An implementation of JSON Schema validation for Python

If you have nox installed (perhaps via pipx install nox or your package manager), running nox in the directory of your source checkout will run jsonschema’s test suite on all of the versions of Python jsonschema supports.

July 23, 2025 - The jsonschema is a Python library used for validating JSON data against a schema. A schema defines the structure and constraints for JSON data, ensuring that the data adheres to specific rules and formats.

May 9, 2024 - import json from pathlib import Path import jsonschema import pytest from rest_framework.test import APIClient from django.contrib.auth.models import User @pytest.mark.django_db def test_get_user(): # Create a user _ = User.objects.create_user(username="test-user", email="test-user@example.com") client = APIClient() response = client.get('/users/1/') assert response.status_code == 200 # Load the JSON schema user_json_schema = Path(".") / "quickstart" / "json-schema" / "user.json" with open(user_json_schema) as schema_file: schema = json.load(schema_file) # Validate the response JSON against the schema jsonschema.validate(response.json(), schema)

Python 3.9 and abovePython 3.10 and above · import json from typing import Optional from pydantic import BaseModel, Field from pydantic.json_schema import GenerateJsonSchema, JsonSchemaValue class MyGenerateJsonSchema(GenerateJsonSchema): def sort( self, value: JsonSchemaValue, parent_key: Optional[str] = None ) -> JsonSchemaValue: """No-op, we don't want to sort schema values at all.""" return value class Bar(BaseModel): c: str b: str a: str = Field(json_schema_extra={'c': 'hi', 'b': 'hello', 'a': 'world'}) json_schema = Bar.model_json_schema(schema_generator=MyGenerateJsonSchema) print(json

August 21, 2020 - Handling complex JSON Schemas in Python In a previous post we looked at how to test your Python API app with JSON Schema. In case you have to deal with complex and nested JSON data, schema …

June 17, 2025 - This tutorial will walk you through each step, from binding a schema to validation. ... Learn how to retrieve an organization and schema. If they do not exist, understand how to create them. ... Add annotations to the folder and validate them against the schema. Attach a file to the folder, add annotations, and validate the file against the schema. ... You have a working installation of the Synapse Python Client.

Support only for Python 3.3 and higher. fastjsonschema implements validation of JSON documents by JSON schema. The library implements JSON schema drafts 04, 06, and 07. The main purpose is to have a really fast implementation. See some numbers: Probably the most popular, jsonschema, can take ...

An implementation of the JSON Schema specification for Python - python-jsonschema/jsonschema

October 20, 2023 - remove name.... json_obj = {"price": 21.47} jsonschema.validate(json_obj, schema) Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment ·

In Python, we can use the JSON Schema library to validate a JSON document against a schema. ... Summary: The jsonschema library validates JSON data against schemas, utilizing keywords like type, properties, and required.

February 16, 2024 - Python offers several libraries and tools for working with JSON schemas, but one of the most popular choices is the "jsonschema" library. In this guide, we will use this library to create JSON schemas in Python.

JSON Schema is defined specifically ... for Python objects which could have possibly existed as JSON. If you stick to the subset of YAML for which this is the case then you shouldn’t have issue, but if you pass schemas (or instances) around whose structure could never have possibly existed as JSON (e.g. a mapping whose keys are not strings), all bets are off. For an example on how to handle that, have a look at the parsers/yaml.py file in the check-jsonschema ...

The Basics: The simplest way to validate an instance under a given schema is to use the validate function. The Validator Protocol: jsonschema defines a protocol that all validator classes adhere to...

JSON Schema - a declarative language for validating JSON documents

JSON Schema implementation and surrounding tooling for Python - Python + JSON Schema

January 11, 2023 - >>> from jsonschema import validate >>> # A sample schema, like what we'd get from json.load() >>> schema = { ... "type" : "object", ... "properties" : { ... "price" : {"type" : "number"}, ... "name" : {"type" : "string"}, ... }, ... } >>> # If no exception is raised by validate(), the instance ...

>>> import python_jsonschema_objects as pjs >>> builder = pjs.ObjectBuilder(examples['Example Schema']) >>> ns = builder.build_classes() >>> Person = ns.ExampleSchema >>> james = Person(firstName="James", lastName="Bond") >>> str(james.lastName) 'Bond' >>> james.lastName += "ing" >>> str(james.lastName) 'Bonding' >>> james.age = 4 >>> james.age - 1 3 >>> 3 + james.age 7 >>> james.lastName / 4 Traceback (most recent call last): ...

January 21, 2025 - from jsonschema import validate >>> # A sample schema, like what we'd get from json.load() >>> schema = { ... "type" : "object", ... "properties" : { ... "price" : {"type" : "number"}, ... "name" : {"type" : "string"}, ... }, ... } >>> # If ...

My schema specifies format validation. Why do invalid instances seem valid?: The format keyword can be a bit of a stumbling block for new users working with JSON Schema. In a schema such as: JSON S...