Sort a csv in python using limited memory

gistfile1.py

import os
import csv
import json
import heapq

def sortCSV(infile, column, reverse, cast):
    outfiles = []

    if reverse:
      class Desc(list):
          def __lt__(self, other):
                return self[0] > other[0]
    else:
      class Desc(list):
          def __lt__(self, other):
                return self[0] < other[0]

    with open(infile, 'r') as f:
        r = csv.reader(f, delimiter=',')
        while 1:
            rows = []
            for row in r:
                rows.append(row)
                if len(rows) == 100000:
                    break
            if len(rows) == 0:
                break
            rows = sorted(rows, key=lambda row: cast(row[column]), reverse=reverse)
            t    = os.tmpfile()
            w    = csv.writer(t, delimiter=',')
            for row in rows:
                w.writerow(row)
            t.flush()
            t.seek(0)
            outfiles.append(csv.reader(t, delimiter=','))

    decorated   = [(Desc([cast(line[column]), line]) for line in f) for f in outfiles]
    merged      = heapq.merge(*decorated)
    for line in merged:
        yield line[1]

    return


if __name__ == '__main__':
    # column 1 as int descending
    s = sortCSV('test.csv', 1, True, int)
    for row in s:
        print row