json234 B

JSON Schema Edge — Pattern Sku

Minimal JSON Schema SAMPLE focusing on pattern sku constraints.

Schema / OpenAPI testing Schema validation JSON parsing

Preview — first 14 linesjson

{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "type": "object",
  "properties": {
    "sku": {
      "type": "string",
      "pattern": "^SKU-[A-Z0-9]{4,12}$"
    }
  },
  "required": [
    "sku"
  ]
}

Specifications

Draft: 2020-12
Wave: I
Role: schema-edge

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 Edge — Pattern Sku” is a deterministic Novus Examples fixture for Schema / OpenAPI testing, Schema validation, 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: schema-edge. 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("pattern-sku.json") as f:
    data = json.load(f)
print(type(data), len(data))

Generated by generation/pad_wave_i.py. Free for any use, no attribution required — license.

Specifications

What is a .json file?

How to use this file

How to use this file for testing

Code examples

Related files