JSON Schema — Optional Properties without a Type Constraint
Omitting type is legal JSON Schema. The x property has an empty subschema, x is optional, and non-object instances are not rejected by properties.
{
"title": "Bad",
"properties": {
"x": {}
}
}
Specifications
- Valid
- true
- Issue
- json-schema-missing-type
Testing contract
Expected to pass- Scenario
- Validate this schema and apply it to object and non-object instances.
- Expected result
- Omitting type is legal JSON Schema. The x property has an empty subschema, x is optional, and non-object instances are not rejected by properties.
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
“JSON Schema — Optional Properties without a Type Constraint” 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: JSON · 62 bytes. 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("json-schema-missing-type.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 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.
- jsonJSON Schema — Empty Schema Accepts Any InstanceThe empty schema is valid and accepts every instance. The old invalid label was incorrect; no type or required-property constraint exists.
- jsonPayment Instance — InvalidInvalid payment JSON (negative amount, short currency) for schema error reporting tests.
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