napari.plugins.PackageMetadata¶

class napari.plugins.PackageMetadata(*, metadata_version: Literal['1.0', '1.1', '1.2', '2.0', '2.1', '2.2'] = '1.0', name: npe2.manifest._package_metadata.ConstrainedStrValue, version: str, dynamic: List[str] = None, platform: List[str] = None, supported_platform: List[str] = None, summary: str = None, description: str = None, description_content_type: str = None, keywords: str = None, home_page: str = None, download_url: str = None, author: str = None, author_email: str = None, maintainer: str = None, maintainer_email: str = None, license: str = None, classifier: List[str] = None, requires_dist: List[str] = None, requires_python: str = None, requires_external: List[str] = None, project_url: List[str] = None, provides_extra: List[str] = None, provides_dist: List[str] = None, obsoletes_dist: List[str] = None)[source]¶

Bases: pydantic.main.BaseModel

Pydantic model for standard python package metadata.

https://www.python.org/dev/peps/pep-0566/ https://packaging.python.org/specifications/core-metadata/

The importlib.metadata provides the metadata() function, but it returns a somewhat awkward email.message.Message object.

Methods

`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.
`for_package`(name)	Get PackageMetadata from a package name.
`from_dist_metadata`(meta)	Accepts importlib.metadata.Distribution.metadata
`from_orm`(obj)
`json`(*[, include, exclude, by_alias, ...])	Generate a JSON representation of the model, include and exclude arguments as per dict().
`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)

Attributes

Details

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.

classmethod for_package(name: str) → npe2.manifest._package_metadata.PackageMetadata[source]¶: Get PackageMetadata from a package name.

classmethod from_dist_metadata(meta: email.message.Message) → PackageMetadata[source]¶: Accepts importlib.metadata.Distribution.metadata

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 and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

classmethod update_forward_refs(**localns: Any) → None¶: Try to update ForwardRefs on fields based on this Model, globalns and localns.

napari.plugins.NapariPluginManager

napari.plugins.Path