o ix@sdddZddZddZdS) FcCs\t|}|t|krtd|dkr|rdSdStddt||D}|r,|t|S|S)aCompute the Hamming distance between the two sequences `seq1` and `seq2`. The Hamming distance is the number of differing items in two ordered sequences of the same length. If the sequences submitted do not have the same length, an error will be raised. If `normalized` evaluates to `False`, the return value will be an integer between 0 and the length of the sequences provided, edge values included; otherwise, it will be a float between 0 and 1 included, where 0 means equal, and 1 totally different. Normalized hamming distance is computed as: 0.0 if len(seq1) == 0 hamming_dist / len(seq1) otherwise z'expected two strings of the same lengthgcss|] \}}||kVqdS)N).0c1c2rrI/home/ubuntu/.local/lib/python3.10/site-packages/distance/_simpledists.py szhamming..)len ValueErrorsumzipfloat)seq1seq2 normalizedLdistrrrhammings   rcCs2t|t|}}dt||@tt||BS)zCompute the Jaccard distance between the two sequences `seq1` and `seq2`. They should contain hashable items. The return value is a float between 0 and 1, where 0 means equal, and 1 totally different. setrr r rset1set2rrrjaccards rcCs:t|t|}}ddt||@tt|t|S)zCompute the Sorensen distance between the two sequences `seq1` and `seq2`. They should contain hashable items. The return value is a float between 0 and 1, where 0 means equal, and 1 totally different. rrrrrrsorensen%s(rN)F)rrrrrrrs