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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 distribute(self, func, partitioned_chunks, kwargs):
 """ Calculates the features in a parallel fashion by distributing the map command to the dask workers on a local machine :param func: the function to send to each worker. :type func: callable :param partitioned_chunks: The list of data chunks - each element is again a list of chunks - and should be processed by one worker. :type partitioned_chunks: iterable :param kwargs: parameters for the map function :type kwargs: dict of string to parameter :return: The result of the calculation as a list - each item should be the result of the application of func to a single element. """

        result = self.client.gather(self.client.map(partial(func, **kwargs), partitioned_chunks))
        return [item for sublist in result for item in sublist]