sequences the merge sort code def merge(seqstartmidstop)lst [ start mid merge the two lists while each has more elements while mid and stopif seq[iseq[ ]lst append(seq[ ] += elselst append(seq[ ] += copy in the rest of the start to mid sequence while midlst append(seq[ ] += many merge sort implementations copy the rest of the sequence from to stop at this point this is not necessary since in the next part of the code the same part of the sequence would be copied right back to the same place while stoplst append(seq[ ] += copy the elements back to the original sequence for in range(len(lst))seq[start+ ]=lst[ def mergesortrecursively(seqstartstop)we must use >here only when the sequence we are sorting is empty otherwise start =stop- in the base case if start >stop- return mid (start stop/ mergesortrecursively(seqstartmidmergesortrecursively(seqmidstopmerge(seqstartmidstop def mergesort(seq)mergesortrecursively(seq len(seq)the merge sort algorithm takes this divide and conquer strategy to the extreme it divides the listthen divides it again and againuntil we are left with lists of size sublist of length is already sorted two sorted sublists can be merged into one sorted list in (ntime list can be divided into lists of size by repeatedly splitting in (log ntime each of the split lists are then merged together in (ntime this results in complexity of ( log nfor merge sort the merge sort code appears in sect the merge function takes care of merging two adjacent sublists the first sublist runs from start to mid- the second sublist runs from mid to stop- the elements this copy belongs to 'acha