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 15This module provides a simple way to time small bits of Python code. It has both 16a :ref:`timeit-command-line-interface` as well as a :ref:`callable <python-interface>` 17one. It avoids a number of common traps for measuring execution times. 18See also Tim Peters' introduction to the "Algorithms" chapter in the *Python 19Cookbook*, published by O'Reilly. 20 21 22Basic Examples 23-------------- 24 25The following example shows how the :ref:`timeit-command-line-interface` 26can be used to compare three different expressions: 27 28.. code-block:: shell-session 29 30 $ python3 -m timeit '"-".join(str(n) for n in range(100))' 31 10000 loops, best of 5: 30.2 usec per loop 32 $ python3 -m timeit '"-".join([str(n) for n in range(100)])' 33 10000 loops, best of 5: 27.5 usec per loop 34 $ python3 -m timeit '"-".join(map(str, range(100)))' 35 10000 loops, best of 5: 23.2 usec per loop 36 37This 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 48Note however that :mod:`timeit` will automatically determine the number of 49repetitions 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 55Python Interface 56---------------- 57 58The 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=5, 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 .. versionchanged:: 3.7 83 Default value of *repeat* changed from 3 to 5. 84 85.. function:: default_timer() 86 87 The default timer, which is always :func:`time.perf_counter`. 88 89 .. versionchanged:: 3.3 90 :func:`time.perf_counter` is now the default timer. 91 92 93.. class:: Timer(stmt='pass', setup='pass', timer=<timer function>, globals=None) 94 95 Class for timing execution speed of small code snippets. 96 97 The constructor takes a statement to be timed, an additional statement used 98 for setup, and a timer function. Both statements default to ``'pass'``; 99 the timer function is platform-dependent (see the module doc string). 100 *stmt* and *setup* may also contain multiple statements separated by ``;`` 101 or newlines, as long as they don't contain multi-line string literals. The 102 statement will by default be executed within timeit's namespace; this behavior 103 can be controlled by passing a namespace to *globals*. 104 105 To measure the execution time of the first statement, use the :meth:`.timeit` 106 method. The :meth:`.repeat` and :meth:`.autorange` methods are convenience 107 methods to call :meth:`.timeit` multiple times. 108 109 The execution time of *setup* is excluded from the overall timed execution run. 110 111 The *stmt* and *setup* parameters can also take objects that are callable 112 without arguments. This will embed calls to them in a timer function that 113 will then be executed by :meth:`.timeit`. Note that the timing overhead is a 114 little larger in this case because of the extra function calls. 115 116 .. versionchanged:: 3.5 117 The optional *globals* parameter was added. 118 119 .. method:: Timer.timeit(number=1000000) 120 121 Time *number* executions of the main statement. This executes the setup 122 statement once, and then returns the time it takes to execute the main 123 statement a number of times, measured in seconds as a float. 124 The argument is the number of times through the loop, defaulting to one 125 million. The main statement, the setup statement and the timer function 126 to be used are passed to the constructor. 127 128 .. note:: 129 130 By default, :meth:`.timeit` temporarily turns off :term:`garbage 131 collection` during the timing. The advantage of this approach is that 132 it makes independent timings more comparable. The disadvantage is 133 that GC may be an important component of the performance of the 134 function being measured. If so, GC can be re-enabled as the first 135 statement in the *setup* string. For example:: 136 137 timeit.Timer('for i in range(10): oct(i)', 'gc.enable()').timeit() 138 139 140 .. method:: Timer.autorange(callback=None) 141 142 Automatically determine how many times to call :meth:`.timeit`. 143 144 This is a convenience function that calls :meth:`.timeit` repeatedly 145 so that the total time >= 0.2 second, returning the eventual 146 (number of loops, time taken for that number of loops). It calls 147 :meth:`.timeit` with increasing numbers from the sequence 1, 2, 5, 148 10, 20, 50, ... until the time taken is at least 0.2 second. 149 150 If *callback* is given and is not ``None``, it will be called after 151 each trial with two arguments: ``callback(number, time_taken)``. 152 153 .. versionadded:: 3.6 154 155 156 .. method:: Timer.repeat(repeat=5, number=1000000) 157 158 Call :meth:`.timeit` a few times. 159 160 This is a convenience function that calls the :meth:`.timeit` repeatedly, 161 returning a list of results. The first argument specifies how many times 162 to call :meth:`.timeit`. The second argument specifies the *number* 163 argument for :meth:`.timeit`. 164 165 .. note:: 166 167 It's tempting to calculate mean and standard deviation from the result 168 vector and report these. However, this is not very useful. 169 In a typical case, the lowest value gives a lower bound for how fast 170 your machine can run the given code snippet; higher values in the 171 result vector are typically not caused by variability in Python's 172 speed, but by other processes interfering with your timing accuracy. 173 So the :func:`min` of the result is probably the only number you 174 should be interested in. After that, you should look at the entire 175 vector and apply common sense rather than statistics. 176 177 .. versionchanged:: 3.7 178 Default value of *repeat* changed from 3 to 5. 179 180 181 .. method:: Timer.print_exc(file=None) 182 183 Helper to print a traceback from the timed code. 184 185 Typical use:: 186 187 t = Timer(...) # outside the try/except 188 try: 189 t.timeit(...) # or t.repeat(...) 190 except Exception: 191 t.print_exc() 192 193 The advantage over the standard traceback is that source lines in the 194 compiled template will be displayed. The optional *file* argument directs 195 where the traceback is sent; it defaults to :data:`sys.stderr`. 196 197 198.. _timeit-command-line-interface: 199 200Command-Line Interface 201---------------------- 202 203When called as a program from the command line, the following form is used:: 204 205 python -m timeit [-n N] [-r N] [-u U] [-s S] [-h] [statement ...] 206 207Where the following options are understood: 208 209.. program:: timeit 210 211.. cmdoption:: -n N, --number=N 212 213 how many times to execute 'statement' 214 215.. cmdoption:: -r N, --repeat=N 216 217 how many times to repeat the timer (default 5) 218 219.. cmdoption:: -s S, --setup=S 220 221 statement to be executed once initially (default ``pass``) 222 223.. cmdoption:: -p, --process 224 225 measure process time, not wallclock time, using :func:`time.process_time` 226 instead of :func:`time.perf_counter`, which is the default 227 228 .. versionadded:: 3.3 229 230.. cmdoption:: -u, --unit=U 231 232 specify a time unit for timer output; can select nsec, usec, msec, or sec 233 234 .. versionadded:: 3.5 235 236.. cmdoption:: -v, --verbose 237 238 print raw timing results; repeat for more digits precision 239 240.. cmdoption:: -h, --help 241 242 print a short usage message and exit 243 244A multi-line statement may be given by specifying each line as a separate 245statement argument; indented lines are possible by enclosing an argument in 246quotes and using leading spaces. Multiple :option:`-s` options are treated 247similarly. 248 249If :option:`-n` is not given, a suitable number of loops is calculated by trying 250successive powers of 10 until the total time is at least 0.2 seconds. 251 252:func:`default_timer` measurements can be affected by other programs running on 253the same machine, so the best thing to do when accurate timing is necessary is 254to repeat the timing a few times and use the best time. The :option:`-r` 255option is good for this; the default of 5 repetitions is probably enough in 256most cases. You can use :func:`time.process_time` to measure CPU time. 257 258.. note:: 259 260 There is a certain baseline overhead associated with executing a pass statement. 261 The code here doesn't try to hide it, but you should be aware of it. The 262 baseline overhead can be measured by invoking the program without arguments, 263 and it might differ between Python versions. 264 265 266.. _timeit-examples: 267 268Examples 269-------- 270 271It is possible to provide a setup statement that is executed only once at the beginning: 272 273.. code-block:: shell-session 274 275 $ python -m timeit -s 'text = "sample string"; char = "g"' 'char in text' 276 5000000 loops, best of 5: 0.0877 usec per loop 277 $ python -m timeit -s 'text = "sample string"; char = "g"' 'text.find(char)' 278 1000000 loops, best of 5: 0.342 usec per loop 279 280:: 281 282 >>> import timeit 283 >>> timeit.timeit('char in text', setup='text = "sample string"; char = "g"') 284 0.41440500499993504 285 >>> timeit.timeit('text.find(char)', setup='text = "sample string"; char = "g"') 286 1.7246671520006203 287 288The same can be done using the :class:`Timer` class and its methods:: 289 290 >>> import timeit 291 >>> t = timeit.Timer('char in text', setup='text = "sample string"; char = "g"') 292 >>> t.timeit() 293 0.3955516149999312 294 >>> t.repeat() 295 [0.40183617287970225, 0.37027556854118704, 0.38344867356679524, 0.3712595970846668, 0.37866875250654886] 296 297 298The following examples show how to time expressions that contain multiple lines. 299Here we compare the cost of using :func:`hasattr` vs. :keyword:`try`/:keyword:`except` 300to test for missing and present object attributes: 301 302.. code-block:: shell-session 303 304 $ python -m timeit 'try:' ' str.__bool__' 'except AttributeError:' ' pass' 305 20000 loops, best of 5: 15.7 usec per loop 306 $ python -m timeit 'if hasattr(str, "__bool__"): pass' 307 50000 loops, best of 5: 4.26 usec per loop 308 309 $ python -m timeit 'try:' ' int.__bool__' 'except AttributeError:' ' pass' 310 200000 loops, best of 5: 1.43 usec per loop 311 $ python -m timeit 'if hasattr(int, "__bool__"): pass' 312 100000 loops, best of 5: 2.23 usec per loop 313 314:: 315 316 >>> import timeit 317 >>> # attribute is missing 318 >>> s = """\ 319 ... try: 320 ... str.__bool__ 321 ... except AttributeError: 322 ... pass 323 ... """ 324 >>> timeit.timeit(stmt=s, number=100000) 325 0.9138244460009446 326 >>> s = "if hasattr(str, '__bool__'): pass" 327 >>> timeit.timeit(stmt=s, number=100000) 328 0.5829014980008651 329 >>> 330 >>> # attribute is present 331 >>> s = """\ 332 ... try: 333 ... int.__bool__ 334 ... except AttributeError: 335 ... pass 336 ... """ 337 >>> timeit.timeit(stmt=s, number=100000) 338 0.04215312199994514 339 >>> s = "if hasattr(int, '__bool__'): pass" 340 >>> timeit.timeit(stmt=s, number=100000) 341 0.08588060699912603 342 343 344To give the :mod:`timeit` module access to functions you define, you can pass a 345*setup* parameter which contains an import statement:: 346 347 def test(): 348 """Stupid test function""" 349 L = [i for i in range(100)] 350 351 if __name__ == '__main__': 352 import timeit 353 print(timeit.timeit("test()", setup="from __main__ import test")) 354 355Another option is to pass :func:`globals` to the *globals* parameter, which will cause the code 356to be executed within your current global namespace. This can be more convenient 357than individually specifying imports:: 358 359 def f(x): 360 return x**2 361 def g(x): 362 return x**4 363 def h(x): 364 return x**8 365 366 import timeit 367 print(timeit.timeit('[func(42) for func in (f,g,h)]', globals=globals())) 368