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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 treeAggregate(self, zeroValue, seqOp, combOp, depth=2):
 """ Aggregates the elements of this RDD in a multi-level tree pattern. :param depth: suggested depth of the tree (default: 2) -5 -5 -5 -5 -5 """

        if depth < 1:
            raise ValueError("Depth cannot be smaller than 1 but got %d." % depth)

        if self.getNumPartitions() == 0:
            return zeroValue

        def aggregatePartition(iterator):
            acc = zeroValue
            for obj in iterator:
                acc = seqOp(acc, obj)
            yield acc

        partiallyAggregated = self.mapPartitions(aggregatePartition)
        numPartitions = partiallyAggregated.getNumPartitions()
        scale = max(int(ceil(pow(numPartitions, 1.0 / depth))), 2)
        # If creating an extra level doesn't help reduce the wall-clock time, we stop the tree
        # aggregation.
        while numPartitions > scale + numPartitions / scale:
            numPartitions /= scale
            curNumPartitions = int(numPartitions)

            def mapPartition(i, iterator):
                for obj in iterator:
                    yield (i % curNumPartitions, obj)

            partiallyAggregated = partiallyAggregated \
                .mapPartitionsWithIndex(mapPartition) \
                .reduceByKey(combOp, curNumPartitions) \
                .values()

        return partiallyAggregated.reduce(combOp)