def test_canonicalises_to_equivalent_fixpoint(schema_strategy, data):
"""Check that an object drawn from an arbitrary schema is valid."""
schema = data.draw(schema_strategy, label="schema")
cc = canonicalish(schema)
assert cc == canonicalish(cc)
instance = data.draw(JSON_STRATEGY | from_schema(cc), label="instance")
assert is_valid(instance, schema) == is_valid(instance, cc)
def test_merge_semantics(data, s1, s2):
assume(canonicalish(s1) != FALSEY and canonicalish(s2) != FALSEY)
combined = merged([s1, s2])
assume(combined is not None)
assume(combined != FALSEY)
note(combined)
ic = data.draw(from_schema(combined), label="combined")
i1 = data.draw(from_schema(s1), label="s1")
i2 = data.draw(from_schema(s2), label="s2")
assert is_valid(ic, s1) and is_valid(ic, s2)
assert is_valid(i1, s2) == is_valid(i1, combined)
assert is_valid(i2, s1) == is_valid(i2, combined)
def test_generated_data_matches_schema(schema_strategy, data):
"""Check that an object drawn from an arbitrary schema is valid."""
schema = data.draw(schema_strategy)
try:
value = data.draw(from_schema(schema), "value from schema")
except InvalidArgument:
reject()
jsonschema.validate(value, schema)
# This checks that our canonicalisation is semantically equivalent.
jsonschema.validate(value, canonicalish(schema))
def test_self_merge_eq_canonicalish(schema):
m = merged([schema, schema])
assert m == canonicalish(schema)
def test_canonicalises_to_expected(schema, expected):
assert canonicalish(schema) == expected, (schema, canonicalish(schema),
expected)
def test_canonicalises_to_empty(schema):
assert canonicalish(schema) == {"not": {}}, (schema, canonicalish(schema))