<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def search(self, query, threshold=None):
 """Search the index for items whose key exceeds threshold similarity to the query string. :param query: returned items will have at least `threshold` \ similarity to the query string. :return: list of pairs of (item, similarity) by decreasing similarity. [((0, 'SPAM'), 0.375), ((1, 'SPAN'), 0.375)] [((0, 'SPAM'), 0.125)] [((2, 'EG'), 1.0)] """

        threshold = threshold if threshold is not None else self.threshold
        results = []
        # Identify possible results
        for match, samegrams in self.items_sharing_ngrams(query).items():
            allgrams = (len(self.pad(query))
                        + self.length[match] - (2 * self.N) - samegrams + 2)
            similarity = self.ngram_similarity(samegrams, allgrams, self.warp)
            if similarity >= threshold:
                results.append((match, similarity))
        # Sort results by decreasing similarity
        results.sort(key=lambda x: x[1], reverse=True)
        return results