def map_reduce(data, mapper, reducer=None):
'''Simple map/reduce for data analysis.
Each data element is passed to a *mapper* function.
The mapper returns key/value pairs
or None for data elements to be skipped.
Returns a dict with the data grouped into lists.
If a *reducer* is specified, it aggregates each list.
>>> def even_odd(elem): # sample mapper
... if 10 <= elem <= 20: # skip elems outside the range
... key = elem % 2 # group into evens and odds
... return key, elem
>>> map_reduce(range(30), even_odd) # group into evens and odds
{0: [10, 12, 14, 16, 18, 20], 1: [11, 13, 15, 17, 19]}
>>> map_reduce(range(30), even_odd, sum) # sum each group
{0: 90, 1: 75}
'''
d = {}
for entry in data:
r = mapper(entry)
if r is not None:
k, v = r
d.setdefault(k, []).append(v)
if reducer is not None:
for k, group in d.items():
d[k] = reducer(group)
return d
if __name__ == '__main__':
from collections import namedtuple
from pprint import pprint
import doctest
Person = namedtuple('Person', ['name', 'gender', 'age', 'height'])
persons = [
Person('mary', 'fem', 20, 60.2),
Person('suzy', 'fem', 30, 50.1),
Person('jane', 'fem', 20, 58.1),
Person('jill', 'fem', 20, 49.1),
Person('bess', 'fem', 40, 56.6),
Person('john', 'mal', 20, 50.8),
Person('jack', 'mal', 40, 59.1),
Person('jase', 'mal', 50, 60.3),
Person('zack', 'mal', 40, 53.7),
Person('ambr', 'fem', 20, 57.0),
Person('bill', 'mal', 20, 62.1)
]
def height_by_gender_and_agegroup(p):
key = p.gender, p.age //10
val = p.height
return key, val
def avg(s):
return sum(s) / len(s)
pprint(persons) # input dataset
pprint(map_reduce(persons, lambda p: ((p.gender, p.age), p), None)) # grouped people
pprint(map_reduce(persons, height_by_gender_and_agegroup, None)) # grouped heights
pprint(map_reduce(persons, height_by_gender_and_agegroup, len)) # size of each group
pprint(map_reduce(persons, height_by_gender_and_agegroup, max)) # maximum height by group
pprint(map_reduce(persons, height_by_gender_and_agegroup, avg)) # average height by group
print(doctest.testmod())
Diff to Previous Revision
--- revision 4 2011-04-25 22:11:59
+++ revision 5 2011-04-25 22:19:08
@@ -36,7 +36,7 @@
from collections import namedtuple
from pprint import pprint
- from math import fsum
+ import doctest
Person = namedtuple('Person', ['name', 'gender', 'age', 'height'])
@@ -60,7 +60,7 @@
return key, val
def avg(s):
- return fsum(s) / len(s)
+ return sum(s) / len(s)
pprint(persons) # input dataset
pprint(map_reduce(persons, lambda p: ((p.gender, p.age), p), None)) # grouped people
@@ -68,3 +68,5 @@
pprint(map_reduce(persons, height_by_gender_and_agegroup, len)) # size of each group
pprint(map_reduce(persons, height_by_gender_and_agegroup, max)) # maximum height by group
pprint(map_reduce(persons, height_by_gender_and_agegroup, avg)) # average height by group
+
+ print(doctest.testmod())
