A platform agnostic (web, flutter or vm) Dart library for validating JSON instances against JSON Schemas (multi-version support with latest of Draft 7).

1. Ensure you have latest stable Dart installed.
2. make pubget
3. make format
4. make analyze
5. make test-with-serve-remotes

1. make serve-remotes (in a separate terminal tab - HTTP fixtures need to be served for tests to pass)
2. make test or dart test -n <YOUR TEST>
3. SIGINT your make serve-remotes tab or run make stop-serve-remotes

Note: For convenience, make stop-serve-remotes will be run as a prerequisite before make test-with-serve-remotes and make serve-remotes

1. make gen-fixtures Generates Dart source files that contain the JSON-Schema-Test-Suite tests and fixtures for use in cross-platform testing that doesn't require dart:io to read the files on disk.
2. Commit the results of generation, if any.

Note: CI runs make gen-fixtures --check to ensure these are up-to-date on each

The simplest way to create a schema is to pass JSON data directly to JsonSchema.create with a JSON String, or decoded JSON via Dart Map or bool.

After creating any schema, JSON instances can be validated by calling .validate(instance) on that schema. By default, instances are expected to be pre-parsed JSON as native dart primitives (Map, List, String, bool, num, int). You can also optionally parse at validation time by passing in a string and setting parseJson: schema.validate('{ "name": "any JSON object"}', parseJson: true).

Note: Creating JsonSchemas synchronously implies access to all $refs within the root schema. If you don't have access to all this data at the time of the construction, see "Asynchronous Creation" examples below.

import 'package:json_schema/json_schema.dart';

main() {
  /// Define schema in a Dart [Map] or use a JSON [String].
  final mustBeIntegerSchemaMap = {"type": "integer"};

  // Create some examples to validate against the schema.
  final n = 3;
  final decimals = 3.14;
  final str = 'hi';

  // Construct the schema from the schema map or JSON string.
  final schema = JsonSchema.create(mustBeIntegerSchemaMap);

  print('$n => ${schema.validate(n)}'); // true
  print('$decimals => ${schema.validate(decimals)}'); // false
  print('$str => ${schema.validate(str)}'); // false
}

Or see json_schema/example/readme/synchronous_creation/self_contained.dart

And run dart run ./example/readme/synchronous_creation/self_contained.dart

If you want to create JsonSchemas synchronously, and you have $refs that cannot be resolved within the root schema, but you have a cache of those $ref'd schemas locally, you can write a RefProvider to get them during schema evaluation.

See json_schema/example/readme/synchronous_creation/local_ref_cache.dart

Or run dart run ./example/readme/synchronous_creation/local_ref_cache.dart

If you have schemas that have nested $refs that are HTTP URIs that are publicly accessible, you can use Future<JsonSchema> JsonSchema.createAsync and the references will be fetched as needed during evaluation. You can also use JsonSchema.createFromUrl if you want to fetch the root schema remotely as well (see next example).

See json_schema/example/readme/asynchronous_creation/remote_http_refs.dart

Or run dart run ./example/readme/asynchronous_creation/remote_http_refs.dart

You can also create a schema directly from a publicly accessible URL or File.

See json_schema/example/readme/asynchronous_creation/from_url.dart

Or run dart run ./example/readme/asynchronous_creation/from_url.dart

See json_schema/example/readme/asynchronous_creation/from_file.dart

Or run dart run ./example/readme/asynchronous_creation/from_file.dart

If you have nested $refs that are either non-HTTP URIs or non-publicly-accessible HTTP $refs, you can supply an async RefProvider to createAsync, and perform any custom logic you need.

See json_schema/example/readme/asynchronous_creation/remote_ref_cache.dart

Or run dart run ./example/readme/asynchronous_creation/remote_ref_cache.dart

Schema information can be used for validation; but it can also be a valuable source of information about the structure of data. The JsonSchema class fully parses the schema first, which itself must be valid on all paths within the schema. Accessors are provided for all specified keywords of the JSON Schema specification associated with a schema, so tools can use it to create rich views of the data, like forms or diagrams.