Hi folks,

I'm trying to a somewhat sophisticated diff between individual rows in two CSV files. I need to ensure that a row from one file does not appear in the other file, but I am given no guarantee of the order of the rows in either file. As a starting point, I've been trying to compare the hashes of the string representations of the rows (i.e. Python lists). For example:

import csv

hashes = []
for row in csv.reader(open('old.csv','rb')):
  hashes.append( hash(str(row)) )

for row in csv.reader(open('new.csv','rb')):
  if hash(str(row)) not in hashes:
    print 'Not found'

But this is failing miserably. I am constrained by artificially imposed memory limits that I cannot change, and thusly I went with the hashes instead of storing and comparing the lists directly. Some of the files I am comparing can be hundreds of megabytes in size. Any ideas for a way to accurately compress Python lists so that they can be compared in terms of simple equality to other lists? I.e. a hashing system that actually works? Bonus points: why didn't the above method work?