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        "author": "Adrian Kuhn",
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        "description": "A little language for schema-enforced models\n============================================\n\nFame is a framework for metamodelling in Python.\n\n-  Entities are described by models\n-  Models are described by metamodels\n-  Models have fields, derived fields and constraints\n-  Entities can have custom fields\n-  Entities can be created even if data is invalid\n-  There are functions to validate and get error messages\n-  Validation checks presence and type of fields\n-  Validation checks all constraints\n-  Derived fields are memoized\n\nExample\n\n::\n\n    class Experiment(Model):\n\n        @schema\n        def metamodel(self, m):\n            m.field('name', str)\n            m.field('subject', options(\n                'user',\n                'visitor',\n                'email',\n                'listing',\n                'market'\n            ))\n            m.field('treatments', array(str))\n            m.field('percent_exposed', int, default=100)\n            m.field('design', nullable(regexp('^https?')))\n\n        @derived_field\n        def is_miscellanous(self):\n            return self.subject not in ['user', 'visitor']\n\n        @constraint(\"expected percent_exposed to not exceed 100, got {}\")\n        def constraint(self):\n            if self.percent_exposed > 100:\n                return self.percent_exposed\n\nConventions\n\n-  Define metamodel function first\n-  Then define derived field functions\n-  Then define all the constraint functions\n-  Constraint functions are all named \u201cconstraint\u201d, that is intentional\n\nInstallation\n------------\n\nTo install this package, run\n\n::\n\n    pip install fame\n\nContributing\n------------\n\nBug reports and pull requests are welcome on github at,\nhttps://github.com/akuhn/py-fame",
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