possibly trivial newbie list/array question

[Alex Martelli]

"Sylvain Thenault" <syt at pegasus.logilab.fr> wrote in message
news:slrn9o6qhq.11k.syt at pegasus.logilab.fr...
    ...
> >IMHO, the faster way to do it consists in using builtin map function:
> >
> >map([1.0, 2.0, 3.0], lambda x: 4.0*x)
> >
> oops, this is better:
> map(lambda x: x*4.0, [1.0, 2.0, 3.0])

Why opine when you can measure?

mul.py:
import time

start = time.clock()
for i in range(10000):
    junk = map(lambda x: 4.0*x, [1.0, 2.0, 3.0])
stend = time.clock()
print "%.2f"%(stend-start)

start = time.clock()
for i in range(10000):
    junk = [4.0*x for x in [1.0, 2.0, 3.0]]
stend = time.clock()
print "%.2f"%(stend-start)

[repeated another time to avoid cache effects]

On my trusty old box:

D:\py21>python -OO mul.py
0.34
0.31
0.34
0.31

D:\py21>python -OO mul.py
0.34
0.31
0.34
0.31

D:\py21>python -OO mul.py
0.33
0.31
0.34
0.31

So, the nifty list-comprehension is at least as
fast as the map+lambda combo, and presumably a
bit faster, about 10% -- at least on this box
(Python 2.1.1, WinNT4, Pentium3-300, lots of RAM).


Alex