python - Finding the k-mer that results in minimum hamming distance in a list of dna -


i writing program given input k=some number , dna=a list of fragments of dna, output should give k-mer of size k has minimum hamming distance in array of strings. have 3 functions, 1. 1 calculates hamming distance between k-mer , different windows of fragment dna , returns hamming distance of window lowest score, 2. 1 generates possible k-mers of size k, , 3. 1 iterates through of windows of size k , every possible k-mer. unfortunately, program giving me output aaa, incorrect. know logic error not in combination(k) nor in hammingdistance, since i've used them before correct result. 

import itertools def combination(k):     bases=['a','t','g','c']     combo=[''.join(p) p in itertools.product(bases, repeat=k)]     return combo  def hammingdistance(pattern, seq):         if pattern == seq:                return 0         else:                 dist=0                 in range(len(seq)):                         if pattern[i] != seq[i]:                                 dist += 1         return dist  def median_string(k, dna):     k_mers = combination(k)     distance = 0      temp = 1000000000000000000     string in dna:         hamming = 1000000000000000000         c = 0         k_mer in k_mers:             subset in string[c: len(string) - k]:                 if hamming > hammingdistance(k_mer, string[c : c+k]):                     hamming = hammingdistance(k_mer, string[c : c+k])                 c += 1             distance += hamming             if distance < temp:                 temp = distance                 best_pattern = k_mer             distance = 0     return best_pattern

it turned out indentation error in last conditional. 

def median_string(k, dna):     k_mers = combination(k)     distance = 0     temp = 1000000000000000000     k_mer in k_mers:         string in dna:             hamming = 1000000000000000000             c = 0             subset in string[c: len(string) - k]:                 if hamming > hammingdistance(k_mer, string[c : c+k]):                     hamming = hammingdistance(k_mer, string[c : c+k])                 c += 1             distance += hamming         if distance < temp:                 temp = distance                 best_pattern=k_mer         distance=0     return best_pattern

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