Mandus wrote:
jepp - faster, but still slower than the map.
1000000 iterations:
zip+list-comprehension: 8.1s
izip+list-comprehension: 7.5s
map: 7.0s
Strange. On 2.4.1 izip is the fastest.
The thing is that if you put benchmark code in global the
results are not fair as each variable access is a LOAD_GLOBAL
and costs a dictionary lookup. That can lead to wrong
results, like that 'try ... except ..' is faster than
'if i in ..'.
With this benchmak:
#--------------------------------------------------------
from itertools import izip
from time import time
def f1():
return map(lambda bb,ii,dd: bb+ii*dd,b,i,d)
def f2():
return [ bb+ii*dd for bb,ii,dd in zip(b,i,d) ]
def f3():
return [ bb+ii*dd for bb,ii,dd in izip(b,i,d) ]
def run(f, K):
t0 = time ()
for i in xrange (K):
f()
return time()-t0
T = 2000000
def BENCH(K):
global b, i, d
N = T/K
print "%i times tuples of size %i:" % (K,N)
b = tuple (range(0, -N, -1))
i = tuple (range(N))
d = tuple (N*[1])
for x, y in sorted ([(run (x1,K), y1) for x1, y1 in
((f1,'map'),(f2 ,'zip'),(f3,'iz ip'))]):
print '%s: %.2f' %(y,x),
print
BENCH(200000)
BENCH(20000)
BENCH(2000)
BENCH(200)
BENCH(20)
BENCH(1)
#--------------------------------------------------------
On 2.4.1 I get:
python zipmap.py
200000 times tuples of size 10:
izip: 1.32 zip: 1.50 map: 1.60
20000 times tuples of size 100:
izip: 1.00 zip: 1.14 map: 1.29
2000 times tuples of size 1000:
izip: 0.94 zip: 1.10 map: 1.28
200 times tuples of size 10000:
izip: 0.93 map: 1.29 zip: 1.51
20 times tuples of size 100000:
izip: 0.96 map: 1.31 zip: 2.28
1 times tuples of size 2000000:
izip: 0.96 map: 1.33 zip: 13.28
Stelios
