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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 update(self, x, w=1):
 """ Update the t-digest with value x and weight w. """

        self.n += w

        if len(self) == 0:
            self._add_centroid(Centroid(x, w))
            return

        S = self._find_closest_centroids(x)

        while len(S) != 0 and w > 0:
            j = choice(list(range(len(S))))
            c_j = S[j]

            q = self._compute_centroid_quantile(c_j)

            # This filters the out centroids that do not satisfy the second part
            # of the definition of S. See original paper by Dunning.
            if c_j.count + w > self._threshold(q):
                S.pop(j)
                continue

            delta_w = min(self._threshold(q) - c_j.count, w)
            self._update_centroid(c_j, x, delta_w)
            w -= delta_w
            S.pop(j)

        if w > 0:
            self._add_centroid(Centroid(x, w))

        if len(self) > self.K / self.delta:
            self.compress()

        return