===========
validictory
===========
:warning: **:warning: As of 2018 this library is deprecated, please consider using jsonschema (https://pypi.python.org/pypi/jsonschema) instead.**
.. image:: https://travis-ci.org/jamesturk/validictory.svg?branch=master
:target: https://travis-ci.org/jamesturk/validictory
.. image:: https://coveralls.io/repos/jamesturk/validictory/badge.png?branch=master
: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.
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/>`_.
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