[扩展阅读] timeit 模块详解（准确测量小段代码的执行时间）

timeit 模块详解 -- 准确测量小段代码的执行时间

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timeit 模块提供了测量 Python 小段代码执行时间的方法。它既可以在命令行界面直接使用，也可以通过导入模块进行调用。该模块灵活地避开了测量执行时间所容易出现的错误。

以下例子是命令行界面的使用方法：

$ python -m timeit '"-".join(str(n) for n in range(100))'
10000 loops, best of 3: 40.3 usec per loop
$ python -m timeit '"-".join([str(n) for n in range(100)])'
10000 loops, best of 3: 33.4 usec per loop
$ python -m timeit '"-".join(map(str, range(100)))'
10000 loops, best of 3: 25.2 usec per loop

以下例子是 IDLE 下调用的方法：

>>> import timeit
>>> timeit.timeit('"-".join(str(n) for n in range(100))', number=10000)
0.8187260627746582
>>> timeit.timeit('"-".join([str(n) for n in range(100)])', number=10000)
0.7288308143615723
>>> timeit.timeit('"-".join(map(str, range(100)))', number=10000) #map是将第一个参数的函数，分别第二个参数实施
0.5858950614929199

需要注意的是，只有当使用命令行界面时，timeit 才会自动确定重复的次数。

timeit 模块

该模块定义了三个实用函数和一个公共类。

timeit.timeit(stmt='pass', setup='pass', timer=<default timer>, number=1000000)

创建一个 Timer 实例，参数分别是 stmt（需要测量的语句或函数），setup（初始化代码或构建环境的导入语句），timer（计时函数），number（每一次测量中语句被执行的次数）

注：由于 timeit() 正在执行语句，语句中如果存在返回值的话会阻止 timeit() 返回执行时间。timeit() 会取代原语句中的返回值。

timeit.repeat(stmt='pass', setup='pass', timer=<default timer>, repeat=3, number=1000000)

创建一个 Timer 实例，参数分别是 stmt（需要测量的语句或函数），setup（初始化代码或构建环境的导入语句），timer（计时函数），repeat（重复测量的次数），number（每一次测量中语句被执行的次数）

timeit.default_timer()

默认的计时器，一般是 time.perf_counter()，time.perf_counter() 方法能够在任一平台提供最高精度的计时器（它也只是记录了自然时间，记录自然时间会被很多其他因素影响，例如计算机的负载）。

class timeit.Timer(stmt='pass', setup='pass', timer=<timer function>)

计算小段代码执行速度的类，构造函数需要的参数有 stmt（需要测量的语句或函数），setup（初始化代码或构建环境的导入语句），timer（计时函数）。前两个参数的默认值都是 'pass'，timer 参数是平台相关的；前两个参数都可以包含多个语句，多个语句间使用分号（;）或新行分隔开。

第一次测试语句的时间，可以使用 timeit() 方法；repeat() 方法相当于持续多次调用 timeit() 方法并将结果返回为一个列表。

stmt 和 setup 参数也可以是可供调用但没有参数的对象，这将会在一个计时函数中嵌套调用它们，然后被 timeit() 所执行。注意，由于额外的调用，计时开销会相对略高。

下面是类的一些功能

- timeit(number=1000000)

功能：计算语句执行 number 次的时间。

它会先执行一次 setup 参数的语句，然后计算 stmt 参数的语句执行 number 次的时间，返回值是以秒为单位的浮点数。number 参数的默认值是一百万，stmt、setup 和 timer 参数由 timeit.Timer 类的构造函数传递。

注意：默认情况下，timeit() 在计时的时候会暂时关闭 Python 的垃圾回收机制。这样做的优点是计时结果更具有可比性，但缺点是 GC（garbage collection，垃圾回收机制的缩写）有时候是测量函数性能的一个重要组成部分。如果是这样的话，GC 可以在 setup 参数执行第一条语句的时候被重新启动，例如：

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

- repeat(repeat=3, number=1000000)

功能：重复调用 timeit()。

repeat() 方法相当于持续多次调用 timeit() 方法并将结果返回为一个列表。repeat 参数指定重复的次数，number 参数传递给 timeit() 方法的 number 参数。

注意：人们很容易计算出平均值和标准偏差，但这并不是非常有用。在典型的情况下，最低值取决于你的机器可以多快地运行给定的代码段；在结果中更高的那些值通常不是由于 Python 的速度导致，而是因为其他进程干扰了你的计时精度。所以，你所应感兴趣的只有结果的最低值（可以用 min() 求出）。

 

- print_exc(file=None)

功能：输出计时代码的回溯（Traceback）

典型的用法：

t = Timer(...)       # outside the try/except
try:
    t.timeit(...)    # or t.repeat(...)
except Exception:
    t.print_exc()

标准回溯的优点是在编译模板中，源语句行会被显示出来。可选的 file 参数指定将回溯发送的位置，默认是发送到 sys.stderr。

命令行界面

当被作为命令行程序调用时，可以使用下列选项：

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

各个选项的含义：

选项	原型	含义
-n N	--number=N	执行指定语句（段）的次数
-r N	--repeat=N	重复测量的次数（默认 3 次）
-s S	--setup=S	指定初始化代码或构建环境的导入语句（默认是 pass）
-p	--process	测量进程时间而不是实际执行时间（使用 time.process_time() 代替默认的 time.perf_counter()）
以下是 Python3.3 新增：
-t	--time	使用 time.time()（不推荐）
-c	--clock	使用 time.clock()（不推荐）
-v	--verbose	打印原始的计时结果，输出更大精度的数值
-h	--help	打印一个简短的用法信息并退出

示例

以下演示如果在开始的时候设置初始化语句：

命令行：

$ python -m timeit -s 'text = "I love FishC.com!"; char = "o"'  'char in text'
10000000 loops, best of 3: 0.0877 usec per loop
$ python -m timeit -s 'text = "I love FishC.com!"; char = "o"'  'text.find(char)'
1000000 loops, best of 3: 0.342 usec per loop

使用 timeit 模块：

>>> import timeit
>>> timeit.timeit('char in text', setup='text = "I love FishC.com!"; char = "o"')
0.41440500499993504
>>> timeit.timeit('text.find(char)', setup='text = "I love FishC.com!"; char = "o"')
1.7246671520006203

使用 Timer 对象：

>>> import timeit
>>> t = timeit.Timer('char in text', setup='text = "I love FishC.com!"; char = "o"')
>>> t.timeit()
0.3955516149999312
>>> t.repeat()
[0.40193588800002544, 0.3960157959998014, 0.39594301399984033]

以下演示包含多行语句如何进行测量：

（我们通过 hasattr() 和 try/except 两种方法测试属性是否存在，并且比较它们之间的效率）

命令行：

$ python -m timeit 'try:' '  str.__bool__' 'except AttributeError:' '  pass'
100000 loops, best of 3: 15.7 usec per loop
$ python -m timeit 'if hasattr(str, "__bool__"): pass'
100000 loops, best of 3: 4.26 usec per loop

$ python -m timeit 'try:' '  int.__bool__' 'except AttributeError:' '  pass'
1000000 loops, best of 3: 1.43 usec per loop
$ python -m timeit 'if hasattr(int, "__bool__"): pass'
100000 loops, best of 3: 2.23 usec per loop

使用 timeit 模块：

>>> import timeit
>>> # attribute is missing
>>> s = """
... try:
...     str.__bool__
... except AttributeError:
...     pass
... """
>>> timeit.timeit(stmt=s, number=100000)
0.9138244460009446
>>> s = "if hasattr(str, '__bool__'): pass"
>>> timeit.timeit(stmt=s, number=100000)
0.5829014980008651
>>>
>>> # attribute is present
>>> s = """
... try:
...     int.__bool__
... except AttributeError:
...     pass
... """
>>> timeit.timeit(stmt=s, number=100000)
0.04215312199994514
>>> s = "if hasattr(int, '__bool__'): pass"
>>> timeit.timeit(stmt=s, number=100000)
0.08588060699912603

为了使 timeit 模块可以测量你的函数，你可以在 setup 参数中通过 import 语句导入：

def test():
    """Stupid test function"""
    L = [i for i in range(100)]

if __name__ == '__main__':
    import timeit
    print(timeit.timeit("test()", setup="from __main__ import test"))

附上 timeit 模块的实现源代码，小甲鱼强烈建议有时间的朋友可以研究一下（这对你的编程能力大有裨益）：

#! /usr/bin/env python3

"""Tool for measuring execution time of small code snippets.

This module avoids a number of common traps for measuring execution
times.  See also Tim Peters' introduction to the Algorithms chapter in
the Python Cookbook, published by O'Reilly.

Library usage: see the Timer class.

Command line usage:
    python timeit.py [-n N] [-r N] [-s S] [-t] [-c] [-p] [-h] [--] [statement]

Options:
  -n/--number N: how many times to execute 'statement' (default: see below)
  -r/--repeat N: how many times to repeat the timer (default 3)
  -s/--setup S: statement to be executed once initially (default 'pass')
  -p/--process: use time.process_time() (default is time.perf_counter())
  -t/--time: use time.time() (deprecated)
  -c/--clock: use time.clock() (deprecated)
  -v/--verbose: print raw timing results; repeat for more digits precision
  -h/--help: print this usage message and exit
  --: separate options from statement, use when statement starts with -
  statement: statement to be timed (default 'pass')

A multi-line statement may be given by specifying each line as a
separate argument; indented lines are possible by enclosing an
argument in quotes and using leading spaces.  Multiple -s options are
treated similarly.

If -n is not given, a suitable number of loops is calculated by trying
successive powers of 10 until the total time is at least 0.2 seconds.

Note: there is a certain baseline overhead associated with executing a
pass statement.  It differs between versions.  The code here doesn't try
to hide it, but you should be aware of it.  The baseline overhead can be
measured by invoking the program without arguments.

Classes:

    Timer

Functions:

    timeit(string, string) -> float
    repeat(string, string) -> list
    default_timer() -> float

"""

import gc
import sys
import time
import itertools

__all__ = ["Timer", "timeit", "repeat", "default_timer"]

dummy_src_name = "<timeit-src>"
default_number = 1000000
default_repeat = 3
default_timer = time.perf_counter

# Don't change the indentation of the template; the reindent() calls
# in Timer.__init__() depend on setup being indented 4 spaces and stmt
# being indented 8 spaces.
template = """
def inner(_it, _timer):
    {setup}
    _t0 = _timer()
    for _i in _it:
        {stmt}
    _t1 = _timer()
    return _t1 - _t0
"""

def reindent(src, indent):
    """Helper to reindent a multi-line statement."""
    return src.replace("
", "
" + " "*indent)

def _template_func(setup, func):
    """Create a timer function. Used if the "statement" is a callable."""
    def inner(_it, _timer, _func=func):
        setup()
        _t0 = _timer()
        for _i in _it:
            _func()
        _t1 = _timer()
        return _t1 - _t0
    return inner

class Timer:
    """Class for timing execution speed of small code snippets.

    The constructor takes a statement to be timed, an additional
    statement used for setup, and a timer function.  Both statements
    default to 'pass'; the timer function is platform-dependent (see
    module doc string).

    To measure the execution time of the first statement, use the
    timeit() method.  The repeat() method is a convenience to call
    timeit() multiple times and return a list of results.

    The statements may contain newlines, as long as they don't contain
    multi-line string literals.
    """

    def __init__(self, stmt="pass", setup="pass", timer=default_timer):
        """Constructor.  See class doc string."""
        self.timer = timer
        ns = {}
        if isinstance(stmt, str):
            stmt = reindent(stmt, 8)
            if isinstance(setup, str):
                setup = reindent(setup, 4)
                src = template.format(stmt=stmt, setup=setup)
            elif callable(setup):
                src = template.format(stmt=stmt, setup='_setup()')
                ns['_setup'] = setup
            else:
                raise ValueError("setup is neither a string nor callable")
            self.src = src # Save for traceback display
            code = compile(src, dummy_src_name, "exec")
            exec(code, globals(), ns)
            self.inner = ns["inner"]
        elif callable(stmt):
            self.src = None
            if isinstance(setup, str):
                _setup = setup
                def setup():
                    exec(_setup, globals(), ns)
            elif not callable(setup):
                raise ValueError("setup is neither a string nor callable")
            self.inner = _template_func(setup, stmt)
        else:
            raise ValueError("stmt is neither a string nor callable")

    def print_exc(self, file=None):
        """Helper to print a traceback from the timed code.

        Typical use:

            t = Timer(...)       # outside the try/except
            try:
                t.timeit(...)    # or t.repeat(...)
            except:
                t.print_exc()

        The advantage over the standard traceback is that source lines
        in the compiled template will be displayed.

        The optional file argument directs where the traceback is
        sent; it defaults to sys.stderr.
        """
        import linecache, traceback
        if self.src is not None:
            linecache.cache[dummy_src_name] = (len(self.src),
                                               None,
                                               self.src.split("
"),
                                               dummy_src_name)
        # else the source is already stored somewhere else

        traceback.print_exc(file=file)

    def timeit(self, number=default_number):
        """Time 'number' executions of the main statement.

        To be precise, this executes the setup statement once, and
        then returns the time it takes to execute the main statement
        a number of times, as a float measured in seconds.  The
        argument is the number of times through the loop, defaulting
        to one million.  The main statement, the setup statement and
        the timer function to be used are passed to the constructor.
        """
        it = itertools.repeat(None, number)
        gcold = gc.isenabled()
        gc.disable()
        try:
            timing = self.inner(it, self.timer)
        finally:
            if gcold:
                gc.enable()
        return timing

    def repeat(self, repeat=default_repeat, number=default_number):
        """Call timeit() a few times.

        This is a convenience function that calls the timeit()
        repeatedly, returning a list of results.  The first argument
        specifies how many times to call timeit(), defaulting to 3;
        the second argument specifies the timer argument, defaulting
        to one million.

        Note: it's tempting to calculate mean and standard deviation
        from the result vector and report these.  However, this is not
        very useful.  In a typical case, the lowest value gives a
        lower bound for how fast your machine can run the given code
        snippet; higher values in the result vector are typically not
        caused by variability in Python's speed, but by other
        processes interfering with your timing accuracy.  So the min()
        of the result is probably the only number you should be
        interested in.  After that, you should look at the entire
        vector and apply common sense rather than statistics.
        """
        r = []
        for i in range(repeat):
            t = self.timeit(number)
            r.append(t)
        return r

def timeit(stmt="pass", setup="pass", timer=default_timer,
           number=default_number):
    """Convenience function to create Timer object and call timeit method."""
    return Timer(stmt, setup, timer).timeit(number)

def repeat(stmt="pass", setup="pass", timer=default_timer,
           repeat=default_repeat, number=default_number):
    """Convenience function to create Timer object and call repeat method."""
    return Timer(stmt, setup, timer).repeat(repeat, number)

def main(args=None, *, _wrap_timer=None):
    """Main program, used when run as a script.

    The optional 'args' argument specifies the command line to be parsed,
    defaulting to sys.argv[1:].

    The return value is an exit code to be passed to sys.exit(); it
    may be None to indicate success.

    When an exception happens during timing, a traceback is printed to
    stderr and the return value is 1.  Exceptions at other times
    (including the template compilation) are not caught.

    '_wrap_timer' is an internal interface used for unit testing.  If it
    is not None, it must be a callable that accepts a timer function
    and returns another timer function (used for unit testing).
    """
    if args is None:
        args = sys.argv[1:]
    import getopt
    try:
        opts, args = getopt.getopt(args, "n:s:r:tcpvh",
                                   ["number=", "setup=", "repeat=",
                                    "time", "clock", "process",
                                    "verbose", "help"])
    except getopt.error as err:
        print(err)
        print("use -h/--help for command line help")
        return 2
    timer = default_timer
    stmt = "
".join(args) or "pass"
    number = 0 # auto-determine
    setup = []
    repeat = default_repeat
    verbose = 0
    precision = 3
    for o, a in opts:
        if o in ("-n", "--number"):
            number = int(a)
        if o in ("-s", "--setup"):
            setup.append(a)
        if o in ("-r", "--repeat"):
            repeat = int(a)
            if repeat <= 0:
                repeat = 1
        if o in ("-t", "--time"):
            timer = time.time
        if o in ("-c", "--clock"):
            timer = time.clock
        if o in ("-p", "--process"):
            timer = time.process_time
        if o in ("-v", "--verbose"):
            if verbose:
                precision += 1
            verbose += 1
        if o in ("-h", "--help"):
            print(__doc__, end=' ')
            return 0
    setup = "
".join(setup) or "pass"
    # Include the current directory, so that local imports work (sys.path
    # contains the directory of this script, rather than the current
    # directory)
    import os
    sys.path.insert(0, os.curdir)
    if _wrap_timer is not None:
        timer = _wrap_timer(timer)
    t = Timer(stmt, setup, timer)
    if number == 0:
        # determine number so that 0.2 <= total time < 2.0
        for i in range(1, 10):
            number = 10**i
            try:
                x = t.timeit(number)
            except:
                t.print_exc()
                return 1
            if verbose:
                print("%d loops -> %.*g secs" % (number, precision, x))
            if x >= 0.2:
                break
    try:
        r = t.repeat(repeat, number)
    except:
        t.print_exc()
        return 1
    best = min(r)
    if verbose:
        print("raw times:", " ".join(["%.*g" % (precision, x) for x in r]))
    print("%d loops," % number, end=' ')
    usec = best * 1e6 / number
    if usec < 1000:
        print("best of %d: %.*g usec per loop" % (repeat, precision, usec))
    else:
        msec = usec / 1000
        if msec < 1000:
            print("best of %d: %.*g msec per loop" % (repeat, precision, msec))
        else:
            sec = msec / 1000
            print("best of %d: %.*g sec per loop" % (repeat, precision, sec))
    return None

if __name__ == "__main__":
    sys.exit(main())