hydromt.data_catalog.drivers.XarrayDriverOptions

pydantic model hydromt.data_catalog.drivers.XarrayDriverOptions

Options for configuring xarray-based drivers.

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.

field preprocess: str | None = None

Name of preprocessor to apply before merging datasets. Available preprocessors include: round_latlon, to_datetimeindex, remove_duplicates, harmonise_dims. See their docstrings for details.

field ext_override: str | None = None

Override the file extension check and try to read all files as the given extension. Useful when reading zarr files without the .zarr extension.

get_preprocessor() → Callable[[Dataset], Dataset]

Get the preprocessor instance based on the configured preprocess string.

get_reading_ext(uri: str) → str

Determine the file extension to use for reading, either from the override or from the URI.

get_io_format(uri: str) → XarrayIOFormat | None

Determine the xarray reading format based on the file extension or override.

Parameters:

uri (str) – The URI of the file to read, used to infer the format from the extension if no override is set.

Returns:

format – The xarray reading format, either ‘zarr’ or ‘netcdf4’. Returns None if the extension is unsupported.

Return type:

XarrayIOFormat | None

filter_uris_by_format(uris: list[str]) → tuple[list[str], XarrayIOFormat]

Filter the list of URIs to only include those matching the specified format.

Parameters:

uris (list[str]) – List of URIs to filter.

Returns:

• filtered_uris (list[str]) – List of URIs that match the specified format.

• io_format (XarrayIOFormat) – The xarray reading format to filter by, either ‘zarr’ or ‘netcdf4’.