1 :mod:`timeit` --- Measure execution time of small code snippets 2 =============================================================== 3 4 .. module:: timeit 5 :synopsis: Measure the execution time of small code snippets. 6 7 **Source code:** :source:`Lib/timeit.py` 8 9 .. index:: 10 single: Benchmarking 11 single: Performance 12 13 -------------- 14 15 This module provides a simple way to time small bits of Python code. It has both 16 a :ref:`timeit-command-line-interface` as well as a :ref:`callable <python-interface>` 17 one. It avoids a number of common traps for measuring execution times. 18 See also Tim Peters' introduction to the "Algorithms" chapter in the *Python 19 Cookbook*, published by O'Reilly. 20 21 22 Basic Examples 23 -------------- 24 25 The following example shows how the :ref:`timeit-command-line-interface` 26 can be used to compare three different expressions: 27 28 .. code-block:: sh 29 30 $ python3 -m timeit '"-".join(str(n) for n in range(100))' 31 10000 loops, best of 3: 30.2 usec per loop 32 $ python3 -m timeit '"-".join([str(n) for n in range(100)])' 33 10000 loops, best of 3: 27.5 usec per loop 34 $ python3 -m timeit '"-".join(map(str, range(100)))' 35 10000 loops, best of 3: 23.2 usec per loop 36 37 This can be achieved from the :ref:`python-interface` with:: 38 39 >>> import timeit 40 >>> timeit.timeit('"-".join(str(n) for n in range(100))', number=10000) 41 0.3018611848820001 42 >>> timeit.timeit('"-".join([str(n) for n in range(100)])', number=10000) 43 0.2727368790656328 44 >>> timeit.timeit('"-".join(map(str, range(100)))', number=10000) 45 0.23702679807320237 46 47 48 Note however that :mod:`timeit` will automatically determine the number of 49 repetitions only when the command-line interface is used. In the 50 :ref:`timeit-examples` section you can find more advanced examples. 51 52 53 .. _python-interface: 54 55 Python Interface 56 ---------------- 57 58 The module defines three convenience functions and a public class: 59 60 61 .. function:: timeit(stmt='pass', setup='pass', timer=<default timer>, number=1000000, globals=None) 62 63 Create a :class:`Timer` instance with the given statement, *setup* code and 64 *timer* function and run its :meth:`.timeit` method with *number* executions. 65 The optional *globals* argument specifies a namespace in which to execute the 66 code. 67 68 .. versionchanged:: 3.5 69 The optional *globals* parameter was added. 70 71 72 .. function:: repeat(stmt='pass', setup='pass', timer=<default timer>, repeat=3, number=1000000, globals=None) 73 74 Create a :class:`Timer` instance with the given statement, *setup* code and 75 *timer* function and run its :meth:`.repeat` method with the given *repeat* 76 count and *number* executions. The optional *globals* argument specifies a 77 namespace in which to execute the code. 78 79 .. versionchanged:: 3.5 80 The optional *globals* parameter was added. 81 82 .. function:: default_timer() 83 84 The default timer, which is always :func:`time.perf_counter`. 85 86 .. versionchanged:: 3.3 87 :func:`time.perf_counter` is now the default timer. 88 89 90 .. class:: Timer(stmt='pass', setup='pass', timer=<timer function>, globals=None) 91 92 Class for timing execution speed of small code snippets. 93 94 The constructor takes a statement to be timed, an additional statement used 95 for setup, and a timer function. Both statements default to ``'pass'``; 96 the timer function is platform-dependent (see the module doc string). 97 *stmt* and *setup* may also contain multiple statements separated by ``;`` 98 or newlines, as long as they don't contain multi-line string literals. The 99 statement will by default be executed within timeit's namespace; this behavior 100 can be controlled by passing a namespace to *globals*. 101 102 To measure the execution time of the first statement, use the :meth:`.timeit` 103 method. The :meth:`.repeat` and :meth:`.autorange` methods are convenience 104 methods to call :meth:`.timeit` multiple times. 105 106 The execution time of *setup* is excluded from the overall timed execution run. 107 108 The *stmt* and *setup* parameters can also take objects that are callable 109 without arguments. This will embed calls to them in a timer function that 110 will then be executed by :meth:`.timeit`. Note that the timing overhead is a 111 little larger in this case because of the extra function calls. 112 113 .. versionchanged:: 3.5 114 The optional *globals* parameter was added. 115 116 .. method:: Timer.timeit(number=1000000) 117 118 Time *number* executions of the main statement. This executes the setup 119 statement once, and then returns the time it takes to execute the main 120 statement a number of times, measured in seconds as a float. 121 The argument is the number of times through the loop, defaulting to one 122 million. The main statement, the setup statement and the timer function 123 to be used are passed to the constructor. 124 125 .. note:: 126 127 By default, :meth:`.timeit` temporarily turns off :term:`garbage 128 collection` during the timing. The advantage of this approach is that 129 it makes independent timings more comparable. This disadvantage is 130 that GC may be an important component of the performance of the 131 function being measured. If so, GC can be re-enabled as the first 132 statement in the *setup* string. For example:: 133 134 timeit.Timer('for i in range(10): oct(i)', 'gc.enable()').timeit() 135 136 137 .. method:: Timer.autorange(callback=None) 138 139 Automatically determine how many times to call :meth:`.timeit`. 140 141 This is a convenience function that calls :meth:`.timeit` repeatedly 142 so that the total time >= 0.2 second, returning the eventual 143 (number of loops, time taken for that number of loops). It calls 144 :meth:`.timeit` with *number* set to successive powers of ten (10, 145 100, 1000, ...) up to a maximum of one billion, until the time taken 146 is at least 0.2 second, or the maximum is reached. 147 148 If *callback* is given and is not ``None``, it will be called after 149 each trial with two arguments: ``callback(number, time_taken)``. 150 151 .. versionadded:: 3.6 152 153 154 .. method:: Timer.repeat(repeat=3, number=1000000) 155 156 Call :meth:`.timeit` a few times. 157 158 This is a convenience function that calls the :meth:`.timeit` repeatedly, 159 returning a list of results. The first argument specifies how many times 160 to call :meth:`.timeit`. The second argument specifies the *number* 161 argument for :meth:`.timeit`. 162 163 .. note:: 164 165 It's tempting to calculate mean and standard deviation from the result 166 vector and report these. However, this is not very useful. 167 In a typical case, the lowest value gives a lower bound for how fast 168 your machine can run the given code snippet; higher values in the 169 result vector are typically not caused by variability in Python's 170 speed, but by other processes interfering with your timing accuracy. 171 So the :func:`min` of the result is probably the only number you 172 should be interested in. After that, you should look at the entire 173 vector and apply common sense rather than statistics. 174 175 176 .. method:: Timer.print_exc(file=None) 177 178 Helper to print a traceback from the timed code. 179 180 Typical use:: 181 182 t = Timer(...) # outside the try/except 183 try: 184 t.timeit(...) # or t.repeat(...) 185 except Exception: 186 t.print_exc() 187 188 The advantage over the standard traceback is that source lines in the 189 compiled template will be displayed. The optional *file* argument directs 190 where the traceback is sent; it defaults to :data:`sys.stderr`. 191 192 193 .. _timeit-command-line-interface: 194 195 Command-Line Interface 196 ---------------------- 197 198 When called as a program from the command line, the following form is used:: 199 200 python -m timeit [-n N] [-r N] [-u U] [-s S] [-t] [-c] [-h] [statement ...] 201 202 Where the following options are understood: 203 204 .. program:: timeit 205 206 .. cmdoption:: -n N, --number=N 207 208 how many times to execute 'statement' 209 210 .. cmdoption:: -r N, --repeat=N 211 212 how many times to repeat the timer (default 3) 213 214 .. cmdoption:: -s S, --setup=S 215 216 statement to be executed once initially (default ``pass``) 217 218 .. cmdoption:: -p, --process 219 220 measure process time, not wallclock time, using :func:`time.process_time` 221 instead of :func:`time.perf_counter`, which is the default 222 223 .. versionadded:: 3.3 224 225 .. cmdoption:: -t, --time 226 227 use :func:`time.time` (deprecated) 228 229 .. cmdoption:: -u, --unit=U 230 231 specify a time unit for timer output; can select usec, msec, or sec 232 233 .. versionadded:: 3.5 234 235 .. cmdoption:: -c, --clock 236 237 use :func:`time.clock` (deprecated) 238 239 .. cmdoption:: -v, --verbose 240 241 print raw timing results; repeat for more digits precision 242 243 .. cmdoption:: -h, --help 244 245 print a short usage message and exit 246 247 A multi-line statement may be given by specifying each line as a separate 248 statement argument; indented lines are possible by enclosing an argument in 249 quotes and using leading spaces. Multiple :option:`-s` options are treated 250 similarly. 251 252 If :option:`-n` is not given, a suitable number of loops is calculated by trying 253 successive powers of 10 until the total time is at least 0.2 seconds. 254 255 :func:`default_timer` measurements can be affected by other programs running on 256 the same machine, so the best thing to do when accurate timing is necessary is 257 to repeat the timing a few times and use the best time. The :option:`-r` 258 option is good for this; the default of 3 repetitions is probably enough in 259 most cases. You can use :func:`time.process_time` to measure CPU time. 260 261 .. note:: 262 263 There is a certain baseline overhead associated with executing a pass statement. 264 The code here doesn't try to hide it, but you should be aware of it. The 265 baseline overhead can be measured by invoking the program without arguments, 266 and it might differ between Python versions. 267 268 269 .. _timeit-examples: 270 271 Examples 272 -------- 273 274 It is possible to provide a setup statement that is executed only once at the beginning: 275 276 .. code-block:: sh 277 278 $ python -m timeit -s 'text = "sample string"; char = "g"' 'char in text' 279 10000000 loops, best of 3: 0.0877 usec per loop 280 $ python -m timeit -s 'text = "sample string"; char = "g"' 'text.find(char)' 281 1000000 loops, best of 3: 0.342 usec per loop 282 283 :: 284 285 >>> import timeit 286 >>> timeit.timeit('char in text', setup='text = "sample string"; char = "g"') 287 0.41440500499993504 288 >>> timeit.timeit('text.find(char)', setup='text = "sample string"; char = "g"') 289 1.7246671520006203 290 291 The same can be done using the :class:`Timer` class and its methods:: 292 293 >>> import timeit 294 >>> t = timeit.Timer('char in text', setup='text = "sample string"; char = "g"') 295 >>> t.timeit() 296 0.3955516149999312 297 >>> t.repeat() 298 [0.40193588800002544, 0.3960157959998014, 0.39594301399984033] 299 300 301 The following examples show how to time expressions that contain multiple lines. 302 Here we compare the cost of using :func:`hasattr` vs. :keyword:`try`/:keyword:`except` 303 to test for missing and present object attributes: 304 305 .. code-block:: sh 306 307 $ python -m timeit 'try:' ' str.__bool__' 'except AttributeError:' ' pass' 308 100000 loops, best of 3: 15.7 usec per loop 309 $ python -m timeit 'if hasattr(str, "__bool__"): pass' 310 100000 loops, best of 3: 4.26 usec per loop 311 312 $ python -m timeit 'try:' ' int.__bool__' 'except AttributeError:' ' pass' 313 1000000 loops, best of 3: 1.43 usec per loop 314 $ python -m timeit 'if hasattr(int, "__bool__"): pass' 315 100000 loops, best of 3: 2.23 usec per loop 316 317 :: 318 319 >>> import timeit 320 >>> # attribute is missing 321 >>> s = """\ 322 ... try: 323 ... str.__bool__ 324 ... except AttributeError: 325 ... pass 326 ... """ 327 >>> timeit.timeit(stmt=s, number=100000) 328 0.9138244460009446 329 >>> s = "if hasattr(str, '__bool__'): pass" 330 >>> timeit.timeit(stmt=s, number=100000) 331 0.5829014980008651 332 >>> 333 >>> # attribute is present 334 >>> s = """\ 335 ... try: 336 ... int.__bool__ 337 ... except AttributeError: 338 ... pass 339 ... """ 340 >>> timeit.timeit(stmt=s, number=100000) 341 0.04215312199994514 342 >>> s = "if hasattr(int, '__bool__'): pass" 343 >>> timeit.timeit(stmt=s, number=100000) 344 0.08588060699912603 345 346 347 To give the :mod:`timeit` module access to functions you define, you can pass a 348 *setup* parameter which contains an import statement:: 349 350 def test(): 351 """Stupid test function""" 352 L = [i for i in range(100)] 353 354 if __name__ == '__main__': 355 import timeit 356 print(timeit.timeit("test()", setup="from __main__ import test")) 357 358 Another option is to pass :func:`globals` to the *globals* parameter, which will cause the code 359 to be executed within your current global namespace. This can be more convenient 360 than individually specifying imports:: 361 362 def f(x): 363 return x**2 364 def g(x): 365 return x**4 366 def h(x): 367 return x**8 368 369 import timeit 370 print(timeit.timeit('[func(42) for func in (f,g,h)]', globals=globals())) 371
