 onwards. It can be installed through pip:\n\n.. code:: bash\n\n    $ pip3 install pymdict\n\n\nUSAGE\n#####\n\nIn order to run, a MongoDB server is required.\n\nA Mongo-based dictionary can be instantiated as follows:\n\n.. code:: python\n\n    >>> from pymdict.mongo_dict import MongoDict\n    >>>\n    >>> m = MongoDict(\"custom_id\", mongo_host=\"localhost\", mongo_port=27017)\n\n\nOnce `m` is instantiated, it can be used as a normal dictionary.\n\n.. code:: python\n\n    >>> m[\"key\"] = \"value\"\n    >>> m[44] = \"value2\"\n    >>> m[\"key2\"] = \"value3\"\n    >>> m[\"number\"] = 44\n\n    >>> print(list(m.keys()))\n    [\"key\", 44, \"key2, \"number\"]\n\n    >>> for key, value in m.items():\n    ...     print(\"{}: {}\".format(key, value))\n    key: value\n    44: value2\n    key2: value3\n    number: 44\n\n\nIn addition, there are advanced functionalities like queries:\n\n.. code:: python\n\n    >>> for key, value, _ in m('key % ey'):\n    ...     print(\"{}: {}\".format(key, value))\n    key: value\n    key2: value3\n\n    >>> for key, value, _ in m('key % ey or value = 44'):\n    ...     print(\"{}: {}\".format(key, value))\n    key: value\n    key2: value3\n    number: 44\n\nQueries also support to query with sub-dict elements:\n\n.. code:: python\n\n    >>> m[\"first\"] = {\"example\": 44}\n    >>> m[\"second\"] = {\"example\": 45}\n    >>> m[\"third\"] = {\"example\": 46}\n\n    >>> for key, value, _ in m('value.example > 44 and value.example < 46'):\n    ...     print(\"{}: {}\".format(key, value))\n    second: 45\n\n(TODO: Check the wiki page for more information about the query syntax)\n\nNote that all the stores and removals are stored within a MongoDB. This means for each addition,edit and removal there is at least one connection to the MongoDB backend. In order to optimize it, a bulk operation can be used to wrap such amount of operations in a single connection:\n\n.. code:: python\n\n    >>> with m.bulk(buffer_size=100) as m:\n    ...     for x in range(2000):\n    ...         m[\"key{}\".format(x)] = {\"example\": x}\n\nAlso, a mongo dict can be forked without the need to copy its content. This is specially useful if the target dict is extremely big and a copy is wanted. Note that a fork is an immediate process, and it allows to override or remove elements without modifying an original dictionary. It is achieved by applying a versioning technique with the dictionaries and it is still in an experimental state.\n\n(TODO: More information about forking and versioning in the wiki page)\n\n.. code:: python\n\n    >>> m['foo'] = \"bar\"\n    >>> fork = m.fork()\n    >>> print(fork['foo'])\n    bar\n    >>> fork['foo'] = \"foo\"\n    >>> print(fork['foo'], m['foo'])\n    foo bar\n",
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