Function open_dataset

xarray/backends/api.py:389–628

Open and decode a dataset from a file or file-like object. 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, u

(
    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 | Mapping[str, bool] | None = None,
    decode_times: (
        bool | CFDatetimeCoder | Mapping[str, bool | CFDatetimeCoder] | None
    ) = None,
    decode_timedelta: (
        bool | CFTimedeltaCoder | Mapping[str, bool | CFTimedeltaCoder] | None
    ) = None,
    use_cftime: bool | Mapping[str, bool] | None = None,
    concat_characters: bool | Mapping[str, 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_dataset(
    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 | Mapping[str, bool] | None = None,
    decode_times: (
        bool | CFDatetimeCoder | Mapping[str, bool | CFDatetimeCoder] | None
    ) = None,
    decode_timedelta: (
        bool | CFTimedeltaCoder | Mapping[str, bool | CFTimedeltaCoder] | None
    ) = None,
    use_cftime: bool | Mapping[str, bool] | None = None,
    concat_characters: bool | Mapping[str, 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,
) -> Dataset:
    """Open and decode a dataset from a file or file-like object.

    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 or when large arrays are sliced before computation.
        - ``chunks=-1`` loads the data with dask using a single chunk for all arrays.
        - ``chunks={}`` loads the data with dask using the engine&#x27;s preferred chunk
          size, generally identical to the format&#x27;s chunk size. If not available, a
          single chunk for all arrays.