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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def decode_cf(obj, concat_characters=True, mask_and_scale=True, decode_times=True, decode_coords=True, drop_variables=None, use_cftime=None):
 """Decode the given Dataset or Datastore according to CF conventions into a new Dataset. Parameters obj : Dataset or DataStore Object to decode. concat_characters : bool, optional Should character arrays be concatenated to strings, for example: ['h', 'e', 'l', 'l', 'o'] -> 'hello' mask_and_scale: bool, optional Lazily scale (using scale_factor and add_offset) and mask (using _FillValue). decode_times : bool, optional Decode cf times (e.g., integers since 'hours since 2000-01-01') to np.datetime64. decode_coords : bool, optional Use the 'coordinates' attribute on variable (or the dataset itself) to identify coordinates. drop_variables: string or iterable, optional A variable or list of variables to exclude from being parsed from the dataset. This may be useful to drop variables with problems or inconsistent values. use_cftime: bool, optional Only relevant if encoded dates come from a standard calendar (e.g. 'gregorian', 'proleptic_gregorian', 'standard', or not specified). If None (default), attempt to decode times to ``np.datetime64[ns]`` objects; if this is not possible, decode times to ``cftime.datetime`` objects. If True, always decode times to ``cftime.datetime`` objects, regardless of whether or not they can be represented using ``np.datetime64[ns]`` objects. If False, always decode times to ``np.datetime64[ns]`` objects; if this is not possible raise an error. Returns ------- decoded : Dataset """

    from .core.dataset import Dataset
    from .backends.common import AbstractDataStore

    if isinstance(obj, Dataset):
        vars = obj._variables
        attrs = obj.attrs
        extra_coords = set(obj.coords)
        file_obj = obj._file_obj
        encoding = obj.encoding
    elif isinstance(obj, AbstractDataStore):
        vars, attrs = obj.load()
        extra_coords = set()
        file_obj = obj
        encoding = obj.get_encoding()
    else:
        raise TypeError('can only decode Dataset or DataStore objects')

    vars, attrs, coord_names = decode_cf_variables(
        vars, attrs, concat_characters, mask_and_scale, decode_times,
        decode_coords, drop_variables=drop_variables, use_cftime=use_cftime)
    ds = Dataset(vars, attrs=attrs)
    ds = ds.set_coords(coord_names.union(extra_coords).intersection(vars))
    ds._file_obj = file_obj
    ds.encoding = encoding

    return ds