On Wed, 06 Jul 2005 11:30:14 +0100, Will McGugan wrote: > I was wondering if frozenset was faster or more efficient in some way. > > Thinking back to the dark ages of C++, you could optimize things that > you knew to be constant.
Why would you want to? py> import sets py> import time py> bigset = sets.Set(range(500000)) py> bigimmutableset = sets.ImmutableSet(range(500000)) py> assert len(bigset) == len(bigimmutableset) py> py> def tester(S, L): ... """Test if items from L are in S, and time the process.""" ... t = time.time() ... for i in range(100): ... for item in L: ... item in S ... return time.time() - t # time returned is for 100 loops ... py> Time some successful tests: py> tester(bigset, range(100, 500)) 0.11539506912231445 py> tester(bigimmutableset, range(100, 500)) 0.12014198303222656 Practically no difference when doing 100*400 checks of whether an integer is in the set. But let's try again, just in case: py> tester(bigset, range(100, 500)) 0.10998892784118652 py> tester(bigimmutableset, range(100, 500)) 0.11114096641540527 The difference is insignificant. How about unsuccessful checks? py> tester(bigset, range(-100, -500, -1)) 0.12070298194885254 py> tester(bigset, range(-100, -500, -1)) 0.11681413650512695 py> tester(bigimmutableset, range(-100, -500, -1)) 0.11313891410827637 py> tester(bigimmutableset, range(-100, -500, -1)) 0.11315703392028809 There is no significant speed difference between immutable and mutable sets, at least for queries. Regardless of whether it is successful or unsuccessful, mutable or immutable, it takes about 0.0000025 second to do each test of item in set. Why would you need to optimize that? If you tell us what you are trying to do, and under what circumstances it is too slow, we'll see if we can suggest some ways to optimize it. But if you are just trying to optimize for the sake of optimization, that's a terrible idea. Get your program working first. Then when it works, measure how fast it runs. If, and ONLY if, it is too slow, identify the parts of the program that make it too slow. That means profiling and timing. Then optimize those parts, and nothing else. Otherwise, you will be like the car designer trying to speed up his sports cars by making the seatbelts aerodynamic. -- Steven. -- http://mail.python.org/mailman/listinfo/python-list
