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Implements JSON Schema, JSON Pointer and JSON Reference.

Project description

https://badge.fury.io/py/json-spec.png https://travis-ci.org/johnnoone/json-spec.png?branch=master

This library implements several JSON specs, like JSON Schema, JSON Reference and JSON Pointer:

  • It works on python 3.6 and above

  • It is release under the BSD license

Installation

This library has only weak dependencies. You can simply use pip:

$ pip install json-spec

Regading you needs, you can install more features. For example, this command will enable colorated messages:

$ pip install json-spec[cli]

This one will enable ip format for json schema:

$ pip install json-spec[ip]

CLI Usage

This module expose 2 cli commands.

json-extract will extract parts of your json document:

$ json-extract '#/foo/1' --document-json='{"foo": ["bar", "baz"]}'
$ echo '{"foo": ["bar", "baz"]}' | json-extract '#/foo/1'
$ json-extract '#/foo/1' --document-file=doc.json
$ json-extract '#/foo/1' < doc.json

json-validate will validate your document against a schema:

$ json-validate --schema-file=schema.json --document-json='{"foo": ["bar", "baz"]}'
$ echo '{"foo": ["bar", "baz"]}' | json-validate --schema-file=schema.json
$ json-validate --schema-file=schema.json --document-file=doc.json
$ json-validate --schema-file=schema.json < doc.json

Library usage

Let say you want to fetch / validate JSON like objects in you python scripts.

You can extract member of an object with JSON Pointer:

from jsonspec.pointer import extract

obj = {
    'foo': ['bar', 'baz', 'quux']
}
assert 'baz' == extract(obj, '/foo/1')

You can resolve member of any object with JSON Reference:

from jsonspec.reference import resolve

obj = {
    'foo': ['bar', 'baz', {
        '$ref': '#/sub'
    }],
    'sub': 'quux'
}

assert 'quux' == resolve(obj, '#/foo/2')

You can describe you data with JSON Schema:

from jsonspec.validators import load

# data will validate against this schema
validator = load({
    'title': 'Example Schema',
    'type': 'object',
    'properties': {
        'age': {
            'description': 'Age in years',
            'minimum': 0,
            'type': 'integer'
        },
        'firstName': {
            'type': 'string'
        },
        'lastName': {
            'type': 'string'
        }
    },
    'required': [
        'firstName',
        'lastName'
    ]
})

# validate this data
validator.validate({
    'firstName': 'John',
    'lastName': 'Noone',
    'age': 33,
})

Other examples can be found in the documentation or in the tests.

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