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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 to_netcdf(self, *args, **kwargs):
 """Write DataArray contents to a netCDF file. Parameters path : str or Path, optional Path to which to save this dataset. If no path is provided, this function returns the resulting netCDF file as a bytes object; in this case, we need to use scipy.io.netcdf, which does not support netCDF version 4 (the default format becomes NETCDF3_64BIT). mode : {'w', 'a'}, optional Write ('w') or append ('a') mode. If mode='w', any existing file at this location will be overwritten. format : {'NETCDF4', 'NETCDF4_CLASSIC', 'NETCDF3_64BIT', 'NETCDF3_CLASSIC'}, optional File format for the resulting netCDF file: * NETCDF4: Data is stored in an HDF5 file, using netCDF4 API features. * NETCDF4_CLASSIC: Data is stored in an HDF5 file, using only netCDF 3 compatible API features. * NETCDF3_64BIT: 64-bit offset version of the netCDF 3 file format, which fully supports 2+ GB files, but is only compatible with clients linked against netCDF version 3.6.0 or later. * NETCDF3_CLASSIC: The classic netCDF 3 file format. It does not handle 2+ GB files very well. All formats are supported by the netCDF4-python library. scipy.io.netcdf only supports the last two formats. The default format is NETCDF4 if you are saving a file to disk and have the netCDF4-python library available. Otherwise, xarray falls back to using scipy to write netCDF files and defaults to the NETCDF3_64BIT format (scipy does not support netCDF4). group : str, optional Path to the netCDF4 group in the given file to open (only works for format='NETCDF4'). The group(s) will be created if necessary. engine : {'netcdf4', 'scipy', 'h5netcdf'}, optional Engine to use when writing netCDF files. If not provided, the default engine is chosen based on available dependencies, with a preference for 'netcdf4' if writing to a file on disk. encoding : dict, optional Nested dictionary with variable names as keys and dictionaries of variable specific encodings as values, e.g., ``{'my_variable': {'dtype': 'int16', 'scale_factor': 0.1, Notes ----- Only xarray.Dataset objects can be written to netCDF files, so the xarray.DataArray is converted to a xarray.Dataset object containing a single variable. If the DataArray has no name, or if the name is the same as a co-ordinate name, then it is given the name '__xarray_dataarray_variable__'. All parameters are passed directly to `xarray.Dataset.to_netcdf`. """

        from ..backends.api import DATAARRAY_NAME, DATAARRAY_VARIABLE

        if self.name is None:
            # If no name is set then use a generic xarray name
            dataset = self.to_dataset(name=DATAARRAY_VARIABLE)
        elif self.name in self.coords or self.name in self.dims:
            # The name is the same as one of the coords names, which netCDF
            # doesn't support, so rename it but keep track of the old name
            dataset = self.to_dataset(name=DATAARRAY_VARIABLE)
            dataset.attrs[DATAARRAY_NAME] = self.name
        else:
            # No problems with the name - so we're fine!
            dataset = self.to_dataset()

        return dataset.to_netcdf(*args, **kwargs)