Function open_dataarray

xarray/backends/api.py:631–859

Open a DataArray from a file or file-like object containing a single data variable. This is designed to read netCDF files with only one data variable. If multiple variables are present then a ValueError is raised. Parameters ---------- filename_or_obj : str, Path, file-like

(
    filename_or_obj: T_PathFileOrDataStore,
    *,
    engine: T_Engine = None,
    chunks: T_Chunks = None,
    cache: bool | None = None,
    decode_cf: bool | None = None,
    mask_and_scale: bool | None = None,
    decode_times: (
        bool | CFDatetimeCoder | Mapping[str, bool | CFDatetimeCoder] | None
    ) = None,
    decode_timedelta: bool | CFTimedeltaCoder | None = None,
    use_cftime: bool | None = None,
    concat_characters: bool | None = None,
    decode_coords: Literal["coordinates", "all"] | bool | None = None,
    drop_variables: str | Iterable[str] | None = None,
    create_default_indexes: bool = True,
    inline_array: bool = False,
    chunked_array_type: str | None = None,
    from_array_kwargs: dict[str, Any] | None = None,
    backend_kwargs: dict[str, Any] | None = None,
    **kwargs,
)

def open_dataarray(
    filename_or_obj: T_PathFileOrDataStore,
    *,
    engine: T_Engine = None,
    chunks: T_Chunks = None,
    cache: bool | None = None,
    decode_cf: bool | None = None,
    mask_and_scale: bool | None = None,
    decode_times: (
        bool | CFDatetimeCoder | Mapping[str, bool | CFDatetimeCoder] | None
    ) = None,
    decode_timedelta: bool | CFTimedeltaCoder | None = None,
    use_cftime: bool | None = None,
    concat_characters: bool | None = None,
    decode_coords: Literal["coordinates", "all"] | bool | None = None,
    drop_variables: str | Iterable[str] | None = None,
    create_default_indexes: bool = True,
    inline_array: bool = False,
    chunked_array_type: str | None = None,
    from_array_kwargs: dict[str, Any] | None = None,
    backend_kwargs: dict[str, Any] | None = None,
    **kwargs,
) -> DataArray:
    """Open a DataArray from a file or file-like object containing a single
    data variable.

    This is designed to read netCDF files with only one data variable. If
    multiple variables are present then a ValueError is raised.

    Parameters
    ----------
    filename_or_obj : str, Path, file-like, bytes, memoryview or DataStore
        Strings and Path objects are interpreted as a path to a netCDF file
        or an OpenDAP URL and opened with python-netCDF4, unless the filename
        ends with .gz, in which case the file is gunzipped and opened with
        scipy.io.netcdf (only netCDF3 supported). Bytes, memoryview and
        file-like objects are opened by scipy.io.netcdf (netCDF3) or h5netcdf
        (netCDF4).
    engine : {"netcdf4", "scipy", "pydap", "h5netcdf", "zarr", None}\
        , installed backend \
        or subclass of xarray.backends.BackendEntrypoint, optional
        Engine to use when reading files. If not provided, the default engine
        is chosen based on available dependencies, by default preferring
        "netcdf4" over "h5netcdf" over "scipy" (customizable via
        ``netcdf_engine_order`` in ``xarray.set_options()``). A custom backend
        class (a subclass of ``BackendEntrypoint``) can also be used.
    chunks : int, dict, 'auto' or None, default: None
        If provided, used to load the data into dask arrays.

        - ``chunks='auto'`` will use dask ``auto`` chunking taking into account the
          engine preferred chunks.
        - ``chunks=None`` skips using dask. This uses xarray's internally private
          :ref:`lazy indexing classes <internal design.lazy indexing>`,
          but data is eagerly loaded into memory as numpy arrays when accessed.
          This can be more efficient for smaller arrays, though results may vary.
        - ``chunks=-1`` loads the data with dask using a single chunk for all arrays.
        - ``chunks={}`` loads the data with dask using engine preferred chunks if
          exposed by the backend, otherwise with a single chunk for all arrays.