hydromt.data_catalog.sources.GeoDatasetSource

class hydromt.data_catalog.sources.GeoDatasetSource(*, name: str, uri: str, data_adapter: GeoDatasetAdapter = None, driver: GeoDatasetDriver, uri_resolver: URIResolver = None, root: str | None = None, version: str | int | float | None = None, provider: str | None = None, metadata: SourceMetadata = None)

DataSource class for the GeoDatasetSource type.

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.

__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

__init__(**data)	Create a new model by parsing and validating input data from keyword arguments.
construct([_fields_set])
copy(*[, include, exclude, update, deep])	Returns a copy of the model.
detect_bbox([ds])	Detect the bounding box and crs of the dataset.
detect_time_range([ds])	Detect the temporal range of the dataset.
dict(*[, include, exclude, by_alias, ...])
from_orm(obj)
get_bbox([crs, detect])	Return the bounding box and espg code of the dataset.
get_time_range([detect])	Detect the time range of the dataset.
json(*[, include, exclude, by_alias, ...])
model_construct([_fields_set])	Creates a new instance of the Model class with validated data.
model_copy(*[, update, deep])	Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy
model_dump(*[, mode, include, exclude, ...])	Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump
model_dump_json(*[, indent, include, ...])	Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json
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, /)	We need to both initialize private attributes and call the user-defined model_post_init method.
model_rebuild(*[, force, raise_errors, ...])	Try to rebuild the pydantic-core schema for the model.
model_validate(obj, *[, strict, ...])	Validate a pydantic model instance.
model_validate_json(json_data, *[, strict, ...])	Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing
model_validate_strings(obj, *[, strict, context])	Validate the given object with string data against the Pydantic model.
parse_file(path, *[, content_type, ...])
parse_obj(obj)
parse_raw(b, *[, content_type, encoding, ...])
read_data(*[, mask, predicate, variables, ...])	Read data from this source.
schema([by_alias, ref_template])
schema_json(*[, by_alias, ref_template])
summary()	Return a summary of the DataSource.
to_file(file_path, *[, driver_override, ...])	Write the GeoDatasetSource to a local file.
to_stac_catalog([handle_nodata])	Convert a geodataset into a STAC Catalog representation.
update_forward_refs(**localns)
validate(value)

Attributes

data_type
full_uri	Join root with uri.
model_computed_fields	A dictionary of computed field names and their corresponding ComputedFieldInfo objects.
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	Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.
model_fields_set	Returns the set of fields that have been explicitly set on this model instance.
driver
data_adapter
name
uri
uri_resolver
root
version
provider
metadata