hydromt.data_catalog.drivers.RasterDatasetXarrayDriver

class hydromt.data_catalog.drivers.RasterDatasetXarrayDriver(*, filesystem: ~fsspec.spec.Annotated[~fsspec.spec.AbstractFileSystem, ~pydantic.functional_validators.PlainValidator(func=~hydromt._typing.fsspec_types.validate_filesystem, json_schema_input_type=~typing.Any), ~pydantic.functional_serializers.PlainSerializer(func=~hydromt._typing.fsspec_types.serialize_filesystem, return_type=PydanticUndefined, when_used=always)] = <factory>, options: ~typing.Dict[str, ~typing.Any] = <factory>)

Driver for RasterDataset using the xarray library: raster_xarray.

Supports reading and writing zarr and netcdf files using xarray. zarr files will be read using xr.open_zarr and netcdf files using xr.open_mfdataset.

Driver options include:

• preprocess: Optional[str], name of preprocessor to apply before merging datasets. Available preprocessors include: round_latlon, to_datetimeindex, remove_duplicates, harmonise_dims. See their docstrings for details.

• ext_override: Optional[str], if set, will override the file extension check and try to read all files as the given extension. Useful when reading zarr files without the .zarr extension.

• Any other option supported by xr.open_zarr or xr.open_mfdataset.

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.
dict(*[, include, exclude, by_alias, ...])
find_all_possible_types()	Return all possible sub types for this object as an iterator.
from_orm(obj)
json(*[, include, exclude, by_alias, ...])
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, include, ...])	!!! 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, ...])	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.
parse_file(path, *[, content_type, ...])
parse_obj(obj)
parse_raw(b, *[, content_type, encoding, ...])
read(uris, *[, mask, variables, time_range, ...])	Read zarr data to an xarray DataSet.
schema([by_alias, ref_template])
schema_json(*[, by_alias, ref_template])
update_forward_refs(**localns)
validate(value)
write(path, ds, **kwargs)	Write the RasterDataset to a local file using zarr.

Attributes

SUPPORTED_EXTENSIONS
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.
name
supports_writing
filesystem
options