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1 | ________________________________________________________________________\r |
| 2 | \r |
| 3 | PYBENCH - A Python Benchmark Suite\r |
| 4 | ________________________________________________________________________\r |
| 5 | \r |
| 6 | Extendable suite of of low-level benchmarks for measuring\r |
| 7 | the performance of the Python implementation \r |
| 8 | (interpreter, compiler or VM).\r |
| 9 | \r |
| 10 | pybench is a collection of tests that provides a standardized way to\r |
| 11 | measure the performance of Python implementations. It takes a very\r |
| 12 | close look at different aspects of Python programs and let's you\r |
| 13 | decide which factors are more important to you than others, rather\r |
| 14 | than wrapping everything up in one number, like the other performance\r |
| 15 | tests do (e.g. pystone which is included in the Python Standard\r |
| 16 | Library).\r |
| 17 | \r |
| 18 | pybench has been used in the past by several Python developers to\r |
| 19 | track down performance bottlenecks or to demonstrate the impact of\r |
| 20 | optimizations and new features in Python.\r |
| 21 | \r |
| 22 | The command line interface for pybench is the file pybench.py. Run\r |
| 23 | this script with option '--help' to get a listing of the possible\r |
| 24 | options. Without options, pybench will simply execute the benchmark\r |
| 25 | and then print out a report to stdout.\r |
| 26 | \r |
| 27 | \r |
| 28 | Micro-Manual\r |
| 29 | ------------\r |
| 30 | \r |
| 31 | Run 'pybench.py -h' to see the help screen. Run 'pybench.py' to run\r |
| 32 | the benchmark suite using default settings and 'pybench.py -f <file>'\r |
| 33 | to have it store the results in a file too.\r |
| 34 | \r |
| 35 | It is usually a good idea to run pybench.py multiple times to see\r |
| 36 | whether the environment, timers and benchmark run-times are suitable\r |
| 37 | for doing benchmark tests. \r |
| 38 | \r |
| 39 | You can use the comparison feature of pybench.py ('pybench.py -c\r |
| 40 | <file>') to check how well the system behaves in comparison to a\r |
| 41 | reference run. \r |
| 42 | \r |
| 43 | If the differences are well below 10% for each test, then you have a\r |
| 44 | system that is good for doing benchmark testings. Of you get random\r |
| 45 | differences of more than 10% or significant differences between the\r |
| 46 | values for minimum and average time, then you likely have some\r |
| 47 | background processes running which cause the readings to become\r |
| 48 | inconsistent. Examples include: web-browsers, email clients, RSS\r |
| 49 | readers, music players, backup programs, etc.\r |
| 50 | \r |
| 51 | If you are only interested in a few tests of the whole suite, you can\r |
| 52 | use the filtering option, e.g. 'pybench.py -t string' will only\r |
| 53 | run/show the tests that have 'string' in their name.\r |
| 54 | \r |
| 55 | This is the current output of pybench.py --help:\r |
| 56 | \r |
| 57 | """\r |
| 58 | ------------------------------------------------------------------------\r |
| 59 | PYBENCH - a benchmark test suite for Python interpreters/compilers.\r |
| 60 | ------------------------------------------------------------------------\r |
| 61 | \r |
| 62 | Synopsis:\r |
| 63 | pybench.py [option] files...\r |
| 64 | \r |
| 65 | Options and default settings:\r |
| 66 | -n arg number of rounds (10)\r |
| 67 | -f arg save benchmark to file arg ()\r |
| 68 | -c arg compare benchmark with the one in file arg ()\r |
| 69 | -s arg show benchmark in file arg, then exit ()\r |
| 70 | -w arg set warp factor to arg (10)\r |
| 71 | -t arg run only tests with names matching arg ()\r |
| 72 | -C arg set the number of calibration runs to arg (20)\r |
| 73 | -d hide noise in comparisons (0)\r |
| 74 | -v verbose output (not recommended) (0)\r |
| 75 | --with-gc enable garbage collection (0)\r |
| 76 | --with-syscheck use default sys check interval (0)\r |
| 77 | --timer arg use given timer (time.time)\r |
| 78 | -h show this help text\r |
| 79 | --help show this help text\r |
| 80 | --debug enable debugging\r |
| 81 | --copyright show copyright\r |
| 82 | --examples show examples of usage\r |
| 83 | \r |
| 84 | Version:\r |
| 85 | 2.0\r |
| 86 | \r |
| 87 | The normal operation is to run the suite and display the\r |
| 88 | results. Use -f to save them for later reuse or comparisons.\r |
| 89 | \r |
| 90 | Available timers:\r |
| 91 | \r |
| 92 | time.time\r |
| 93 | time.clock\r |
| 94 | systimes.processtime\r |
| 95 | \r |
| 96 | Examples:\r |
| 97 | \r |
| 98 | python2.1 pybench.py -f p21.pybench\r |
| 99 | python2.5 pybench.py -f p25.pybench\r |
| 100 | python pybench.py -s p25.pybench -c p21.pybench\r |
| 101 | """\r |
| 102 | \r |
| 103 | License\r |
| 104 | -------\r |
| 105 | \r |
| 106 | See LICENSE file.\r |
| 107 | \r |
| 108 | \r |
| 109 | Sample output\r |
| 110 | -------------\r |
| 111 | \r |
| 112 | """\r |
| 113 | -------------------------------------------------------------------------------\r |
| 114 | PYBENCH 2.0\r |
| 115 | -------------------------------------------------------------------------------\r |
| 116 | * using Python 2.4.2\r |
| 117 | * disabled garbage collection\r |
| 118 | * system check interval set to maximum: 2147483647\r |
| 119 | * using timer: time.time\r |
| 120 | \r |
| 121 | Calibrating tests. Please wait...\r |
| 122 | \r |
| 123 | Running 10 round(s) of the suite at warp factor 10:\r |
| 124 | \r |
| 125 | * Round 1 done in 6.388 seconds.\r |
| 126 | * Round 2 done in 6.485 seconds.\r |
| 127 | * Round 3 done in 6.786 seconds.\r |
| 128 | ...\r |
| 129 | * Round 10 done in 6.546 seconds.\r |
| 130 | \r |
| 131 | -------------------------------------------------------------------------------\r |
| 132 | Benchmark: 2006-06-12 12:09:25\r |
| 133 | -------------------------------------------------------------------------------\r |
| 134 | \r |
| 135 | Rounds: 10\r |
| 136 | Warp: 10\r |
| 137 | Timer: time.time\r |
| 138 | \r |
| 139 | Machine Details:\r |
| 140 | Platform ID: Linux-2.6.8-24.19-default-x86_64-with-SuSE-9.2-x86-64\r |
| 141 | Processor: x86_64\r |
| 142 | \r |
| 143 | Python:\r |
| 144 | Executable: /usr/local/bin/python\r |
| 145 | Version: 2.4.2\r |
| 146 | Compiler: GCC 3.3.4 (pre 3.3.5 20040809)\r |
| 147 | Bits: 64bit\r |
| 148 | Build: Oct 1 2005 15:24:35 (#1)\r |
| 149 | Unicode: UCS2\r |
| 150 | \r |
| 151 | \r |
| 152 | Test minimum average operation overhead\r |
| 153 | -------------------------------------------------------------------------------\r |
| 154 | BuiltinFunctionCalls: 126ms 145ms 0.28us 0.274ms\r |
| 155 | BuiltinMethodLookup: 124ms 130ms 0.12us 0.316ms\r |
| 156 | CompareFloats: 109ms 110ms 0.09us 0.361ms\r |
| 157 | CompareFloatsIntegers: 100ms 104ms 0.12us 0.271ms\r |
| 158 | CompareIntegers: 137ms 138ms 0.08us 0.542ms\r |
| 159 | CompareInternedStrings: 124ms 127ms 0.08us 1.367ms\r |
| 160 | CompareLongs: 100ms 104ms 0.10us 0.316ms\r |
| 161 | CompareStrings: 111ms 115ms 0.12us 0.929ms\r |
| 162 | CompareUnicode: 108ms 128ms 0.17us 0.693ms\r |
| 163 | ConcatStrings: 142ms 155ms 0.31us 0.562ms\r |
| 164 | ConcatUnicode: 119ms 127ms 0.42us 0.384ms\r |
| 165 | CreateInstances: 123ms 128ms 1.14us 0.367ms\r |
| 166 | CreateNewInstances: 121ms 126ms 1.49us 0.335ms\r |
| 167 | CreateStringsWithConcat: 130ms 135ms 0.14us 0.916ms\r |
| 168 | CreateUnicodeWithConcat: 130ms 135ms 0.34us 0.361ms\r |
| 169 | DictCreation: 108ms 109ms 0.27us 0.361ms\r |
| 170 | DictWithFloatKeys: 149ms 153ms 0.17us 0.678ms\r |
| 171 | DictWithIntegerKeys: 124ms 126ms 0.11us 0.915ms\r |
| 172 | DictWithStringKeys: 114ms 117ms 0.10us 0.905ms\r |
| 173 | ForLoops: 110ms 111ms 4.46us 0.063ms\r |
| 174 | IfThenElse: 118ms 119ms 0.09us 0.685ms\r |
| 175 | ListSlicing: 116ms 120ms 8.59us 0.103ms\r |
| 176 | NestedForLoops: 125ms 137ms 0.09us 0.019ms\r |
| 177 | NormalClassAttribute: 124ms 136ms 0.11us 0.457ms\r |
| 178 | NormalInstanceAttribute: 110ms 117ms 0.10us 0.454ms\r |
| 179 | PythonFunctionCalls: 107ms 113ms 0.34us 0.271ms\r |
| 180 | PythonMethodCalls: 140ms 149ms 0.66us 0.141ms\r |
| 181 | Recursion: 156ms 166ms 3.32us 0.452ms\r |
| 182 | SecondImport: 112ms 118ms 1.18us 0.180ms\r |
| 183 | SecondPackageImport: 118ms 127ms 1.27us 0.180ms\r |
| 184 | SecondSubmoduleImport: 140ms 151ms 1.51us 0.180ms\r |
| 185 | SimpleComplexArithmetic: 128ms 139ms 0.16us 0.361ms\r |
| 186 | SimpleDictManipulation: 134ms 136ms 0.11us 0.452ms\r |
| 187 | SimpleFloatArithmetic: 110ms 113ms 0.09us 0.571ms\r |
| 188 | SimpleIntFloatArithmetic: 106ms 111ms 0.08us 0.548ms\r |
| 189 | SimpleIntegerArithmetic: 106ms 109ms 0.08us 0.544ms\r |
| 190 | SimpleListManipulation: 103ms 113ms 0.10us 0.587ms\r |
| 191 | SimpleLongArithmetic: 112ms 118ms 0.18us 0.271ms\r |
| 192 | SmallLists: 105ms 116ms 0.17us 0.366ms\r |
| 193 | SmallTuples: 108ms 128ms 0.24us 0.406ms\r |
| 194 | SpecialClassAttribute: 119ms 136ms 0.11us 0.453ms\r |
| 195 | SpecialInstanceAttribute: 143ms 155ms 0.13us 0.454ms\r |
| 196 | StringMappings: 115ms 121ms 0.48us 0.405ms\r |
| 197 | StringPredicates: 120ms 129ms 0.18us 2.064ms\r |
| 198 | StringSlicing: 111ms 127ms 0.23us 0.781ms\r |
| 199 | TryExcept: 125ms 126ms 0.06us 0.681ms\r |
| 200 | TryRaiseExcept: 133ms 137ms 2.14us 0.361ms\r |
| 201 | TupleSlicing: 117ms 120ms 0.46us 0.066ms\r |
| 202 | UnicodeMappings: 156ms 160ms 4.44us 0.429ms\r |
| 203 | UnicodePredicates: 117ms 121ms 0.22us 2.487ms\r |
| 204 | UnicodeProperties: 115ms 153ms 0.38us 2.070ms\r |
| 205 | UnicodeSlicing: 126ms 129ms 0.26us 0.689ms\r |
| 206 | -------------------------------------------------------------------------------\r |
| 207 | Totals: 6283ms 6673ms\r |
| 208 | """\r |
| 209 | ________________________________________________________________________\r |
| 210 | \r |
| 211 | Writing New Tests\r |
| 212 | ________________________________________________________________________\r |
| 213 | \r |
| 214 | pybench tests are simple modules defining one or more pybench.Test\r |
| 215 | subclasses.\r |
| 216 | \r |
| 217 | Writing a test essentially boils down to providing two methods:\r |
| 218 | .test() which runs .rounds number of .operations test operations each\r |
| 219 | and .calibrate() which does the same except that it doesn't actually\r |
| 220 | execute the operations.\r |
| 221 | \r |
| 222 | \r |
| 223 | Here's an example:\r |
| 224 | ------------------\r |
| 225 | \r |
| 226 | from pybench import Test\r |
| 227 | \r |
| 228 | class IntegerCounting(Test):\r |
| 229 | \r |
| 230 | # Version number of the test as float (x.yy); this is important\r |
| 231 | # for comparisons of benchmark runs - tests with unequal version\r |
| 232 | # number will not get compared.\r |
| 233 | version = 1.0\r |
| 234 | \r |
| 235 | # The number of abstract operations done in each round of the\r |
| 236 | # test. An operation is the basic unit of what you want to\r |
| 237 | # measure. The benchmark will output the amount of run-time per\r |
| 238 | # operation. Note that in order to raise the measured timings\r |
| 239 | # significantly above noise level, it is often required to repeat\r |
| 240 | # sets of operations more than once per test round. The measured\r |
| 241 | # overhead per test round should be less than 1 second.\r |
| 242 | operations = 20\r |
| 243 | \r |
| 244 | # Number of rounds to execute per test run. This should be\r |
| 245 | # adjusted to a figure that results in a test run-time of between\r |
| 246 | # 1-2 seconds (at warp 1).\r |
| 247 | rounds = 100000\r |
| 248 | \r |
| 249 | def test(self):\r |
| 250 | \r |
| 251 | """ Run the test.\r |
| 252 | \r |
| 253 | The test needs to run self.rounds executing\r |
| 254 | self.operations number of operations each.\r |
| 255 | \r |
| 256 | """\r |
| 257 | # Init the test\r |
| 258 | a = 1\r |
| 259 | \r |
| 260 | # Run test rounds\r |
| 261 | #\r |
| 262 | # NOTE: Use xrange() for all test loops unless you want to face\r |
| 263 | # a 20MB process !\r |
| 264 | #\r |
| 265 | for i in xrange(self.rounds):\r |
| 266 | \r |
| 267 | # Repeat the operations per round to raise the run-time\r |
| 268 | # per operation significantly above the noise level of the\r |
| 269 | # for-loop overhead. \r |
| 270 | \r |
| 271 | # Execute 20 operations (a += 1):\r |
| 272 | a += 1\r |
| 273 | a += 1\r |
| 274 | a += 1\r |
| 275 | a += 1\r |
| 276 | a += 1\r |
| 277 | a += 1\r |
| 278 | a += 1\r |
| 279 | a += 1\r |
| 280 | a += 1\r |
| 281 | a += 1\r |
| 282 | a += 1\r |
| 283 | a += 1\r |
| 284 | a += 1\r |
| 285 | a += 1\r |
| 286 | a += 1\r |
| 287 | a += 1\r |
| 288 | a += 1\r |
| 289 | a += 1\r |
| 290 | a += 1\r |
| 291 | a += 1\r |
| 292 | \r |
| 293 | def calibrate(self):\r |
| 294 | \r |
| 295 | """ Calibrate the test.\r |
| 296 | \r |
| 297 | This method should execute everything that is needed to\r |
| 298 | setup and run the test - except for the actual operations\r |
| 299 | that you intend to measure. pybench uses this method to\r |
| 300 | measure the test implementation overhead.\r |
| 301 | \r |
| 302 | """\r |
| 303 | # Init the test\r |
| 304 | a = 1\r |
| 305 | \r |
| 306 | # Run test rounds (without actually doing any operation)\r |
| 307 | for i in xrange(self.rounds):\r |
| 308 | \r |
| 309 | # Skip the actual execution of the operations, since we\r |
| 310 | # only want to measure the test's administration overhead.\r |
| 311 | pass\r |
| 312 | \r |
| 313 | Registering a new test module\r |
| 314 | -----------------------------\r |
| 315 | \r |
| 316 | To register a test module with pybench, the classes need to be\r |
| 317 | imported into the pybench.Setup module. pybench will then scan all the\r |
| 318 | symbols defined in that module for subclasses of pybench.Test and\r |
| 319 | automatically add them to the benchmark suite.\r |
| 320 | \r |
| 321 | \r |
| 322 | Breaking Comparability\r |
| 323 | ----------------------\r |
| 324 | \r |
| 325 | If a change is made to any individual test that means it is no\r |
| 326 | longer strictly comparable with previous runs, the '.version' class\r |
| 327 | variable should be updated. Therefafter, comparisons with previous\r |
| 328 | versions of the test will list as "n/a" to reflect the change.\r |
| 329 | \r |
| 330 | \r |
| 331 | Version History\r |
| 332 | ---------------\r |
| 333 | \r |
| 334 | 2.0: rewrote parts of pybench which resulted in more repeatable\r |
| 335 | timings:\r |
| 336 | - made timer a parameter\r |
| 337 | - changed the platform default timer to use high-resolution\r |
| 338 | timers rather than process timers (which have a much lower\r |
| 339 | resolution)\r |
| 340 | - added option to select timer\r |
| 341 | - added process time timer (using systimes.py)\r |
| 342 | - changed to use min() as timing estimator (average\r |
| 343 | is still taken as well to provide an idea of the difference)\r |
| 344 | - garbage collection is turned off per default\r |
| 345 | - sys check interval is set to the highest possible value\r |
| 346 | - calibration is now a separate step and done using\r |
| 347 | a different strategy that allows measuring the test\r |
| 348 | overhead more accurately\r |
| 349 | - modified the tests to each give a run-time of between\r |
| 350 | 100-200ms using warp 10\r |
| 351 | - changed default warp factor to 10 (from 20)\r |
| 352 | - compared results with timeit.py and confirmed measurements\r |
| 353 | - bumped all test versions to 2.0\r |
| 354 | - updated platform.py to the latest version\r |
| 355 | - changed the output format a bit to make it look\r |
| 356 | nicer\r |
| 357 | - refactored the APIs somewhat\r |
| 358 | 1.3+: Steve Holden added the NewInstances test and the filtering \r |
| 359 | option during the NeedForSpeed sprint; this also triggered a long \r |
| 360 | discussion on how to improve benchmark timing and finally\r |
| 361 | resulted in the release of 2.0\r |
| 362 | 1.3: initial checkin into the Python SVN repository\r |
| 363 | \r |
| 364 | \r |
| 365 | Have fun,\r |
| 366 | --\r |
| 367 | Marc-Andre Lemburg\r |
| 368 | mal@lemburg.com\r |
projects / mirror_edk2.git / blame