from jsonschema import validate
import json
from hypothesis import given, settings
from hyposchema.hypo_schema import generate_from_schema
EXAMPLE_JSON_SCHEMA= {
"title": "Example Schema",
"type": "object",
"properties": {
"firstName": {
"type": "string"
},
"lastName": {
"type": "string"
},
"age": {
"description": "Age in years",
"type": "integer",
"minimum": 0
},
"listOfElements": {
"type": "array",
"items": {
"type": "number"
}
},
"listOfRandom": {
"min": 4,
"max": 10,
"type": "array"
},
"type": {
"type": "string",
"enum": ["string", "int", "bool"]
},
"nestedMap": {
"type": "object",
"properties": {
"firstProp": {
"type": "string"
}
},
"required": ["firstProp"]
}
},
"required": ["firstName", "lastName", "nestedMap", "listOfElements"]
}
@given(generate_from_schema(EXAMPLE_JSON_SCHEMA))
@settings(max_examples=10)
def test_basic_map(example_data):
print(json.dumps(example_data, indent=4))
validate(example_data, EXAMPLE_JSON_SCHEMA)
test_basic_map()Better using a simpler schema than json-schema, like skema:
import skema
from jsonschema import validate
import json
from hypothesis import given, settings
from hyposchema.hypo_schema import generate_from_schema
EXAMPLE_JSON_SCHEMA=skema.to_jsonschema("""
Root: EventA & EventB
EventA:
type: Str
fields:
args: [
name: Str
type: Str | Any
]
...
EventB:
timestamp: Any
sentBy: Str
madeBy: "me" | "you"
...
""", resolve=True)
@given(generate_from_schema(EXAMPLE_JSON_SCHEMA))
@settings(max_examples=10)
def test_basic_map( example_data):
print(json.dumps(example_data, indent=4))
validate(example_data, EXAMPLE_JSON_SCHEMA)
test_basic_map()