ErrorDetail¶
- class safir.models.ErrorDetail(*, loc: List[str] = None, msg: str, type: str)¶
Bases:
pydantic.main.BaseModel
The detail of the error message.
Methods Summary
construct
([_fields_set])Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
copy
(*[, include, exclude, update, deep])Duplicate a model, optionally choose which fields to include, exclude and change.
dict
(*[, include, exclude, by_alias, ...])Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
from_orm
(obj)json
(*[, include, exclude, by_alias, ...])Generate a JSON representation of the model,
include
andexclude
arguments as perdict()
.parse_file
(path, *[, content_type, ...])parse_obj
(obj)parse_raw
(b, *[, content_type, encoding, ...])schema
([by_alias, ref_template])schema_json
(*[, by_alias, ref_template])update_forward_refs
(**localns)Try to update ForwardRefs on fields based on this Model, globalns and localns.
validate
(value)Methods Documentation
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model ¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if
Config.extra = 'allow'
was set since it adds all passed values
- copy(*, include: Union[AbstractSetIntStr, MappingIntStrAny] = None, exclude: Union[AbstractSetIntStr, MappingIntStrAny] = None, update: DictStrAny = None, deep: bool = False) Model ¶
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to
True
to make a deep copy of the model
- Returns
new model instance
- dict(*, include: Union[AbstractSetIntStr, MappingIntStrAny] = None, exclude: Union[AbstractSetIntStr, MappingIntStrAny] = None, by_alias: bool = False, skip_defaults: bool = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny ¶
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- json(*, include: Union[AbstractSetIntStr, MappingIntStrAny] = None, exclude: Union[AbstractSetIntStr, MappingIntStrAny] = None, by_alias: bool = False, skip_defaults: bool = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode ¶
Generate a JSON representation of the model,
include
andexclude
arguments as perdict()
.encoder
is an optional function to supply asdefault
to json.dumps(), other arguments as perjson.dumps()
.
- classmethod parse_file(path: Union[str, pathlib.Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: pydantic.parse.Protocol = None, allow_pickle: bool = False) Model ¶
- classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: pydantic.parse.Protocol = None, allow_pickle: bool = False) Model ¶
- classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') DictStrAny ¶
- classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) unicode ¶