def test_between_3_and_50_characters(self):
f = Field(..., min_length=3, max_length=50)
field = ModelField(
name="name",
type_=str,
class_validators={},
field_info=f,
model_config=BaseConfig,
)
long_text = "Lorem Ipsum is simply dummy text of\
the printing and typesetting industry. "
with pytest.raises(ValueError):
PartialUser.between_3_and_50_characters("He", field=field)
with pytest.raises(ValueError):
PartialUser.between_3_and_50_characters(
long_text,
field=field,
)
assert PartialUser.between_3_and_50_characters("Hello") == "Hello"
async def serialize_response(
*,
field: ModelField = None,
response: Response,
include: Union[SetIntStr, DictIntStrAny] = None,
exclude: Union[SetIntStr, DictIntStrAny] = set(),
by_alias: bool = True,
exclude_unset: bool = False,
is_coroutine: bool = True,
) -> Any:
if field:
errors = []
if exclude_unset and isinstance(response, BaseModel):
if PYDANTIC_1:
response = response.dict(exclude_unset=exclude_unset)
else:
response = response.dict(
skip_defaults=exclude_unset) # pragma: nocover
if is_coroutine:
value, errors_ = field.validate(response, {}, loc=("response", ))
else:
value, errors_ = await run_in_threadpool(field.validate,
response, {},
loc=("response", ))
if isinstance(errors_, ErrorWrapper):
errors.append(errors_)
elif isinstance(errors_, list):
errors.extend(errors_)
if errors:
raise ValidationError(errors, field.type_)
return jsonable_encoder(
value,
include=include,
exclude=exclude,
by_alias=by_alias,
exclude_unset=exclude_unset,
)
else:
return jsonable_encoder(response)
def create_pydantic_field(
field_name: str, model: Type["Model"], model_field: Type["ManyToManyField"]
) -> None:
"""
Registers pydantic field on through model that leads to passed model
and is registered as field_name passed.
Through model is fetched from through attributed on passed model_field.
:param field_name: field name to register
:type field_name: str
:param model: type of field to register
:type model: Model class
:param model_field: relation field from which through model is extracted
:type model_field: ManyToManyField class
"""
model_field.through.__fields__[field_name] = ModelField(
name=field_name,
type_=model,
model_config=model.__config__,
required=False,
class_validators={},
)
def infer_request_from_annotations(func: Callable) -> Optional[Type[BaseModel]]:
"""Infer an OpenAPI request body from function annotations.
The annotations are converted to a `BaseModel` and schema is extracted from
it.
Args:
func: The function whose annotations are to be inferred.
Returns:
A `BaseModel` generated from the annotation's return value
"""
annot = {x: y for x, y in func.__annotations__.items() if x != "return"}
if annot:
class Annot(BaseModel):
pass
for x, y in annot.items():
Annot.__fields__[x] = ModelField(name=x, type_=y, class_validators={},
model_config=BaseConfig,
required=True)
return Annot
else:
return None
async def serialize_response(
*,
field: ModelField = None,
response_content: Any,
include: Union[SetIntStr, DictIntStrAny] = None,
exclude: Union[SetIntStr, DictIntStrAny] = set(),
by_alias: bool = True,
exclude_unset: bool = False,
is_coroutine: bool = True,
) -> Any:
if field:
errors = []
response_content = _prepare_response_content(
response_content, by_alias=by_alias, exclude_unset=exclude_unset
)
if is_coroutine:
value, errors_ = field.validate(response_content, {}, loc=("response",))
else:
value, errors_ = await run_in_threadpool(
field.validate, response_content, {}, loc=("response",)
)
if isinstance(errors_, ErrorWrapper):
errors.append(errors_)
elif isinstance(errors_, list):
errors.extend(errors_)
if errors:
raise ValidationError(errors, field.type_)
return jsonable_encoder(
value,
include=include,
exclude=exclude,
by_alias=by_alias,
exclude_unset=exclude_unset,
)
else:
return jsonable_encoder(response_content)
def _check_param(
cls, dependent: Dependent, name: str, param: inspect.Parameter
) -> Optional["EventParam"]:
from nonebot.adapters import Event
if param.default == param.empty:
if generic_check_issubclass(param.annotation, Event):
if param.annotation is not Event:
dependent.pre_checkers.append(
_EventChecker(
Required,
field=ModelField(
name=name,
type_=param.annotation,
class_validators=None,
model_config=CustomConfig,
default=None,
required=True,
),
)
)
return cls(Required)
elif param.annotation == param.empty and name == "event":
return cls(Required)
def create_cloned_field(field: ModelField) -> ModelField:
original_type = field.type_
if is_dataclass(original_type) and hasattr(original_type, "__pydantic_model__"):
original_type = original_type.__pydantic_model__ # type: ignore
use_type = original_type
if lenient_issubclass(original_type, BaseModel):
original_type = cast(Type[BaseModel], original_type)
use_type = create_model(
original_type.__name__, __config__=original_type.__config__
)
for f in original_type.__fields__.values():
use_type.__fields__[f.name] = f
use_type.__validators__ = original_type.__validators__
if PYDANTIC_1:
new_field = ModelField(
name=field.name,
type_=use_type,
class_validators={},
default=None,
required=False,
model_config=BaseConfig,
field_info=FieldInfo(None),
)
else: # pragma: nocover
new_field = ModelField( # type: ignore
name=field.name,
type_=use_type,
class_validators={},
default=None,
required=False,
model_config=BaseConfig,
schema=FieldInfo(None),
)
new_field.has_alias = field.has_alias
new_field.alias = field.alias
new_field.class_validators = field.class_validators
new_field.default = field.default
new_field.required = field.required
new_field.model_config = field.model_config
if PYDANTIC_1:
new_field.field_info = field.field_info
else: # pragma: nocover
new_field.schema = field.schema # type: ignore
new_field.allow_none = field.allow_none
new_field.validate_always = field.validate_always
if field.sub_fields:
new_field.sub_fields = [
create_cloned_field(sub_field) for sub_field in field.sub_fields
]
if field.key_field:
new_field.key_field = create_cloned_field(field.key_field)
new_field.validators = field.validators
if PYDANTIC_1:
new_field.pre_validators = field.pre_validators
new_field.post_validators = field.post_validators
else: # pragma: nocover
new_field.whole_pre_validators = field.whole_pre_validators # type: ignore
new_field.whole_post_validators = field.whole_post_validators # type: ignore
new_field.parse_json = field.parse_json
new_field.shape = field.shape
try:
new_field.populate_validators()
except AttributeError: # pragma: nocover
# TODO: remove when removing support for Pydantic < 1.0.0
new_field._populate_validators() # type: ignore
return new_field
def get_param_field(
*,
param: inspect.Parameter,
param_name: str,
default_field_info: Type[params.Param] = params.Param,
force_type: params.ParamTypes = None,
ignore_default: bool = False,
) -> ModelField:
default_value = Required
had_schema = False
if not param.default == param.empty and ignore_default is False:
default_value = param.default
if isinstance(default_value, FieldInfo):
had_schema = True
field_info = default_value
default_value = field_info.default
if (isinstance(field_info, params.Param)
and getattr(field_info, "in_", None) is None):
field_info.in_ = default_field_info.in_
if force_type:
field_info.in_ = force_type # type: ignore
else:
field_info = default_field_info(default_value)
required = default_value == Required
annotation: Any = Any
if not param.annotation == param.empty:
annotation = param.annotation
annotation = get_annotation_from_field_info(annotation, field_info,
param_name)
if not field_info.alias and getattr(field_info, "convert_underscores",
None):
alias = param.name.replace("_", "-")
else:
alias = field_info.alias or param.name
if PYDANTIC_1:
field = ModelField(
name=param.name,
type_=annotation,
default=None if required else default_value,
alias=alias,
required=required,
model_config=BaseConfig,
class_validators={},
field_info=field_info,
)
# TODO: remove when removing support for Pydantic < 1.2.0
field.required = required
else: # pragma: nocover
field = ModelField( # type: ignore
name=param.name,
type_=annotation,
default=None if required else default_value,
alias=alias,
required=required,
model_config=BaseConfig,
class_validators={},
schema=field_info,
)
field.required = required
if not had_schema and not is_scalar_field(field=field):
if PYDANTIC_1:
field.field_info = params.Body(field_info.default)
else:
field.schema = params.Body(
field_info.default) # type: ignore # pragma: nocover
return field
def __new__(mcs, name, bases, namespace, **kwargs):
from pydantic.fields import Undefined
from pydantic.class_validators import extract_validators, inherit_validators
from pydantic.types import PyObject
from pydantic.typing import is_classvar, resolve_annotations
from pydantic.utils import lenient_issubclass, validate_field_name
from pydantic.main import inherit_config, prepare_config, UNTOUCHED_TYPES
fields: Dict[str, ModelField] = {}
config = BaseConfig
validators: Dict[str, List[Validator]] = {}
for base in reversed(bases):
if issubclass(base, AbstractCheckedSession) and base != AbstractCheckedSession:
config = inherit_config(base.__config__, config)
fields.update(deepcopy(base.__fields__))
validators = inherit_validators(base.__validators__, validators)
config = inherit_config(namespace.get('Config'), config)
validators = inherit_validators(extract_validators(namespace), validators)
# update fields inherited from base classes
for field in fields.values():
field.set_config(config)
extra_validators = validators.get(field.name, [])
if extra_validators:
field.class_validators.update(extra_validators)
# re-run prepare to add extra validators
field.populate_validators()
prepare_config(config, name)
# extract and build fields
class_vars = set()
if (namespace.get('__module__'), namespace.get('__qualname__')) != \
('larray.core.checked', 'CheckedSession'):
untouched_types = UNTOUCHED_TYPES + config.keep_untouched
# annotation only fields need to come first in fields
annotations = resolve_annotations(namespace.get('__annotations__', {}),
namespace.get('__module__', None))
for ann_name, ann_type in annotations.items():
if is_classvar(ann_type):
class_vars.add(ann_name)
elif not ann_name.startswith('_'):
validate_field_name(bases, ann_name)
value = namespace.get(ann_name, Undefined)
if (isinstance(value, untouched_types) and ann_type != PyObject
and not lenient_issubclass(getattr(ann_type, '__origin__', None), Type)):
continue
fields[ann_name] = ModelField.infer(name=ann_name, value=value, annotation=ann_type,
class_validators=validators.get(ann_name, []),
config=config)
for var_name, value in namespace.items():
# 'var_name not in annotations' because namespace.items() contains annotated fields
# with default values
# 'var_name not in class_vars' to avoid to update a field if it was redeclared (by mistake)
if (var_name not in annotations and not var_name.startswith('_')
and not isinstance(value, untouched_types) and var_name not in class_vars):
validate_field_name(bases, var_name)
# the method ModelField.infer() fails to infer the type of Group objects
# (which are interpreted as ndarray objects)
annotation = type(value) if isinstance(value, Group) else annotations.get(var_name)
inferred = ModelField.infer(name=var_name, value=value, annotation=annotation,
class_validators=validators.get(var_name, []), config=config)
if var_name in fields and inferred.type_ != fields[var_name].type_:
raise TypeError(f'The type of {name}.{var_name} differs from the new default value; '
f'if you wish to change the type of this field, please use a type '
f'annotation')
fields[var_name] = inferred
new_namespace = {
'__config__': config,
'__fields__': fields,
'__field_defaults__': {n: f.default for n, f in fields.items() if not f.required},
'__validators__': validators,
**{n: v for n, v in namespace.items() if n not in fields},
}
return super().__new__(mcs, name, bases, new_namespace, **kwargs)
DEFAULT_DATA = [
{
"__ejsorm__": "generated",
"__temp__": []
},
{
"__table__": "__other",
"__data__": {}
},
]
PK_FIELD = ModelField(
name=EJ_OBJECT_ID_FIELD,
type_=int,
required=True,
model_config=BaseConfig,
class_validators=None,
)
class Ejsorm:
def __init__(self, path: str):
if not path.endswith(".json"):
raise EJError(f"Path must has .json file extension, got {path}")
self.path = path
self._data: typing.Optional[EJData] = None
@property
def data(self) -> EJData:
if self._data is None:
def check_field_type(field: ModelField, value: V) -> V:
_, errs_ = field.validate(value, {}, loc=())
if errs_:
raise TypeMisMatch(field, value)
return value
def __init__(
self,
path: str,
endpoint: Callable,
*,
response_model: Type[Any] = None,
status_code: int = 200,
tags: List[str] = None,
dependencies: Sequence[params.Depends] = None,
summary: str = None,
description: str = None,
response_description: str = "Successful Response",
responses: Dict[Union[int, str], Dict[str, Any]] = None,
deprecated: bool = None,
name: str = None,
methods: Optional[Union[Set[str], List[str]]] = None,
operation_id: str = None,
response_model_include: Union[SetIntStr, DictIntStrAny] = None,
response_model_exclude: Union[SetIntStr, DictIntStrAny] = set(),
response_model_by_alias: bool = True,
response_model_exclude_unset: bool = False,
include_in_schema: bool = True,
response_class: Optional[Type[Response]] = None,
dependency_overrides_provider: Any = None,
) -> None:
self.path = path
self.endpoint = endpoint
self.name = get_name(endpoint) if name is None else name
self.path_regex, self.path_format, self.param_convertors = compile_path(
path)
if methods is None:
methods = ["GET"]
self.methods = set([method.upper() for method in methods])
self.unique_id = generate_operation_id_for_path(
name=self.name, path=self.path_format, method=list(methods)[0])
self.response_model = response_model
if self.response_model:
assert (
status_code not in STATUS_CODES_WITH_NO_BODY
), f"Status code {status_code} must not have a response body"
response_name = "Response_" + self.unique_id
if PYDANTIC_1:
self.response_field: Optional[ModelField] = ModelField(
name=response_name,
type_=self.response_model,
class_validators={},
default=None,
required=False,
model_config=BaseConfig,
field_info=FieldInfo(None),
)
else:
self.response_field: Optional[
ModelField] = ModelField( # type: ignore # pragma: nocover
name=response_name,
type_=self.response_model,
class_validators={},
default=None,
required=False,
model_config=BaseConfig,
schema=FieldInfo(None),
)
# Create a clone of the field, so that a Pydantic submodel is not returned
# as is just because it's an instance of a subclass of a more limited class
# e.g. UserInDB (containing hashed_password) could be a subclass of User
# that doesn't have the hashed_password. But because it's a subclass, it
# would pass the validation and be returned as is.
# By being a new field, no inheritance will be passed as is. A new model
# will be always created.
self.secure_cloned_response_field: Optional[
ModelField] = create_cloned_field(self.response_field)
else:
self.response_field = None
self.secure_cloned_response_field = None
self.status_code = status_code
self.tags = tags or []
if dependencies:
self.dependencies = list(dependencies)
else:
self.dependencies = []
self.summary = summary
self.description = description or inspect.cleandoc(
self.endpoint.__doc__ or "")
# if a "form feed" character (page break) is found in the description text,
# truncate description text to the content preceding the first "form feed"
self.description = self.description.split("\f")[0]
self.response_description = response_description
self.responses = responses or {}
response_fields = {}
for additional_status_code, response in self.responses.items():
assert isinstance(response,
dict), "An additional response must be a dict"
model = response.get("model")
if model:
assert (
additional_status_code not in STATUS_CODES_WITH_NO_BODY
), f"Status code {additional_status_code} must not have a response body"
assert lenient_issubclass(
model,
BaseModel), "A response model must be a Pydantic model"
response_name = f"Response_{additional_status_code}_{self.unique_id}"
if PYDANTIC_1:
response_field = ModelField(
name=response_name,
type_=model,
class_validators=None,
default=None,
required=False,
model_config=BaseConfig,
field_info=FieldInfo(None),
)
else:
response_field = ModelField( # type: ignore # pragma: nocover
name=response_name,
type_=model,
class_validators=None,
default=None,
required=False,
model_config=BaseConfig,
schema=FieldInfo(None),
)
response_fields[additional_status_code] = response_field
if response_fields:
self.response_fields: Dict[Union[int, str],
ModelField] = response_fields
else:
self.response_fields = {}
self.deprecated = deprecated
self.operation_id = operation_id
self.response_model_include = response_model_include
self.response_model_exclude = response_model_exclude
self.response_model_by_alias = response_model_by_alias
self.response_model_exclude_unset = response_model_exclude_unset
self.include_in_schema = include_in_schema
self.response_class = response_class
assert inspect.isfunction(endpoint) or inspect.ismethod(
endpoint), f"An endpoint must be a function or method"
self.dependant = get_dependant(path=self.path_format,
call=self.endpoint)
for depends in self.dependencies[::-1]:
self.dependant.dependencies.insert(
0,
get_parameterless_sub_dependant(depends=depends,
path=self.path_format),
)
self.body_field = get_body_field(dependant=self.dependant,
name=self.unique_id)
self.dependency_overrides_provider = dependency_overrides_provider
self.app = request_response(self.get_route_handler())
async def serialize_response(
*,
field: ModelField = None,
response_content: Any,
include: Union[SetIntStr, DictIntStrAny] = None,
exclude: Union[SetIntStr, DictIntStrAny] = set(),
by_alias: bool = True,
exclude_unset: bool = False,
exclude_defaults: bool = False,
exclude_none: bool = False,
is_coroutine: bool = True,
skip_jsonable_encoder: bool = False,
skip_validation: bool = False,
) -> Any:
if field:
errors = []
response_content = _prepare_response_content(
response_content,
by_alias=by_alias,
exclude_unset=exclude_unset,
exclude_defaults=exclude_defaults,
exclude_none=exclude_none,
)
if skip_validation:
# If include is explicitly set, then never skip jsonable_encoder
#
# _prepare_response_content emits a decoded dict/list python datastructure.
# It however doesn't complete or coerce any types, so can only be used when
# explicitly specifying that one knows what one is doing, and disabling validation
#
# If you trust the encoder to handle all your types then we can just return
# the output of _prepare_response_content here
if include is None and skip_jsonable_encoder is True:
return response_content
value = response_content
else:
if is_coroutine:
value, errors_ = field.validate(response_content, {},
loc=("response", ))
else:
value, errors_ = await run_in_threadpool(field.validate,
response_content, {},
loc=("response", ))
if isinstance(errors_, ErrorWrapper):
errors.append(errors_)
elif isinstance(errors_, list):
errors.extend(errors_)
if errors:
raise ValidationError(errors, field.type_)
return jsonable_encoder(
value,
include=include,
exclude=exclude,
by_alias=by_alias,
exclude_unset=exclude_unset,
exclude_defaults=exclude_defaults,
exclude_none=exclude_none,
)
else:
# If you trust the encoder to handle all your types then we can just return
# the output of _prepare_response_content here
return (response_content if skip_jsonable_encoder else
jsonable_encoder(response_content))
