Payment JSON Schema (draft-07)
Draft-07 JSON Schema for payment amount/currency validation in fintech API tests.
{
"$schema": "http://json-schema.org/draft-07/schema#",
"type": "object",
"required": [
"amount",
"currency"
],
"properties": {
"amount": {
"type": "number",
"minimum": 0.01
},
"currency": {
"type": "string",
"minLength": 3
}
}
}
Specifications
- Spec
- JSON Schema draft-07
- Domain
- fintech
Testing contract
Expected to pass- Scenario
- Exercise Payment JSON Schema (draft-07) in its schema workflow. Draft-07 JSON Schema for payment amount/currency validation in fintech API tests.
- Expected result
- top-level keys are $schema, type, required, properties; array lengths: required=2; selected values: {"type": "object"}. Declared feature checks: spec=JSON Schema draft-07; domain=fintech.
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
“Payment JSON Schema (draft-07)” is a deterministic Novus Examples fixture for Schema / OpenAPI testing. Valid and intentionally invalid OpenAPI/JSON Schema documents plus request/response examples for schema validators and API tooling.
Documented properties for this file: JSON · 308 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("payment.schema.json") as f:
data = json.load(f)
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