Map-reduce a CSV files using the incredible UNIX sort utility in just ~24 LOC.

#!/usr/bin/env python
import csv
import subprocess
from itertools import groupby

def map_reduce_csv(mapper, reducer, key, infile, outfile):
  """ Map-reduce CSV file using UNIX sort utility. """
  sort = subprocess.Popen(
    ['/usr/bin/sort', '-t,'], 
    env={'LC_ALL': 'C'},

  # map and sort
  reader = csv.reader(infile)
  writer = csv.writer(sort.stdin, quoting=csv.QUOTE_NONE)

  for row in reader:


  # group and reduce
  reader = csv.reader(sort.stdout)
  writer = csv.writer(outfile, quoting=csv.QUOTE_NONE)

  for k, v in groupby(reader, key):
    writer.writerows(reducer(k, list(v)))

def identity(infile, outfile):
  """ Example task simply outputs sorted input file. """
  def key(row):
    return row[0]
  def mapper(row):
    yield row

  def reducer(key, values):
    for value in values:
      yield value

  map_reduce_csv(mapper, reducer, key, infile, outfile)

if __name__ == '__main__':
  import fileinput
  with open('output.csv', 'w') as outfile:
    identity(fileinput.input(), outfile)