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import copy
import pickle
import pytest
from typing_extensions import ( # noqa: UP035 (https://github.com/astral-sh/ruff/pull/18476)
get_args,
get_origin,
get_type_hints,
)
from typing_inspection import typing_objects
from typing_inspection.introspection import UNKNOWN, AnnotationSource, inspect_annotation
from pydantic_core import CoreConfig, CoreSchema, CoreSchemaType, PydanticUndefined, core_schema
from pydantic_core._pydantic_core import (
SchemaError,
SchemaValidator,
ValidationError,
__version__,
build_info,
build_profile,
)
@pytest.mark.parametrize('obj', [ValidationError, SchemaValidator, SchemaError])
def test_module(obj):
assert obj.__module__ == 'pydantic_core._pydantic_core'
def test_version():
assert isinstance(__version__, str)
assert '.' in __version__
def test_build_profile():
assert build_profile in ('debug', 'release')
def test_build_info():
assert isinstance(build_info, str)
def test_schema_error():
err = SchemaError('test')
assert isinstance(err, Exception)
assert str(err) == 'test'
assert repr(err) == 'SchemaError("test")'
def test_validation_error(pydantic_version):
v = SchemaValidator(core_schema.int_schema())
with pytest.raises(ValidationError) as exc_info:
v.validate_python(1.5)
assert exc_info.value.title == 'int'
assert exc_info.value.error_count() == 1
assert (
exc_info.value.errors(include_url=False)
== exc_info.value.errors(include_url=False, include_context=False)
== [
{
'type': 'int_from_float',
'loc': (),
'msg': 'Input should be a valid integer, got a number with a fractional part',
'input': 1.5,
}
]
)
# insert_assert(exc_info.value.errors())
assert exc_info.value.errors() == [
{
'type': 'int_from_float',
'loc': (),
'msg': 'Input should be a valid integer, got a number with a fractional part',
'input': 1.5,
'url': f'https://errors.pydantic.dev/{pydantic_version}/v/int_from_float',
}
]
def test_validation_error_include_context():
v = SchemaValidator(core_schema.list_schema(max_length=2))
with pytest.raises(ValidationError) as exc_info:
v.validate_python([1, 2, 3])
assert exc_info.value.title == 'list[any]'
assert exc_info.value.error_count() == 1
# insert_assert(exc_info.value.errors(include_url=False))
assert exc_info.value.errors(include_url=False) == [
{
'type': 'too_long',
'loc': (),
'msg': 'List should have at most 2 items after validation, not 3',
'input': [1, 2, 3],
'ctx': {'field_type': 'List', 'max_length': 2, 'actual_length': 3},
}
]
# insert_assert(exc_info.value.errors(include_url=False, include_context=False))
assert exc_info.value.errors(include_url=False, include_context=False) == [
{
'type': 'too_long',
'loc': (),
'msg': 'List should have at most 2 items after validation, not 3',
'input': [1, 2, 3],
}
]
def test_custom_title():
v = SchemaValidator(core_schema.int_schema(), config=CoreConfig(title='MyInt'))
with pytest.raises(ValidationError) as exc_info:
v.validate_python(1.5)
assert exc_info.value.title == 'MyInt'
def test_validation_error_multiple(pydantic_version):
class MyModel:
# this is not required, but it avoids `__pydantic_fields_set__` being included in `__dict__`
__slots__ = '__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__'
field_a: str
field_b: int
v = SchemaValidator(
core_schema.model_schema(
cls=MyModel,
schema=core_schema.model_fields_schema(
fields={
'x': core_schema.model_field(schema=core_schema.float_schema()),
'y': core_schema.model_field(schema=core_schema.int_schema()),
}
),
)
)
with pytest.raises(ValidationError) as exc_info:
v.validate_python({'x': 'x' * 60, 'y': 'y'})
assert exc_info.value.title == 'MyModel'
assert exc_info.value.error_count() == 2
assert exc_info.value.errors(include_url=False) == [
{
'type': 'float_parsing',
'loc': ('x',),
'msg': 'Input should be a valid number, unable to parse string as a number',
'input': 'x' * 60,
},
{
'type': 'int_parsing',
'loc': ('y',),
'msg': 'Input should be a valid integer, unable to parse string as an integer',
'input': 'y',
},
]
assert repr(exc_info.value) == (
'2 validation errors for MyModel\n'
'x\n'
' Input should be a valid number, unable to parse string as a number '
"[type=float_parsing, input_value='xxxxxxxxxxxxxxxxxxxxxxxx...xxxxxxxxxxxxxxxxxxxxxxx', input_type=str]\n"
f' For further information visit https://errors.pydantic.dev/{pydantic_version}/v/float_parsing\n'
'y\n'
' Input should be a valid integer, unable to parse string as an integer '
"[type=int_parsing, input_value='y', input_type=str]\n"
f' For further information visit https://errors.pydantic.dev/{pydantic_version}/v/int_parsing'
)
def test_core_schema_type_literal():
def get_type_value(schema_typeddict) -> str:
annotation = get_type_hints(schema_typeddict, include_extras=True)['type']
inspected_ann = inspect_annotation(annotation, annotation_source=AnnotationSource.TYPED_DICT)
annotation = inspected_ann.type
assert annotation is not UNKNOWN
assert typing_objects.is_literal(get_origin(annotation)), (
f"The 'type' key of core schemas must be a Literal form, got {get_origin(annotation)}"
)
args = get_args(annotation)
assert len(args) == 1, (
f"The 'type' key of core schemas must be a Literal form with a single element, got {len(args)} elements"
)
type_ = args[0]
assert isinstance(type_, str), (
f"The 'type' key of core schemas must be a Literal form with a single string element, got element of type {type(type_)}"
)
return type_
schema_types = (get_type_value(x) for x in CoreSchema.__args__)
schema_types = tuple(dict.fromkeys(schema_types)) # remove duplicates while preserving order
if get_args(CoreSchemaType) != schema_types:
literal = ''.join(f'\n {e!r},' for e in schema_types)
print(
f'python code (near end of python/pydantic_core/core_schema.py):\n\nCoreSchemaType = Literal[{literal}\n]'
)
pytest.fail('core_schema.CoreSchemaType needs to be updated')
def test_undefined():
with pytest.raises(NotImplementedError, match='UndefinedType'):
PydanticUndefined.__class__()
undefined_copy = copy.copy(PydanticUndefined)
undefined_deepcopy = copy.deepcopy(PydanticUndefined)
assert undefined_copy is PydanticUndefined
assert undefined_deepcopy is PydanticUndefined
assert pickle.loads(pickle.dumps(PydanticUndefined)) is PydanticUndefined
def test_unicode_error_input_repr() -> None:
"""https://github.com/pydantic/pydantic/issues/6448"""
validator = SchemaValidator(core_schema.int_schema())
danger_str = 'ÿ' * 1000
expected = "1 validation error for int\n Input should be a valid integer, unable to parse string as an integer [type=int_parsing, input_value='ÿÿÿÿÿÿÿÿÿÿÿÿ...ÿÿÿÿÿÿÿÿÿÿÿ', input_type=str]"
with pytest.raises(ValidationError) as exc_info:
validator.validate_python(danger_str)
actual = repr(exc_info.value).split('For further information visit ')[0].strip()
assert expected == actual
def test_core_schema_import_field_validation_info():
with pytest.warns(DeprecationWarning, match='`FieldValidationInfo` is deprecated, use `ValidationInfo` instead.'):
core_schema.FieldValidationInfo
def test_core_schema_import_missing():
with pytest.raises(AttributeError, match="module 'pydantic_core' has no attribute 'foobar'"):
core_schema.foobar
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