pds.api_client.models.metadata module

PDS Registry Search API

Registry API enabling advanced search on PDS data and metadata. The API provides end-points to search for bundles, collections and any PDS products with advanced search queries. It also enables to browse the archive hierarchically downward (e.g. collection/s products) or upward (e.g. bundles containing a product).

The version of the OpenAPI document: 1.3.0 Contact: pds-operator@jpl.nasa.gov Generated by OpenAPI Generator (https://openapi-generator.tech)

Do not edit the class manually.

class pds.api_client.models.metadata.Metadata(*, archive_status: str | None = None, creation_date_time: str | None = None, label_url: str, update_date_time: str | None = None, version: str | None = None)

Bases: BaseModel

archive_status: StrictStr | None

creation_date_time: StrictStr | None

classmethod from_dict(obj: Dict) → Self

Create an instance of Metadata from a dict

classmethod from_json(json_str: str) → Self

Create an instance of Metadata from a JSON string

label_url: StrictStr

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'validate_assignment': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'archive_status': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False), 'creation_date_time': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False), 'label_url': FieldInfo(annotation=str, required=True, metadata=[Strict(strict=True)]), 'update_date_time': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False), 'version': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

model_post_init(__context: Any) → None

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Args:

self: The BaseModel instance. __context: The context.

to_dict() → Dict[str, Any]

Return the dictionary representation of the model using alias.

This has the following differences from calling pydantic’s self.model_dump(by_alias=True):

• None is only added to the output dict for nullable fields that were set at model initialization. Other fields with value None are ignored.

to_json() → str

Returns the JSON representation of the model using alias

to_str() → str

Returns the string representation of the model using alias

update_date_time: StrictStr | None

version: StrictStr | None