Implements JSON Schema, JSON Pointer and JSON Reference.
Project description
This library implements several JSON specs, like JSON Schema, JSON Reference and JSON Pointer:
It works on python 2.7, python 3.3 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 cli commands like:
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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