from python import util dataset = [] while True: s = input() if not s: break dataset.append(s) pairs = set() corr = [] for x in dataset: if not x in pairs: cx = util.reverseComplement(x) if not cx in pairs: pairs.add(x) else: pairs.remove(cx) corr.append(x) corr.append(cx) else: pairs.remove(x) corr.append(x) err_list = list(pairs) for i in err_list: for j in corr: if util.getHammingDistance(i, j) == 1 or util.getHammingDistance(i, util.reverseComplement(j)) == 1: print("%s->%s" % (i, j)) break
def p_distance(s, t): return getHammingDistance(s, t) / len(s)