A simple MapReduce model in Python, introducing the concept of MapReduce in word count problem

simp_mapred.py

from itertools import groupby
# A sample input of a word count problem
source = ["Here is the first line in this source",
          "And Here is the second line in this source",
          "Welcome to the third line in this source"]
# map stage
map_result = map(lambda line: [(word.lower(), 1) for word in line.split()], source)
# [[('here', 1), ('is', 1), ('the', 1), ('first', 1),
#   ('line', 1), ('in', 1), ('this', 1), ('source', 1)],
#  [('and', 1), ('here', 1), ('is', 1), ('the', 1), ('second', 1),
#   ('line', 1), ('in', 1), ('this', 1), ('source', 1)],
#  [('welcome', 1), ('to', 1), ('the', 1), ('third', 1),
#   ('line', 1), ('in', 1), ('this', 1), ('source', 1)]]

#combine stage
combine_result = sorted([key_val for key_values in map_result for key_val in key_values])
# [('and', 1),
#  ('first', 1),
#  ('here', 1), ('here', 1),
#  ('in', 1), ('in', 1), ('in', 1),
#  ('is', 1), ('is', 1),
#  ('line', 1), ('line', 1), ('line', 1),
#  ('second', 1),
#  ('source', 1), ('source', 1), ('source', 1),
#  ('the', 1), ('the', 1), ('the', 1),
#  ('third', 1),
#  ('this', 1), ('this', 1), ('this', 1),
#  ('to', 1),
#  ('welcome', 1)]

#reduce stage
reduce_result = [(key, reduce(lambda x,y:x+y, (v for k, v in key_values)))
                 for key, key_values in groupby(combine_result, lambda kv: kv[0])]
# [('and', 1),
#  ('first', 1),
#  ('here', 2),
#  ('in', 3),
#  ('is', 2),
#  ('line', 3),
#  ('second', 1),
#  ('source', 3),
#  ('the', 3),
#  ('third', 1),
#  ('this', 3),
#  ('to', 1),
#  ('welcome', 1)]

# And a single line of this!
result = [(key, reduce(lambda x,y:x+y, (v for k, v in key_values)))
            for key, key_values in groupby(
                sorted([key_val for key_values in 
                    map(lambda line: [(word.lower(), 1) for word in line.split()], source)
                        for key_val in key_values]), lambda kv: kv[0])]