User JSON Schema (draft 2020-12)
Draft 2020-12 JSON Schema for a user object with email format and role enum — paired with valid/invalid instances.
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"$id": "https://example.com/schemas/user.json",
"title": "User",
"type": "object",
"required": [
"user_id",
"email",
"active"
],
"additionalProperties": false,
"properties": {
"user_id": {
"type": "integer",
"minimum": 1
},
"email": {
"type": "string",
"format": "email"
},
"active": {
"type": "boolean"
},
"role": {
"type": "string",
"enum": [
"admin",
"member",
"guest"
]
}
}
}
Specifications
- Spec
- JSON Schema draft 2020-12
- Required
- user_id, email, active
- Seed
- 42042
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 JSON Schema (draft 2020-12)” is a deterministic Novus Examples fixture for Schema / OpenAPI testing, JSON parsing. Valid and intentionally invalid OpenAPI/JSON Schema documents plus request/response examples for schema validators and API tooling.
Documented properties for this file: seed 42042. 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.schema.json") as f:
data = json.load(f)
print(type(data), len(data))Related files
- jsonJSON Schema Edge — Additional Properties FalseMinimal JSON Schema SAMPLE focusing on additional properties false constraints.
- jsonJSON Schema Edge — Array Unique ItemsMinimal JSON Schema SAMPLE focusing on array unique items constraints.
- jsonJSON Schema Edge — Dependent RequiredMinimal JSON Schema SAMPLE focusing on dependent required constraints.
- jsonJSON Schema Edge — Enum CurrencyMinimal JSON Schema SAMPLE focusing on enum currency constraints.
- jsonJSON Schema Edge — Format Uri EmailMinimal JSON Schema SAMPLE focusing on format uri email constraints.
- jsonJSON Schema Edge — Nullable OptionalMinimal JSON Schema SAMPLE focusing on nullable optional constraints.
Generated by generation/data_wave_f.py. Free for any use, no attribution required — license.