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        "author": "Stefan W",
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        "description": "Schema validation for Python data structures\n============================================\n\nBasic validation for Python data structures in a mostly declarative\nform (there is an escape hatch in \"extraValidation\" callables).\n\nValidation errors are reported as both a path within the data\nstructure (sequence of indices or keys) and a descriptive message\n(string).\n\nTypical usage::\n\n    data = json.load(some_file) # or pickle, or ...\n    errors = dataschema.Validator(my_schema).validate(data)\n    if errors:\n        for path, message in errors:\n            # Report error `message` at path `path`.\n    else:\n        # Any data access or application-specific validation can now\n        # rely on properties of my_schema (e.g. minimum number of\n        # elements in a sequence, data types of elements, presence of\n        # certain keys in a dict, etc.).\n\nSee the unit tests for schema examples.\n\nThere are a few limitations (only string keys for any dictionaries in\ndata) and a more fully Pythonic validator might focus on interfaces\nand abstract base classes over concrete types.  However, dataschema is\na great improvement over ad hoc validation code for many uses today.",
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