Metadata-Version: 1.1
Name: validictory
Version: 1.0.2
Summary: general purpose python data validator
Home-page: http://github.com/jamesturk/validictory
Author: James Turk
Author-email: james.p.turk@gmail.com
License: MIT License
Description: ===========
        validictory
        ===========
        
        .. image:: https://travis-ci.org/jamesturk/validictory.svg?branch=master
            :target: https://travis-ci.org/jamesturk/validictory
        
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            :target: https://coveralls.io/r/jamesturk/validictory
        
        .. image:: https://img.shields.io/pypi/v/validictory.svg
            :target: https://pypi.python.org/pypi/validictory
        
        .. image:: https://readthedocs.org/projects/validictory/badge/?version=latest
            :target: https://readthedocs.org/projects/validictory/?badge=latest
            :alt: Documentation Status
        
        
        A general purpose Python data validator.
        
        Works with Python 2.7 and Python 3.3+
        
        Schema format based on JSON Schema Proposal (http://json-schema.org)
        
        Contains code derived from jsonschema, by Ian Lewis and Yusuke Muraoka.
        
        Usage
        =====
        
        JSON documents and schema must first be loaded into a Python dictionary type
        before it can be validated.
        
        Parsing a simple JSON document::
        
            >>> import validictory
            >>>
            >>> validictory.validate("simplejson", {"type":"string"})
        
        Parsing a more complex JSON document::
        
            >>> import simplejson
            >>> import validictory
            >>>
            >>> data = simplejson.loads('["foo", {"bar":["baz", null, 1.0, 2]}]')
            >>> schema = {
            ...   "type":"array",
            ...   "items":[
            ...     {"type":"string"},
            ...     {"type":"object",
            ...      "properties":{
            ...        "bar":{
            ...          "items":[
            ...            {"type":"string"},
            ...            {"type":"any"},
            ...            {"type":"number"},
            ...            {"type":"integer"}
            ...          ]
            ...        }
            ...      }
            ...    }
            ...   ]
            ... }
            >>> validictory.validate(data,schema)
        
        Catch ValueErrors to handle validation issues::
        
            >>> import validictory
            >>>
            >>> try:
            ...     validictory.validate("simplejson", {"type":"string","minLength":15})
            ... except ValueError, error:
            ...     print error
            ...
            Length of value 'simplejson' for field '_data' must be greater than or equal to 15
        
        You can read more in the official documentation at `Read the Docs <http://validictory.readthedocs.org/en/latest/>`_.
        
Platform: any
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: BSD License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Topic :: Software Development :: Libraries :: Python Modules
