libera_utils.io.umm_g.UMMGranule

class libera_utils.io.umm_g.UMMGranule(*, GranuleUR: ~typing.Annotated[str, ~annotated_types.MinLen(min_length=1), ~annotated_types.MaxLen(max_length=250)], ProviderDates: ~typing.Annotated[list[~libera_utils.io.umm_g.ProviderDateType], ~annotated_types.MinLen(min_length=1), ~annotated_types.MaxLen(max_length=4)], CollectionReference: ~libera_utils.io.umm_g.CollectionReferenceType, MetadataSpecification: ~libera_utils.io.umm_g.MetadataSpecificationType = <factory>, AccessConstraints: ~libera_utils.io.umm_g.AccessConstraintsType | None = None, DataGranule: ~libera_utils.io.umm_g.DataGranuleType | None = None, PGEVersionClass: ~libera_utils.io.umm_g.PGEVersionClassType | None = None, TemporalExtent: ~libera_utils.io.umm_g.TemporalExtentType | None = None, SpatialExtent: ~libera_utils.io.umm_g.SpatialExtentType | None = None, OrbitCalculatedSpatialDomains: ~types.Annotated[list[~libera_utils.io.umm_g.OrbitCalculatedSpatialDomainType] | None, ~annotated_types.MinLen(min_length=1)] = None, MeasuredParameters: ~types.Annotated[list[~libera_utils.io.umm_g.MeasuredParameterType] | None, ~annotated_types.MinLen(min_length=1)] = None, Platforms: ~types.Annotated[list[~libera_utils.io.umm_g.PlatformType] | None, ~annotated_types.MinLen(min_length=1)] = None, Projects: ~types.Annotated[list[~libera_utils.io.umm_g.ProjectType] | None, ~annotated_types.MinLen(min_length=1)] = None, AdditionalAttributes: ~types.Annotated[list[~libera_utils.io.umm_g.AdditionalAttributeType] | None, ~annotated_types.MinLen(min_length=1)] = None, InputGranules: ~types.Annotated[list[~typing.Annotated[str, FieldInfo(annotation=NoneType, required=True, metadata=[MinLen(min_length=1), MaxLen(max_length=500)])]] | None, ~annotated_types.MinLen(min_length=1)] = None, TilingIdentificationSystem: ~libera_utils.io.umm_g.TilingIdentificationSystemType | None = None, CloudCover: float | None = None, RelatedUrls: ~types.Annotated[list[~libera_utils.io.umm_g.RelatedUrlType] | None, ~annotated_types.MinLen(min_length=1)] = None, NativeProjectionNames: list[~libera_utils.io.umm_g.ProjectionNameEnum] | None = None, GridMappingNames: list[~typing.Annotated[str, FieldInfo(annotation=NoneType, required=True, metadata=[MinLen(min_length=1), MaxLen(max_length=1024)])]] | None = None)

Bases: BaseModel

The Unified Metadata Model (UMM) for Granule (UMM-G) defines the metadata structure for describing individual data granules in NASA’s Common Metadata Repository (CMR).

Attributes:

model_extra

Get extra fields set during validation.

model_fields_set

Returns the set of fields that have been explicitly set on this model instance.

Methods

copy(*[, include, exclude, update, deep])	Returns a copy of the model.
model_construct([_fields_set])	Creates a new instance of the Model class with validated data.
model_copy(*[, update, deep])	!!! abstract "Usage Documentation"
model_dump(*[, mode, include, exclude, ...])	!!! abstract "Usage Documentation"
model_dump_json(*[, indent, ensure_ascii, ...])	!!! abstract "Usage Documentation"
model_json_schema(by_alias, ref_template, ...)	Generates a JSON schema for a model class.
model_parametrized_name(params)	Compute the class name for parametrizations of generic classes.
model_post_init(context, /)	Override this method to perform additional initialization after __init__ and model_construct.
model_rebuild(*[, force, raise_errors, ...])	Try to rebuild the pydantic-core schema for the model.
model_validate(obj, *[, strict, extra, ...])	Validate a pydantic model instance.
model_validate_json(json_data, *[, strict, ...])	!!! abstract "Usage Documentation"
model_validate_strings(obj, *[, strict, ...])	Validate the given object with string data against the Pydantic model.

construct
dict
from_dataset
from_orm
json
parse_file
parse_obj
parse_raw
schema
schema_json
update_forward_refs
validate

__init__(**data: Any) → None

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Methods

from_dataset(input_dataset, **kwargs)

Attributes

model_computed_fields
model_config	Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
model_extra	Get extra fields set during validation.
model_fields
model_fields_set	Returns the set of fields that have been explicitly set on this model instance.

model_config = {}

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

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to “allow”.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.