1 

     2 :mod:`timeit` --- Measure execution time of small code snippets

     3 ===============================================================

     4 

     5 .. module:: timeit

     6    :synopsis: Measure the execution time of small code snippets.

     7 

     8 

     9 .. versionadded:: 2.3

    10 

    11 .. index::

    12    single: Benchmarking

    13    single: Performance

    14 

    15 This module provides a simple way to time small bits of Python code. It has both

    16 command line as well as callable interfaces.  It avoids a number of common traps

    17 for measuring execution times.  See also Tim Peters' introduction to the

    18 "Algorithms" chapter in the Python Cookbook, published by O'Reilly.

    19 

    20 The module defines the following public class:

    21 

    22 

    23 .. class:: Timer([stmt='pass' [, setup='pass' [, timer=<timer function>]]])

    24 

    25    Class for timing execution speed of small code snippets.

    26 

    27    The constructor takes a statement to be timed, an additional statement used for

    28    setup, and a timer function.  Both statements default to ``'pass'``; the timer

    29    function is platform-dependent (see the module doc string).  The statements may

    30    contain newlines, as long as they don't contain multi-line string literals.

    31 

    32    To measure the execution time of the first statement, use the :meth:`timeit`

    33    method.  The :meth:`repeat` method is a convenience to call :meth:`timeit`

    34    multiple times and return a list of results.

    35 

    36    .. versionchanged:: 2.6

    37       The *stmt* and *setup* parameters can now also take objects that are callable

    38       without arguments. This will embed calls to them in a timer function that will

    39       then be executed by :meth:`timeit`.  Note that the timing overhead is a little

    40       larger in this case because of the extra function calls.

    41 

    42 

    43 .. method:: Timer.print_exc([file=None])

    44 

    45    Helper to print a traceback from the timed code.

    46 

    47    Typical use::

    48 

    49       t = Timer(...)       # outside the try/except

    50       try:

    51           t.timeit(...)    # or t.repeat(...)

    52       except:

    53           t.print_exc()

    54 

    55    The advantage over the standard traceback is that source lines in the compiled

    56    template will be displayed. The optional *file* argument directs where the

    57    traceback is sent; it defaults to ``sys.stderr``.

    58 

    59 

    60 .. method:: Timer.repeat([repeat=3 [, number=1000000]])

    61 

    62    Call :meth:`timeit` a few times.

    63 

    64    This is a convenience function that calls the :meth:`timeit` repeatedly,

    65    returning a list of results.  The first argument specifies how many times to

    66    call :meth:`timeit`.  The second argument specifies the *number* argument for

    67    :func:`timeit`.

    68 

    69    .. note::

    70 

    71       It's tempting to calculate mean and standard deviation from the result vector

    72       and report these.  However, this is not very useful.  In a typical case, the

    73       lowest value gives a lower bound for how fast your machine can run the given

    74       code snippet; higher values in the result vector are typically not caused by

    75       variability in Python's speed, but by other processes interfering with your

    76       timing accuracy.  So the :func:`min` of the result is probably the only number

    77       you should be interested in.  After that, you should look at the entire vector

    78       and apply common sense rather than statistics.

    79 

    80 

    81 .. method:: Timer.timeit([number=1000000])

    82 

    83    Time *number* executions of the main statement. This executes the setup

    84    statement once, and then returns the time it takes to execute the main statement

    85    a number of times, measured in seconds as a float.  The argument is the number

    86    of times through the loop, defaulting to one million.  The main statement, the

    87    setup statement and the timer function to be used are passed to the constructor.

    88 

    89    .. note::

    90 

    91       By default, :meth:`timeit` temporarily turns off :term:`garbage collection`

    92       during the timing.  The advantage of this approach is that it makes

    93       independent timings more comparable.  This disadvantage is that GC may be

    94       an important component of the performance of the function being measured.

    95       If so, GC can be re-enabled as the first statement in the *setup* string.

    96       For example::

    97 

    98          timeit.Timer('for i in xrange(10): oct(i)', 'gc.enable()').timeit()

    99 

   100 Starting with version 2.6, the module also defines two convenience functions:

   101 

   102 

   103 .. function:: repeat(stmt[, setup[, timer[, repeat=3 [, number=1000000]]]])

   104 

   105    Create a :class:`Timer` instance with the given statement, setup code and timer

   106    function and run its :meth:`repeat` method with the given repeat count and

   107    *number* executions.

   108 

   109    .. versionadded:: 2.6

   110 

   111 

   112 .. function:: timeit(stmt[, setup[, timer[, number=1000000]]])

   113 

   114    Create a :class:`Timer` instance with the given statement, setup code and timer

   115    function and run its :meth:`timeit` method with *number* executions.

   116 

   117    .. versionadded:: 2.6

   118 

   119 

   120 Command Line Interface

   121 ----------------------

   122 

   123 When called as a program from the command line, the following form is used::

   124 

   125    python -m timeit [-n N] [-r N] [-s S] [-t] [-c] [-h] [statement ...]

   126 

   127 where the following options are understood:

   128 

   129 -n N/:option:`--number=N`

   130    how many times to execute 'statement'

   131 

   132 -r N/:option:`--repeat=N`

   133    how many times to repeat the timer (default 3)

   134 

   135 -s S/:option:`--setup=S`

   136    statement to be executed once initially (default ``'pass'``)

   137 

   138 -t/:option:`--time`

   139    use :func:`time.time` (default on all platforms but Windows)

   140 

   141 -c/:option:`--clock`

   142    use :func:`time.clock` (default on Windows)

   143 

   144 -v/:option:`--verbose`

   145    print raw timing results; repeat for more digits precision

   146 

   147 -h/:option:`--help`

   148    print a short usage message and exit

   149 

   150 A multi-line statement may be given by specifying each line as a separate

   151 statement argument; indented lines are possible by enclosing an argument in

   152 quotes and using leading spaces.  Multiple :option:`-s` options are treated

   153 similarly.

   154 

   155 If :option:`-n` is not given, a suitable number of loops is calculated by trying

   156 successive powers of 10 until the total time is at least 0.2 seconds.

   157 

   158 The default timer function is platform dependent.  On Windows,

   159 :func:`time.clock` has microsecond granularity but :func:`time.time`'s

   160 granularity is 1/60th of a second; on Unix, :func:`time.clock` has 1/100th of a

   161 second granularity and :func:`time.time` is much more precise.  On either

   162 platform, the default timer functions measure wall clock time, not the CPU time.

   163 This means that other processes running on the same computer may interfere with

   164 the timing.  The best thing to do when accurate timing is necessary is to repeat

   165 the timing a few times and use the best time.  The :option:`-r` option is good

   166 for this; the default of 3 repetitions is probably enough in most cases.  On

   167 Unix, you can use :func:`time.clock` to measure CPU time.

   168 

   169 .. note::

   170 

   171    There is a certain baseline overhead associated with executing a pass statement.

   172    The code here doesn't try to hide it, but you should be aware of it.  The

   173    baseline overhead can be measured by invoking the program without arguments.

   174 

   175 The baseline overhead differs between Python versions!  Also, to fairly compare

   176 older Python versions to Python 2.3, you may want to use Python's :option:`-O`

   177 option for the older versions to avoid timing ``SET_LINENO`` instructions.

   178 

   179 

   180 Examples

   181 --------

   182 

   183 Here are two example sessions (one using the command line, one using the module

   184 interface) that compare the cost of using :func:`hasattr` vs.

   185 :keyword:`try`/:keyword:`except` to test for missing and present object

   186 attributes. ::

   187 

   188    % timeit.py 'try:' '  str.__nonzero__' 'except AttributeError:' '  pass'

   189    100000 loops, best of 3: 15.7 usec per loop

   190    % timeit.py 'if hasattr(str, "__nonzero__"): pass'

   191    100000 loops, best of 3: 4.26 usec per loop

   192    % timeit.py 'try:' '  int.__nonzero__' 'except AttributeError:' '  pass'

   193    1000000 loops, best of 3: 1.43 usec per loop

   194    % timeit.py 'if hasattr(int, "__nonzero__"): pass'

   195    100000 loops, best of 3: 2.23 usec per loop

   196 

   197 ::

   198 

   199    >>> import timeit

   200    >>> s = """\

   201    ... try:

   202    ...     str.__nonzero__

   203    ... except AttributeError:

   204    ...     pass

   205    ... """

   206    >>> t = timeit.Timer(stmt=s)

   207    >>> print "%.2f usec/pass" % (1000000 * t.timeit(number=100000)/100000)

   208    17.09 usec/pass

   209    >>> s = """\

   210    ... if hasattr(str, '__nonzero__'): pass

   211    ... """

   212    >>> t = timeit.Timer(stmt=s)

   213    >>> print "%.2f usec/pass" % (1000000 * t.timeit(number=100000)/100000)

   214    4.85 usec/pass

   215    >>> s = """\

   216    ... try:

   217    ...     int.__nonzero__

   218    ... except AttributeError:

   219    ...     pass

   220    ... """

   221    >>> t = timeit.Timer(stmt=s)

   222    >>> print "%.2f usec/pass" % (1000000 * t.timeit(number=100000)/100000)

   223    1.97 usec/pass

   224    >>> s = """\

   225    ... if hasattr(int, '__nonzero__'): pass

   226    ... """

   227    >>> t = timeit.Timer(stmt=s)

   228    >>> print "%.2f usec/pass" % (1000000 * t.timeit(number=100000)/100000)

   229    3.15 usec/pass

   230 

   231 To give the :mod:`timeit` module access to functions you define, you can pass a

   232 ``setup`` parameter which contains an import statement::

   233 

   234    def test():

   235        "Stupid test function"

   236        L = []

   237        for i in range(100):

   238            L.append(i)

   239 

   240    if __name__=='__main__':

   241        from timeit import Timer

   242        t = Timer("test()", "from __main__ import test")

   243        print t.timeit()

   244