Help with speeding up dictionary sort loop in Python?

I have a really ugly loop in my code which is really slowing down my program. The loop basically performs a dictionary comparison where, if a specific key in dict_A is the same as in dict_B, then for all matches a sort is performed which is written to a file.

for k, v in A_dict.items():
    for i, value in B_dict.items():
        if k == value[0]:
            sorted_B = [list(value) for key, value in groupby(sorted(B_dict.values()), key=itemgetter(1,2))]
            outfile.write('{0}\t{1}\t{2}\t{3}\t{4}\t{5}\n'.format (i, k, v, value[1], value[2], value[3])

Unfortunately, the dictionaries both contain over a million items. Other than putting this da开发者_如何转开发ta into a database then sorting, does anyone have any suggestions on how to speed up this loop? Thanks for the help.

Your example code may be inaccurate, but as written,

sorted_B = [list(value) for key, value in 
                groupby(sorted(B_dict.values()), key=itemgetter(2,3))]

will be the same every time... why is it in a loop at all?

Also

for k, v in A_dict.items():
    for i, value in B_dict.items():
        if k == value[0]:
            outfile.write('{0}\t{1}\t{2}\t{3}\t{4}\t{5}\n'.format(
                i, k, v, value[1], value[2], value[3])

Looks like it could just be written as

for i, value in B_dict.items():
    k = value[0]
    if k in A_dict:
        outfile.write('{0}\t{1}\t{2}\t{3}\t{4}\t{5}\n'.format(
            i, k, A_dict[k], value[1], value[2], value[3])

Which should be faster -- it's linear time rather than quadratic time.