MetricsExampleModel¶
- class lsst.daf.butler.tests.MetricsExampleModel(*, summary: Dict[str, Any] | None = None, output: Dict[str, Any] | None = None, data: List[Any] | None = None)¶
Bases:
BaseModel
A variant of
MetricsExample
based on model.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_metrics
(metrics)Create a model based on an example.
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: SetStr | None = 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: AbstractSetIntStr | MappingIntStrAny | None = None, exclude: AbstractSetIntStr | MappingIntStrAny | None = None, update: DictStrAny | None = 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: AbstractSetIntStr | MappingIntStrAny | None = None, exclude: AbstractSetIntStr | MappingIntStrAny | None = None, by_alias: bool = False, skip_defaults: bool | None = 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.
- classmethod from_metrics(metrics: MetricsExample) MetricsExampleModel ¶
Create a model based on an example.
- json(*, include: AbstractSetIntStr | MappingIntStrAny | None = None, exclude: AbstractSetIntStr | MappingIntStrAny | None = None, by_alias: bool = False, skip_defaults: bool | None = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Callable[[Any], Any] | None = 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: str | Path, *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) Model ¶
- classmethod parse_raw(b: str | bytes, *, content_type: unicode = None, encoding: unicode = 'utf8', proto: 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 ¶