User Instance — Invalid (5 violations)
User JSON deliberately violating the schema five ways — negative case for validator error reporting.
{
"user_id": 0,
"email": "not-an-email",
"active": "yes",
"role": "superuser",
"extra": true
}
Specifications
- Conforms To
- user.schema.json
- Valid
- false
- Violations
- 5
What is a .json file?
JSON (JavaScript Object Notation) is a lightweight, text-based data-interchange format representing objects, arrays, strings, numbers, booleans, and null. It is language-independent, human-readable, and the dominant format for web APIs and configuration. It requires a single well-formed root value.
How to use this file
Use an example JSON file to test parsers and serializers, schema validation, Unicode and number-precision handling, and API request or response processing.
How to use this file for testing
“User Instance — Invalid (5 violations)” is a deterministic Novus Examples fixture for Schema / OpenAPI testing, Error handling. Valid and intentionally invalid OpenAPI/JSON Schema documents plus request/response examples for schema validators and API tooling.
Documented properties for this file: intentionally invalid. Compare results against paired or grouped companions on this page when present (clean↔damaged, searchable↔scanned, or format twins) so scores stay reproducible across runs.
Download the file once, keep the path stable in CI or local scripts, and treat the spec table as the contract: dimensions, seeds, field lists, and roles are intentional. Corrupt or invalid samples are labelled as such — expect parsers to fail loudly rather than silently accept them.
Data fixtures document their exact quirks — delimiters, encodings, null handling, schema, and row counts — in the spec table. Point your parser or importer at the file and assert it handles the documented edge cases; clean and deliberately-messy siblings make before/after diffs straightforward.
Valid and intentionally invalid siblings are labelled in title and description. Assert parsers accept the valid twin and fail loudly on the invalid one; for time series, check DST gaps and duplicate keys against the spec table.
Code examples
import json
with open("user-invalid.json") as f:
data = json.load(f)
print(type(data), len(data))Related files
- jsonInvalid JSON Schema — Json Schema Bad RefIntentionally invalid JSON Schema (json-schema-bad-ref) for negative validator tests.
- jsonInvalid JSON Schema — Json Schema Empty ObjectIntentionally invalid JSON Schema (json-schema-empty-object) for negative validator tests.
- jsonInvalid JSON Schema — Json Schema Missing TypeIntentionally invalid JSON Schema (json-schema-missing-type) for negative validator tests.
- jsonInvalid OpenAPI — Openapi Broken RefOpenAPI with a response schema $ref pointing at a missing component — tests broken-reference detection.
- jsonInvalid OpenAPI — Openapi Missing PathsOpenAPI document with paths set to null — intentionally invalid for negative schema tests.
- jsonInvalid OpenAPI — Openapi Wrong VersionOpenAPI with an unsupported openapi version string — negative case for version validators.
Generated by generation/data_wave_f.py. Free for any use, no attribution required — license.