Huge News!Announcing our $40M Series B led by Abstract Ventures.Learn More
Socket
Sign inDemoInstall
Socket

validictory

Package Overview
Dependencies
Maintainers
2
Alerts
File Explorer

Advanced tools

Socket logo

Install Socket

Detect and block malicious and high-risk dependencies

Install

validictory

general purpose python data validator

  • 1.1.3
  • PyPI
  • Socket score

Maintainers
2

=========== 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/>_.

FAQs


Did you know?

Socket

Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.

Install

Related posts

SocketSocket SOC 2 Logo

Product

  • Package Alerts
  • Integrations
  • Docs
  • Pricing
  • FAQ
  • Roadmap
  • Changelog

Packages

npm

Stay in touch

Get open source security insights delivered straight into your inbox.


  • Terms
  • Privacy
  • Security

Made with ⚡️ by Socket Inc