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    "info": {
        "author": "Peter Facka",
        "author_email": "pfacka@binaryparadise.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Environment :: Web Environment",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Operating System :: MacOS :: MacOS X",
            "Operating System :: Microsoft :: Windows",
            "Operating System :: POSIX",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3"
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        "description": "dict2colander\n=============\n\n*Convert python dict (YAML, JSON) to colander schema.*\n\n`Colander <http://docs.pylonsproject.org/projects/colander/en/latest/>`_\nis library, which enables you to validate and convert YAML, JSON\nand HTML form data. Colander schema as it is could be defined only\nin Python declaratively for example like this:\n\n\n\n.. code-block:: python\n\n    import colander\n    \n    class Person(colander.MappingSchema):\n        name = colander.SchemaNode(colander.String())\n        age = colander.SchemaNode(colander.Int(),\n                                  validator=colander.Range(0, 200))\n    \n        @colander.instantiate()\n        class phones(colander.SequenceSchema):\n    \n            @colander.instantiate()\n            class phone(colander.MappingSchema):\n                location = colander.SchemaNode(colander.String(),\n                                     validator=colander.OneOf(['home', 'work']))\n                number = colander.SchemaNode(colander.String())\n\nWith dict2colander you can define the same colander schema in\ndictionary and convert it to colader.MappingSchema object.\n\nInstalation\n-----------\n\nYou can install dict2colander from\n`Python Package Index <https://pypi.python.org/pypi/dict2colander/0.1>`_\nlike this:\n\n\n\n.. code-block:: shell\n\n    pip install dict2colander\n\nUsage\n-----\n\n\n\n.. code-block:: python\n\n    from dict2colander import dict2colander\n    \n    schema_dict = {\n        'type': 'Mapping',\n        'name': 'person',\n        'subnodes': [\n            {'type': 'String', 'name': 'name'},\n    \n            {'type': 'Integer', 'name': 'age',\n             'validators':\n                {'Range': {'args': ('0', '200')}}},\n    \n            {'type': 'Sequence',\n             'name': 'phones',\n             'subnodes': [\n    \n                 {'type': 'Mapping', 'name': 'phone',\n                  'subnodes': [\n    \n                      {'type': 'String', 'name': 'location',\n                       'validators':\n                         {'OneOf': {'args': (['home', 'work'],)}}},\n    \n                      {'type': 'String', 'name': 'number'}\n    \n                  ]}]},\n        ]\n    }\n    \n    schema = dict2colander(schema_dict)\n    data = {\n             'name': 'keith',\n             'age': '20',\n             'friends':[('1', 'jim'),('2', 'bob'), ('3', 'joe'), ('4', 'fred')],\n             'phones':[{'location':'home', 'number':'555-1212'},\n                       {'location':'work', 'number':'555-8989'},],\n             }\n    \n    serialized_data = schema.deserialize(data)\n    print serialized_data\n\nDict2colander is intended to make possible to read colander schemas\nfrom YAML or JSON format. So here is schema from previous example\nwritten in YAML:\n\n\n\n.. code-block:: yaml\n\n    ---\n    name: person\n    type: Mapping\n    \n    subnodes:\n        - name: name\n          type: String\n    \n        - name: age\n          type: Integer\n          validators:\n            Range:\n                args: ['0', '200']\n    \n        - name: phones\n          type: Sequence\n          subnodes: \n            - name: phone\n              type: Mapping\n              subnodes:\n                - name: location\n                  type: String\n                  validators:\n                    OneOf:\n                        args: [[home, work]]\n    \n                - name: number\n                  type: String\n\nNote that *Range* validator has arguments defined as *Strings* not\n*Integers* although that field *age* is of type *Integer*.\n\nHere are data to deserialize in YAML format from first example:\n\n\n\n.. code-block:: yaml\n\n    ---\n    name: keith\n    age: 20\n    friends:\n        - [1, jim]\n        - [2, bob]\n        - [3, joe]\n        - [4, fred]\n    \n    phones:\n        - location: home\n          number: 555-1212\n    \n        - location: work\n          number: 555-8989\n\nHere is example how YAML data are deserialized with schema defined\nin YAML document.\n\n\n\n.. code-block:: python\n\n    import yaml\n    import dict2colander\n    \n    def deserialize(yaml_doc, yaml_schema):\n        mapping_schema = dict2colander.dict2colander(yaml_schema)\n        return mapping_schema.deserialize(yaml_doc)\n    \n    f = open('doc.yaml')\n    doc = yaml.load(f)\n    f.close()\n    \n    f = open('schema.yaml')\n    schema = yaml.load(f)\n    f.close()\n    \n    dict_doc = deserialize(doc, schema)\n    print dict_doc",
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        "keywords": "schema validation dictionary Colander YAML JSON",
        "license": "MIT Licence (http://opensource.org/licenses/MIT)",
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