===========
validictory

:warning: :warning: As of 2018 this library is deprecated, please consider using jsonschema (https://pypi.python.org/pypi/jsonschema) instead.

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A general purpose Python data validator.

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("something", {"type":"string"})

Parsing a more complex JSON document::

>>> import json
>>> import validictory
>>>
>>> data = json.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("something", {"type":"string","minLength":15})
... except ValueError, error:
...     print(error)
...
Length of value 'something' 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/>_.

Dependencies of validictory (2).
Dependency	Optional
pytest	true
pytest-cov	true

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validictory

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