`timeit` — 度量小代码片段的执行时间 ¶

源代码： Lib/timeit.py

此模块提供计时小段 Python 代码的简单方式。它拥有命令行接口及 callable 接口。它避免了度量执行时间的许多常见陷阱。另请参阅 Tim Peters 的 "算法" 章节介绍在第 2 版的 Python Cookbook ，由 O’Reilly 出版。

基本范例 ¶

以下范例展示如何命令行接口可以用来比较 3 个不同表达式：

$ python -m timeit "'-'.join(str(n) for n in range(100))"
10000 loops, best of 5: 30.2 usec per loop
$ python -m timeit "'-'.join([str(n) for n in range(100)])"
10000 loops, best of 5: 27.5 usec per loop
$ python -m timeit "'-'.join(map(str, range(100)))"
10000 loops, best of 5: 23.2 usec per loop

这可以达成从 Python 接口采用：

>>> import timeit
>>> timeit.timeit('"-".join(str(n) for n in range(100))', number=10000)
0.3018611848820001
>>> timeit.timeit('"-".join([str(n) for n in range(100)])', number=10000)
0.2727368790656328
>>> timeit.timeit('"-".join(map(str, range(100)))', number=10000)
0.23702679807320237

也可以传递可调用从 Python 接口 :

>>> timeit.timeit(lambda: "-".join(map(str, range(100))), number=10000)
0.19665591977536678

注意，不管怎样 timeit() 将在使用命令行接口时才自动确定重复数。在范例章节，可以找到更多高级范例。

Python 接口 ¶

The module defines three convenience functions and a public class:

timeit. timeit ( stmt='pass' , setup='pass' , timer=<default timer> , number=1000000 , globals=None ) ¶

创建 Timer instance with the given statement, setup code and timer function and run its timeit() method with number executions. The optional globals argument specifies a namespace in which to execute the code.

3.5 版改变：可选 globals 参数被添加。

timeit. repeat ( stmt='pass' , setup='pass' , timer=<default timer> , repeat=5 , number=1000000 , globals=None ) ¶

创建 Timer instance with the given statement, setup code and timer function and run its repeat() method with the given repeat count and number executions. The optional globals argument specifies a namespace in which to execute the code.

3.5 版改变：可选 globals 参数被添加。

3.7 版改变： Default value of repeat changed from 3 to 5.

timeit. default_timer ( ) ¶

The default timer, which is always time.perf_counter(), returns float seconds. An alternative, time.perf_counter_ns, returns integer nanoseconds.

3.3 版改变： time.perf_counter() is now the default timer.

class timeit. Timer ( stmt='pass' , setup='pass' , timer=<timer function> , globals=None ) ¶

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 the module doc string). stmt and setup may also contain multiple statements separated by ; or newlines, as long as they don’t contain multi-line string literals. The statement will by default be executed within timeit’s namespace; this behavior can be controlled by passing a namespace to globals .

To measure the execution time of the first statement, use the timeit() 方法。 repeat() and autorange() methods are convenience methods to call timeit() 多次。

The execution time of setup is excluded from the overall timed execution run.

The stmt and setup parameters can also take objects that are callable without arguments. This will embed calls to them in a timer function that will then be executed by timeit() . Note that the timing overhead is a little larger in this case because of the extra function calls.

3.5 版改变：可选 globals 参数被添加。

timeit ( number = 1000000 ) ¶

时间 number executions of the main statement. This executes the setup statement once, and then returns the time it takes to execute the main statement a number of times. The default timer returns seconds as a float. 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.

注意

默认情况下， timeit() temporarily turns off 垃圾收集 during the timing. The advantage of this approach is that it makes independent timings more comparable. The disadvantage is that GC may be an important component of the performance of the function being measured. If so, GC can be re-enabled as the first statement in the setup string. For example:

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

autorange ( callback = None ) ¶

Automatically determine how many times to call timeit() .

This is a convenience function that calls timeit() repeatedly so that the total time >= 0.2 second, returning the eventual (number of loops, time taken for that number of loops). It calls timeit() with increasing numbers from the sequence 1, 2, 5, 10, 20, 50, … until the time taken is at least 0.2 seconds.

若 callback is given and is not None , it will be called after each trial with two arguments: callback(number, time_taken) .

Added in version 3.6.

repeat ( repeat = 5 , number = 1000000 ) ¶

调用 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() . The second argument specifies the number argument for timeit() .

注意

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.

3.7 版改变： Default value of repeat changed from 3 to 5.

print_exc ( 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 Exception:
    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 .

命令行接口 ¶

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

python -m timeit [-n N] [-r N] [-u U] [-s S] [-p] [-v] [-h] [statement ...]

Where the following options are understood:

-n N , --number =N ¶

-r N , --repeat =N ¶

-s S , --setup =S ¶: statement to be executed once initially (default pass )

-p , --process ¶

measure process time, not wallclock time, using time.process_time() 而不是 time.perf_counter() , which is the default

Added in version 3.3.

-u , --unit =U ¶

specify a time unit for timer output; can select nsec , usec , msec ，或 sec

Added in version 3.5.

-v , --verbose ¶: print raw timing results; repeat for more digits precision

-h , --help ¶: print a short usage message and exit

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

若 -n is not given, a suitable number of loops is calculated by trying increasing numbers from the sequence 1, 2, 5, 10, 20, 50, … until the total time is at least 0.2 seconds.

default_timer() measurements can be affected by other programs running on the same machine, so the best thing to do when accurate timing is necessary is to repeat the timing a few times and use the best time. The -r option is good for this; the default of 5 repetitions is probably enough in most cases. You can use time.process_time() to measure CPU time.

注意

There is a certain baseline overhead associated with executing a pass statement. 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, and it might differ between Python versions.

范例 ¶

It is possible to provide a setup statement that is executed only once at the beginning:

$ python -m timeit -s "text = 'sample string'; char = 'g'" "char in text"
5000000 loops, best of 5: 0.0877 usec per loop
$ python -m timeit -s "text = 'sample string'; char = 'g'" "text.find(char)"
1000000 loops, best of 5: 0.342 usec per loop

In the output, there are three fields. The loop count, which tells you how many times the statement body was run per timing loop repetition. The repetition count (‘best of 5’) which tells you how many times the timing loop was repeated, and finally the time the statement body took on average within the best repetition of the timing loop. That is, the time the fastest repetition took divided by the loop count.

>>> import timeit
>>> timeit.timeit('char in text', setup='text = "sample string"; char = "g"')
0.41440500499993504
>>> timeit.timeit('text.find(char)', setup='text = "sample string"; char = "g"')
1.7246671520006203

The same can be done using the Timer class and its methods:

>>> import timeit
>>> t = timeit.Timer('char in text', setup='text = "sample string"; char = "g"')
>>> t.timeit()
0.3955516149999312
>>> t.repeat()
[0.40183617287970225, 0.37027556854118704, 0.38344867356679524, 0.3712595970846668, 0.37866875250654886]

The following examples show how to time expressions that contain multiple lines. Here we compare the cost of using hasattr() vs. try / except to test for missing and present object attributes:

$ python -m timeit "try:" "  str.__bool__" "except AttributeError:" "  pass"
20000 loops, best of 5: 15.7 usec per loop
$ python -m timeit "if hasattr(str, '__bool__'): pass"
50000 loops, best of 5: 4.26 usec per loop
$ python -m timeit "try:" "  int.__bool__" "except AttributeError:" "  pass"
200000 loops, best of 5: 1.43 usec per loop
$ python -m timeit "if hasattr(int, '__bool__'): pass"
100000 loops, best of 5: 2.23 usec per loop

>>> 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

To give the timeit module access to functions you define, you can pass a setup parameter which contains an import statement:

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"))

Another option is to pass globals() 到 globals parameter, which will cause the code to be executed within your current global namespace. This can be more convenient than individually specifying imports:

def f(x):
    return x**2
def g(x):
    return x**4
def h(x):
    return x**8
import timeit
print(timeit.timeit('[func(42) for func in (f,g,h)]', globals=globals()))

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timeit — 度量小代码片段的执行时间 ¶

基本范例 ¶

Python 接口 ¶

命令行接口 ¶

范例 ¶

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`timeit` — 度量小代码片段的执行时间 ¶