Here the results of my micro benckmark pybench 0.7: PYBENCH 0.7 Benchmark: /home/lemburg/tmp/pybench-2.1a1.pyb (rounds=10, warp=20) Tests: per run per oper. diff * ------------------------------------------------------------------------ BuiltinFunctionCalls: 1102.30 ms 8.65 us +7.56% BuiltinMethodLookup: 966.75 ms 1.84 us +4.56% ConcatStrings: 1198.55 ms 7.99 us +11.63% ConcatUnicode: 1835.60 ms 12.24 us +19.29% CreateInstances: 1556.40 ms 37.06 us +2.49% CreateStringsWithConcat: 1396.70 ms 6.98 us +5.44% CreateUnicodeWithConcat: 1895.80 ms 9.48 us +31.61% DictCreation: 1760.50 ms 11.74 us +2.43% ForLoops: 1426.90 ms 142.69 us -7.51% IfThenElse: 1155.25 ms 1.71 us -6.24% ListSlicing: 555.40 ms 158.69 us -4.14% NestedForLoops: 784.55 ms 2.24 us -6.33% NormalClassAttribute: 1052.80 ms 1.75 us -10.42% NormalInstanceAttribute: 1053.80 ms 1.76 us +0.89% PythonFunctionCalls: 1127.50 ms 6.83 us +12.56% PythonMethodCalls: 909.10 ms 12.12 us +9.70% Recursion: 942.40 ms 75.39 us +23.74% SecondImport: 924.20 ms 36.97 us +3.98% SecondPackageImport: 951.10 ms 38.04 us +6.16% SecondSubmoduleImport: 1211.30 ms 48.45 us +7.69% SimpleComplexArithmetic: 1635.30 ms 7.43 us +5.58% SimpleDictManipulation: 963.35 ms 3.21 us -0.57% SimpleFloatArithmetic: 877.00 ms 1.59 us -2.92% SimpleIntFloatArithmetic: 851.10 ms 1.29 us -5.89% SimpleIntegerArithmetic: 850.05 ms 1.29 us -6.41% SimpleListManipulation: 1168.50 ms 4.33 us +8.14% SimpleLongArithmetic: 1231.15 ms 7.46 us +1.52% SmallLists: 2153.35 ms 8.44 us +10.77% SmallTuples: 1314.65 ms 5.48 us +3.80% SpecialClassAttribute: 1050.80 ms 1.75 us +1.48% SpecialInstanceAttribute: 1248.75 ms 2.08 us -2.32% StringMappings: 1702.60 ms 13.51 us +19.69% StringPredicates: 1024.25 ms 3.66 us -25.49% StringSlicing: 1093.35 ms 6.25 us +4.35% TryExcept: 1584.85 ms 1.06 us -10.90% TryRaiseExcept: 1239.50 ms 82.63 us +4.64% TupleSlicing: 983.00 ms 9.36 us +3.36% UnicodeMappings: 1631.65 ms 90.65 us +42.76% UnicodePredicates: 1762.10 ms 7.83 us +15.99% UnicodeProperties: 1410.80 ms 7.05 us +19.57% UnicodeSlicing: 1366.20 ms 7.81 us +19.23% ------------------------------------------------------------------------ Average round time: 58001.00 ms +3.30% *) measured against: /home/lemburg/tmp/pybench-2.0.pyb (rounds=10, warp=20) The benchmark is available here in case someone wants to verify the results on different platforms: http://www.lemburg.com/python/pybench-0.7.zip The above tests were done on a Linux 2.2 system, AMD K6 233MHz. The figures shown compare CVS Python (2.1a1) against stock Python 2.0. As you can see, Python function calls have suffered a lot for some reason. Unicode mappings and other Unicode database related methods show the effect of the compression of the Unicode database -- a clear space/speed tradeoff. I can't really explain why Unicode concatenation has had a slowdown -- perhaps the new coercion logic has something to do with this ?! On the nice side: attribute lookups are faster; probably due to the string key optimizations in the dictionary implementation. Loops and exceptions are also a tad faster. -- Marc-Andre Lemburg ______________________________________________________________________ Company: http://www.egenix.com/ Consulting: http://www.lemburg.com/ Python Pages: http://www.lemburg.com/python/