我有一个Python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timeit模块,但它似乎只适用于小代码片段。我想给整个节目计时。


当前回答

使用line_profiler。

line_profiler将描述单个代码行执行所需的时间。分析器通过Cython在C语言中实现,以减少分析开销。

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))]

其他回答

我认为这是最好和最简单的方法:

from time import monotonic

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

或与装饰师一起:

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

这是保罗·麦奎尔的回答,对我来说很有用。以防有人在运行这个问题时遇到问题。

import atexit
from time import clock

def reduce(function, iterable, initializer=None):
    it = iter(iterable)
    if initializer is None:
        value = next(it)
    else:
        value = initializer
    for element in it:
        value = function(value, element)
    return value

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)

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

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

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

导入文件后,从程序中调用timing.main()。

我使用来自ttictoc的tic和toc。

pip install ttictoc

然后可以在脚本中使用:

from ttictoc import tic,toc
tic()

# foo()

print(toc())

Python程序执行度量的时间可能不一致,具体取决于:

可以使用不同的算法评估相同的程序运行时间因算法而异运行时间因实现而异运行时间因计算机而异基于小输入,运行时间不可预测

这是因为最有效的方法是使用“增长顺序”,并学习大“O”符号来正确地执行。

无论如何,您可以尝试使用以下简单算法来评估任何Python程序在每秒特定机器计数步骤中的性能:使其适应您想要评估的计划

import time

now = time.time()
future = now + 10
step = 4 # Why 4 steps? Because until here already four operations executed
while time.time() < future:
    step += 3 # Why 3 again? Because a while loop executes one comparison and one plus equal statement
step += 4 # Why 3 more? Because one comparison starting while when time is over plus the final assignment of step + 1 and print statement
print(str(int(step / 10)) + " steps per second")

我很喜欢保罗·麦奎尔的答案,但我使用的是Python 3。因此,对于感兴趣的人来说:这里是他在*nix上使用Python 3的答案的修改(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,你仍然应该投票给他的答案,而不是这一个,因为他做了大部分工作;)。