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        "author": "Douglas Treadwell",
        "author_email": "douglas.treadwell@gmail.com",
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            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: Implementation :: CPython",
            "Programming Language :: Python :: Implementation :: PyPy"
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        "description": "Marshmallow Models\n==================\n\n\nInstallation\n------------\n\n```\npip install marshmallow-models\n```\n\n\nContributing\n------------\n\nFeature requests, feedback,\n[issues](https://github.com/douglas-treadwell/marshmallow-models/issues),\nand pull requests are welcome and appreciated.\n\nPlease follow the [Marshmallow Contributing Guidelines](\nhttps://github.com/marshmallow-code/marshmallow/blob/dev/CONTRIBUTING.rst\n).\n\n\nOverview\n--------\n\nInspired by [Schematics](https://github.com/schematics/schematics),\npowered by [Marshmallow](https://github.com/marshmallow-code/marshmallow).\n\nWhereas Marshmallow is an excellent serialization/deserialization\nand validation library, it wasn't intended to be a class or type\ndefinition library, which Schematics was.\n\nThis library provides a Schematics-like Model but\nusing Marshmallow's Fields and validation.  This library also\nintentionally maintains the usage style of marshmallow so that\nusers of Marshmallow Schemas will be able to use these Models easily.\n\nUsage\n-----\n\nModels are defined like Schemas, but whereas a Schema is instantiated\nwith parameters and then used to schema.dump(data) or schema.load(data),\nor schema.validate(data),\nModels are instantiated, attributes may be assigned to them, and then\nthey can be .dump()'d, .dumps()'d or .validate()'d.\n\n### Basic Usage\n\n```python\nfrom marshmallow_models import Model\nfrom marshmallow.fields import String, Integer\n\nclass PersonModel(Model):\n    name = String(required=True)\n    age = Integer(required=True)\n\nperson = PersonModel()\n\nperson.name = 'Tester'\nperson.age = 100\n\n# or equivalently:\nperson = PersonModel({'name': 'Tester', 'age': 100})\n\n# or equivalently:\nperson = PersonModel(name='Tester', age=100)\n\n# throws marshmallow.exceptions.ValidationError if invalid\nperson.validate()\n\nperson.dump().data  # {'name': 'Tester', 'age': 100}\n```\n\n### Missing and Default Attributes\n\n```python\nclass PersonModel(Model):\n    name = String(missing='Anonymous')\n    age = Integer(default=0)\n\nperson = PersonModel()\n\nperson.name  # 'Anonymous'\nperson.age  # 0\n```\n\nDefault and missing parameters may be provided as they are to\nMarshmallow Schemas.\n\nConstructing a model is treated like\n\"loading\" data (as in, schema.load(data)).  If attributes are\nmissing and a `missing` configuration was provided, those values\nwill be assigned to the missing attributes.\n\nReading attributes is treated like \"dumping\" data (as in,\nschema.dump(data)), as are calls to model.dump() and dumps().\nIf a value doesn't exist when read or dumped, the default value\nwill be substituted for that attribute.\n\nIn many cases `default` and `missing` can be used interchangeably\nin the context of Models, but there may be cases where their\ndifferent treatment is meaningful.\n\n### Nested Models\n\nNested models are also supported.\n\n```python\nclass ParentModel(PersonModel):\n    child = NestedModel(PersonModel)\n\nparent = ParentModel(name='Tester', age=40, child=dict(name='Child', age=10))\n\nself.assertEqual(parent.child.name, 'Child')\n\nparent.child.name = 'Kid'\n\nself.assertEqual(parent.child.name, 'Kid')\n```\n\nConfiguration\n-------------\n\nMarshmallow Models support the \"class Meta\" configuration method.\n\nAn additional Meta attribute is supported: `strict_constructor`.\n\nIn Marshmallow Schemas, transformation of input data to output data\nwas a single step process.  In Marshmallow Models, it might be\nreasonable for users to instantiate a model with incomplete attributes\nand then fill in the attributes before attempting to validate() or\ndump() the data.\n\nBy default, even for Models with `strict = True`\nthe constructor does not raise exceptions for incomplete attributes.\nIf exceptions are wanted in this case, set `strict_constructor = True`.\n\n\n```python\nclass PersonWithStrictConstructorModel(Model):\n    class Meta:\n        strict_constructor = True\n\n    name = String(required=True)\n    age = Integer(required=True)\n\nwith self.assertRaises(ValidationError):\n    person = PersonWithStrictConstructorModel()\n```\n\n\n",
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        "license": "MIT",
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