我如何获得Python程序的执行时间？

Question

我在Python中有一个命令行程序需要一段时间才能完成.我想知道完成跑步所需的确切时间.

我看过这个timeit模块,但它似乎只适用于小代码片段.我想要整个计划的时间.

Answer 1

Python中最简单的方法:

import time
start_time = time.time()
main()
print("--- %s seconds ---" % (time.time() - start_time))

这假定您的程序至少需要十分之一秒才能运行.

打印:

--- 0.764891862869 seconds ---

Answer 2

我把这个timing.py模块放到我自己的site-packages目录中,只需插入import timing我模块的顶部:

import atexit
from time import clock

def secondsToStr(t):
    return "%d:%02d:%02d.%03d" % \
        reduce(lambda ll,b : divmod(ll[0],b) + ll[1:],
            [(t*1000,),1000,60,60])

line = "="*40
def log(s, elapsed=None):
    print line
    print secondsToStr(clock()), '-', s
    if elapsed:
        print "Elapsed time:", elapsed
    print line
    print

def endlog():
    end = clock()
    elapsed = end-start
    log("End Program", secondsToStr(elapsed))

def now():
    return secondsToStr(clock())

start = clock()
atexit.register(endlog)
log("Start Program")

timing.log如果我想要显示的程序中有重要的阶段,我也可以从我的程序中调用.但只是包括import timing将打印开始和结束时间,以及总体经过的时间.(原谅我的模糊secondsToStr功能,它只是将浮点数秒格式化为hh:mm:ss.sss形式.)

注意:可以在此处或此处找到上述代码的Python 3版本.

Answer 3

在Linux或UNIX中:

time python yourprogram.py

在Windows中,请参阅此Stackoverflow讨论: 如何在windows命令行中测量命令的执行时间？

Answer 4

我非常喜欢Paul McGuire的回答,但我使用的是Python3.所以对于那些感兴趣的人:这里是他的答案的修改,适用于*nix上的Python 3(我想,在Windows下,应该使用clock()而不是time()):

#python3
import atexit
from time import time, strftime, localtime
from datetime import timedelta

def secondsToStr(elapsed=None):
    if elapsed is None:
        return strftime("%Y-%m-%d %H:%M:%S", localtime())
    else:
        return str(timedelta(seconds=elapsed))

def log(s, elapsed=None):
    line = "="*40
    print(line)
    print(secondsToStr(), '-', s)
    if elapsed:
        print("Elapsed time:", elapsed)
    print(line)
    print()

def endlog():
    end = time()
    elapsed = end-start
    log("End Program", secondsToStr(elapsed))

start = time()
atexit.register(endlog)
log("Start Program")

如果你觉得这很有用,你应该继续投票给他的答案而不是这个,因为他完成了大部分的工作;).

Answer 5

import time

start_time = time.clock()
main()
print time.clock() - start_time, "seconds"

time.clock()返回处理器时间,这允许我们只计算此过程使用的时间(无论如何在Unix上).文档说"无论如何,这是用于基准测试Python或计时算法的函数"

Answer 6

time.clock已在 Python 3.3 中弃用，并将从 Python 3.8 中删除：使用time.perf_counterortime.process_time代替

import time
start_time = time.perf_counter ()
for x in range(1, 100):
    print(x)
end_time = time.perf_counter ()
print(end_time - start_time, "seconds")

Answer 7

您可以使用python profiler cProfile来测量CPU时间,以及每个函数内部花费的时间以及每个函数调用的次数.如果您想要在不知道从哪里开始的情况下提高脚本的性能,这非常有用.对另一个SO问题的答案非常好.在文档中查看也总是好的.

以下是如何使用命令行中的cProfile配置脚本的示例:

$ python -m cProfile euler048.py

1007 function calls in 0.061 CPU seconds

Ordered by: standard name
ncalls  tottime  percall  cumtime  percall filename:lineno(function)
    1    0.000    0.000    0.061    0.061 <string>:1(<module>)
 1000    0.051    0.000    0.051    0.000 euler048.py:2(<lambda>)
    1    0.005    0.005    0.061    0.061 euler048.py:2(<module>)
    1    0.000    0.000    0.061    0.061 {execfile}
    1    0.002    0.002    0.053    0.053 {map}
    1    0.000    0.000    0.000    0.000 {method 'disable' of '_lsprof.Profiler objects}
    1    0.000    0.000    0.000    0.000 {range}
    1    0.003    0.003    0.003    0.003 {sum}

Answer 8

我喜欢datetime模块提供的输出,其中时间delta对象以人类可读的方式显示日期,小时,分钟等.

例如:

from datetime import datetime
start_time = datetime.now()
# do your work here
end_time = datetime.now()
print('Duration: {}'.format(end_time - start_time))

样本输出例如

Duration: 0:00:08.309267

要么

Duration: 1 day, 1:51:24.269711

更新:正如JF Sebastian所提到的,这种方法可能会遇到一些当地时间的棘手案例,因此使用起来更安全:

import time
from datetime import timedelta
start_time = time.monotonic()
end_time = time.monotonic()
print(timedelta(seconds=end_time - start_time))

Answer 9

对Linux来说更好: /usr/bin/time

$ /usr/bin/time -v python rhtest2.py

    Command being timed: "python rhtest2.py"
    User time (seconds): 4.13
    System time (seconds): 0.07
    Percent of CPU this job got: 91%
    Elapsed (wall clock) time (h:mm:ss or m:ss): 0:04.58
    Average shared text size (kbytes): 0
    Average unshared data size (kbytes): 0
    Average stack size (kbytes): 0
    Average total size (kbytes): 0
    Maximum resident set size (kbytes): 0
    Average resident set size (kbytes): 0
    Major (requiring I/O) page faults: 15
    Minor (reclaiming a frame) page faults: 5095
    Voluntary context switches: 27
    Involuntary context switches: 279
    Swaps: 0
    File system inputs: 0
    File system outputs: 0
    Socket messages sent: 0
    Socket messages received: 0
    Signals delivered: 0
    Page size (bytes): 4096
    Exit status: 0

通常,只是time一个更简单的shell内置阴影能力更强/usr/bin/time.

Answer 10

对于使用Jupyter Notebook的数据人员

在一个单元格中，可以使用 Jupyter 的%%time魔法命令来测量执行时间：

%%time
[ x**2 for x in range(10000)]

输出

%%time
[ x**2 for x in range(10000)]

这只会捕获特定单元格的执行时间。如果您想捕获整个笔记本（即程序）的执行时间，您可以在同一目录中创建一个新笔记本并在新笔记本中执行所有单元格：

假设上面的笔记本被称为example_notebook.ipynb。在同一目录中的新笔记本中：

# Convert your notebook to a .py script:
!jupyter nbconvert --to script example_notebook.ipynb

# Run the example_notebook with -t flag for time
%run -t example_notebook

输出

CPU times: user 4.54 ms, sys: 0 ns, total: 4.54 ms
Wall time: 4.12 ms

Answer 11

time.clock()

从版本3.3开始不推荐使用:此函数的行为取决于平台:根据您的要求,使用perf_counter()或process_time()来定义明确的行为.

time.perf_counter()

返回性能计数器的值(以小数秒为单位),即具有最高可用分辨率的时钟,以测量短持续时间.它确实包括睡眠期间经过的时间,并且是系统范围的.

time.process_time()

返回当前进程的系统和用户CPU时间总和的值(以小数秒为单位).它不包括睡眠期间经过的时间.

start = time.process_time()
... do something
elapsed = (time.process_time() - start)

Answer 12

以下代码段以一种漂亮的人类可读<HH:MM:SS>格式打印已用时间.

import time
from datetime import timedelta

start_time = time.time()

#
# Perform lots of computations.
#

elapsed_time_secs = time.time() - start_time

msg = "Execution took: %s secs (Wall clock time)" % timedelta(seconds=round(elapsed_time_secs))

print(msg)    

Answer 13

与@rogeriopvl 的响应类似，我添加了一个轻微的修改，使用相同的库将长时间运行的作业转换为小时分秒。

import time
start_time = time.time()
main()
seconds = time.time() - start_time
print('Time Taken:', time.strftime("%H:%M:%S",time.gmtime(seconds)))

样本输出

Time Taken: 00:00:08

Answer 14

我认为这是最好也是最简单的方法：

from time import monotonic

start_time = monotonic()
# something
print(f"Run time {monotonic() - start_time} seconds")

或者使用装饰器：

from time import monotonic
    
def record_time(function):
    def wrap(*args, **kwargs):
        start_time = monotonic()
        function_return = function(*args, **kwargs)
        print(f"Run time {monotonic() - start_time} seconds")
        return function_return
    return wrap

@record_time
def your_function():
    # something

Answer 15

只需使用timeit模块.它适用于Python 2和Python 3

import timeit

start = timeit.default_timer()

# All the program statements
stop = timeit.default_timer()
execution_time = stop - start

print("Program Executed in "+execution_time) # It returns time in seconds

它以秒为单位返回,您可以拥有执行时间.很简单但你应该在Main Function中编写这些函数来启动程序执行.如果你想获得执行时间,即使你得到错误,然后把你的参数"开始"给它并在那里计算

def sample_function(start,**kwargs):
     try:
         # Your statements
     Except:
         # Except statements
         stop = timeit.default_timer()
         execution_time = stop - start
         print("Program executed in " + execution_time)

Answer 16

后来回答，但我使用内置的timeit：

import timeit
code_to_test = """
a = range(100000)
b = []
for i in a:
    b.append(i*2)
"""
elapsed_time = timeit.timeit(code_to_test, number=500)
print(elapsed_time)
# 10.159821493085474

• 将所有代码（包括您可能拥有的任何导入）包装在code_to_test.
• number 参数指定代码应重复的次数。
• 演示

Answer 17

我尝试使用以下脚本发现时差。

import time

start_time = time.perf_counter()
[main code here]
print (time.perf_counter() - start_time, "seconds")

Answer 18

我看过timeit模块,但它似乎只适用于小代码片段.我想要整个计划的时间.

$ python -mtimeit -n1 -r1 -t -s "from your_module import main" "main()"

它运行一次your_module.main()功能,并使用time.time()函数作为计时器打印已用时间.

要/usr/bin/time在Python中模拟,请参阅使用/ usr/bin/time的Python子进程:如何捕获时序信息但忽略所有其他输出？.

要测量time.sleep()每个函数的CPU时间(例如,不包括时间),您可以使用profile模块(cProfile在Python 2上):

$ python3 -mprofile your_module.py

如果要使用与模块使用相同的计时器,可以传递-p给timeit上面的命令profile.

请参阅如何配置Python脚本？

Answer 19

Ipython"timeit"任何脚本:

def foo():
    %run bar.py
timeit foo()

Answer 20

from time import time
start_time = time()
...
end_time = time()
time_taken = end_time - start_time # time_taken is in seconds
hours, rest = divmod(time_taken,3600)
minutes, seconds = divmod(rest, 60)

Answer 21

我使用了一个非常简单的函数来计时一部分代码执行：

import time
def timing():
    start_time = time.time()
    return lambda x: print("[{:.2f}s] {}".format(time.time() - start_time, x))

而要使用它，只需在代码之前调用它来衡量检索函数的时间，然后在带有注释的代码之后调用该函数。时间会出现在评论前面。例如：

t = timing()
train = pd.read_csv('train.csv',
                        dtype={
                            'id': str,
                            'vendor_id': str,
                            'pickup_datetime': str,
                            'dropoff_datetime': str,
                            'passenger_count': int,
                            'pickup_longitude': np.float64,
                            'pickup_latitude': np.float64,
                            'dropoff_longitude': np.float64,
                            'dropoff_latitude': np.float64,
                            'store_and_fwd_flag': str,
                            'trip_duration': int,
                        },
                        parse_dates = ['pickup_datetime', 'dropoff_datetime'],
                   )
t("Loaded {} rows data from 'train'".format(len(train)))

然后输出将如下所示：

[9.35s] Loaded 1458644 rows data from 'train'

Answer 22

我在很多地方都遇到了同样的问题，所以我创建了一个便利包horology。您可以安装它，pip install horology然后以优雅的方式进行安装：

from horology import Timing

with Timing(name='Important calculations: '):
    prepare()
    do_your_stuff()
    finish_sth()

将输出：

Important calculations: 12.43 ms

或者更简单（如果你有一个功能）：

Important calculations: 12.43 ms

将输出：

main: 7.12 h

它负责单位和舍入。它适用于 python 3.6 或更新版本。

Answer 23

Timeit 是 Python 中的一个类，用于计算小块代码的执行时间。

Default_timer 是此类中的一个方法，用于测量挂钟计时，而不是 CPU 执行时间。因此其他流程执行可能会干扰这一点。因此它对于小代码块很有用。

代码示例如下：

from timeit import default_timer as timer

start= timer()

# Some logic

end = timer()

print("Time taken:", end-start)

Answer 24

首先，通过以管理员身份打开命令提示符（CMD）并在那里输入来安装人性化的包 - pip install humanfriendly

代码：

from humanfriendly import format_timespan
import time
begin_time = time.time()
# Put your code here
end_time = time.time() - begin_time
print("Total execution time: ", format_timespan(end_time))

输出：

Answer 25

有一个timeit模块可用于计算python代码的执行时间.它在python文档中有详细的文档和示例(https://docs.python.org/2/library/timeit.html)

Answer 26

我也喜欢Paul McGuire的答案,并提出了一个适合我更多需求的上下文管理器表单.

import datetime as dt
import timeit

class TimingManager(object):
    """Context Manager used with the statement 'with' to time some execution.

    Example:

    with TimingManager() as t:
       # Code to time
    """

    clock = timeit.default_timer

    def __enter__(self):
        """
        """
        self.start = self.clock()
        self.log('\n=> Start Timing: {}')

        return self

    def __exit__(self, exc_type, exc_val, exc_tb):
        """
        """
        self.endlog()

        return False

    def log(self, s, elapsed=None):
        """Log current time and elapsed time if present.
        :param s: Text to display, use '{}' to format the text with
            the current time.
        :param elapsed: Elapsed time to display. Dafault: None, no display.
        """
        print s.format(self._secondsToStr(self.clock()))

        if(elapsed is not None):
            print 'Elapsed time: {}\n'.format(elapsed)

    def endlog(self):
        """Log time for the end of execution with elapsed time.
        """
        self.log('=> End Timing: {}', self.now())

    def now(self):
        """Return current elapsed time as hh:mm:ss string.
        :return: String.
        """
        return str(dt.timedelta(seconds = self.clock() - self.start))

    def _secondsToStr(self, sec):
        """Convert timestamp to h:mm:ss string.
        :param sec: Timestamp.
        """
        return str(dt.datetime.fromtimestamp(sec))

Answer 27

使用line_profiler。

line_profiler将分析各个代码行执行所需的时间。剖析器通过Cython在C中实现，以减少分析的开销。

from line_profiler import LineProfiler
import random

def do_stuff(numbers):
    s = sum(numbers)
    l = [numbers[i]/43 for i in range(len(numbers))]
    m = ['hello'+str(numbers[i]) for i in range(len(numbers))]

numbers = [random.randint(1,100) for i in range(1000)]
lp = LineProfiler()
lp_wrapper = lp(do_stuff)
lp_wrapper(numbers)
lp.print_stats()

结果将是：

Timer unit: 1e-06 s

Total time: 0.000649 s
File: <ipython-input-2-2e060b054fea>
Function: do_stuff at line 4

Line #      Hits         Time  Per Hit   % Time  Line Contents
==============================================================
     4                                           def do_stuff(numbers):
     5         1           10     10.0      1.5      s = sum(numbers)
     6         1          186    186.0     28.7      l = [numbers[i]/43 for i in range(len(numbers))]
     7         1          453    453.0     69.8      m = ['hello'+str(numbers[i]) for i in range(len(numbers))]

Answer 28

您只需在 Python 中执行此操作。没有必要让它变得复杂。

import time

start = time.localtime()
end = time.localtime()
"""Total execution time in minutes$ """
print(end.tm_min - start.tm_min)
"""Total execution time in seconds$ """
print(end.tm_sec - start.tm_sec)

Answer 29

对于函数，我建议使用我创建的这个简单的装饰器。

def timeit(method):
    def timed(*args, **kwargs):
        ts = time.time()
        result = method(*args, **kwargs)
        te = time.time()
        if 'log_time' in kwargs:
            name = kwargs.get('log_name', method.__name__.upper())
            kwargs['log_time'][name] = int((te - ts) * 1000)
        else:
            print('%r  %2.22f ms' % (method.__name__, (te - ts) * 1000))
        return result
    return timed

@timeit
def foo():
    do_some_work()

# foo()
# 'foo'  0.000953 ms

Answer 30

遵循这个答案创建了一个简单但方便的仪器。

import time
from datetime import timedelta

def start_time_measure(message=None):
    if message:
        print(message)
    return time.monotonic()

def end_time_measure(start_time, print_prefix=None):
    end_time = time.monotonic()
    if print_prefix:
        print(print_prefix + str(timedelta(seconds=end_time - start_time)))
    return end_time

用法：

total_start_time = start_time_measure()    
start_time = start_time_measure('Doing something...')
# Do something
end_time_measure(start_time, 'Done in: ')
start_time = start_time_measure('Doing something else...')
# Do something else
end_time_measure(start_time, 'Done in: ')
end_time_measure(total_start_time, 'Total time: ')

输出：

Doing something...
Done in: 0:00:01.218000
Doing something else...
Done in: 0:00:01.313000
Total time: 0:00:02.672000