Here’s a speed test, why not:
import random
numEntries = 1000000
d = dict(zip(range(numEntries), [random.sample(range(0, 100), 2) for x in range(numEntries)]))
def m1(d):
for k in d:
for x in d[k]:
pass
def m2(d):
for k, dk in d.iteritems():
for x in dk:
pass
import cProfile
cProfile.run('m1(d)')
print
cProfile.run('m2(d)')
# Ran 3 trials:
# m1: 0.205, 0.194, 0.193: average 0.197 s
# m2: 0.176, 0.166, 0.173: average 0.172 s
# Method 1 takes 15% more time than method 2
cProfile example output:
3 function calls in 0.194 seconds
Ordered by: standard name
ncalls tottime percall cumtime percall filename:lineno(function)
1 0.000 0.000 0.194 0.194 <string>:1(<module>)
1 0.194 0.194 0.194 0.194 stackoverflow.py:7(m1)
1 0.000 0.000 0.000 0.000 {method 'disable' of '_lsprof.Profiler' objects}
4 function calls in 0.179 seconds
Ordered by: standard name
ncalls tottime percall cumtime percall filename:lineno(function)
1 0.000 0.000 0.179 0.179 <string>:1(<module>)
1 0.179 0.179 0.179 0.179 stackoverflow.py:12(m2)
1 0.000 0.000 0.000 0.000 {method 'disable' of '_lsprof.Profiler' objects}
1 0.000 0.000 0.000 0.000 {method 'iteritems' of 'dict' objects}