如果您想以微秒为单位测量时间，那么可以使用以下版本，完全基于Paul McGuire和Nicojo的答案——这是Python 3代码。我还为它添加了一些颜色：

import atexit
from time import time
from datetime import timedelta, datetime


def seconds_to_str(elapsed=None):
    if elapsed is None:
        return datetime.now().strftime("%Y-%m-%d %H:%M:%S.%f")
    else:
        return str(timedelta(seconds=elapsed))


def log(txt, elapsed=None):
    colour_cyan = '\033[36m'
    colour_reset = '\033[0;0;39m'
    colour_red = '\033[31m'
    print('\n ' + colour_cyan + '  [TIMING]> [' + seconds_to_str() + '] ----> ' + txt + '\n' + colour_reset)
    if elapsed:
        print("\n " + colour_red + " [TIMING]> Elapsed time ==> " + elapsed + "\n" + colour_reset)


def end_log():
    end = time()
    elapsed = end-start
    log("End Program", seconds_to_str(elapsed))


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

log（）=>打印定时信息的函数。

txt==>要记录的第一个参数及其用于标记计时的字符串。

atexit==>Python模块，用于注册程序退出时可以调用的函数。

我定义了以下Python装饰器：

def profile(fct):
  def wrapper(*args, **kw):
    start_time = time.time()
    ret = fct(*args, **kw)
    print("{} {} {} return {} in {} seconds".format(args[0].__class__.__name__,
                                                    args[0].__class__.__module__,
                                                    fct.__name__,
                                                    ret,
                                                    time.time() - start_time))
    return ret
  return wrapper

并将其用于函数或类/方法：

@profile
def main()
   ...

我在查找两种不同方法的运行时间时遇到的问题，这两种方法用于查找所有<=一个数的素数。当在程序中进行用户输入时。

错误的方法

#Sample input for a number 20 
#Sample output [2, 3, 5, 7, 11, 13, 17, 19]
#Total Running time = 0.634 seconds

import time

start_time = time.time()

#Method 1 to find all the prime numbers <= a Number

# Function to check whether a number is prime or not.
def prime_no(num):
if num<2:
    return False
else:
    for i in range(2, num//2+1):
        if num % i == 0:
            return False
    return True

#To print all the values <= n
def Prime_under_num(n):
    a = [2]
    if n <2:
        print("None")
    elif n==2:
        print(2)
    else:
"Neglecting all even numbers as even numbers won't be prime in order to reduce the time complexity."
        for i in range(3, n+1, 2):   
            if prime_no(i):
                a.append(i)
        print(a)


"When Method 1 is only used outputs of running time for different inputs"
#Total Running time = 2.73761 seconds #n = 100
#Total Running time = 3.14781 seconds #n = 1000
#Total Running time = 8.69278 seconds #n = 10000
#Total Running time = 18.73701 seconds #n = 100000

#Method 2 to find all the prime numbers <= a Number

def Prime_under_num(n):
    a = [2]
    if n <2:
        print("None")
    elif n==2:
        print(2)
    else:
        for i in range(3, n+1, 2):   
            if n%i ==0:
                pass
            else:
                a.append(i)
        print(a)

"When Method 2 is only used outputs of running time for different inputs"
# Total Running time = 2.75935 seconds #n = 100
# Total Running time = 2.86332 seconds #n = 1000
# Total Running time = 4.59884 seconds #n = 10000
# Total Running time = 8.55057 seconds #n = 100000

if __name__ == "__main__" :
    n = int(input())
    Prime_under_num(n)
    print("Total Running time = {:.5f} seconds".format(time.time() - start_time))

上述所有情况下获得的不同运行时间都是错误的。对于我们正在接受输入的问题，我们必须在接受输入后才开始计时。这里，用户键入输入所花费的时间也与运行时间一起计算。

正确的方法

我们必须从开头删除start_time=time.time（）并将其添加到主块中。

if __name__ == "__main__" :
    n = int(input())
    start_time = time.time()
    Prime_under_num(n)
    print("Total Running time = {:.3f} seconds".format(time.time() - start_time))

因此，两种方法单独使用时的输出如下：-

# Method 1

# Total Running time = 0.00159 seconds #n = 100
# Total Running time = 0.00506 seconds #n = 1000
# Total Running time = 0.22987 seconds #n = 10000
# Total Running time = 18.55819 seconds #n = 100000

# Method 2

# Total Running time = 0.00011 seconds #n = 100
# Total Running time = 0.00118 seconds #n = 1000
# Total Running time = 0.00302 seconds #n = 10000
# Total Running time = 0.01450 seconds #n = 100000

现在我们可以看到，与错误方法相比，总运行时间有显著差异。即使方法2在两种方法中的性能优于方法1，但第一种方法（错误方法）是错误的。

有一个timeit模块，可用于对Python代码的执行时间进行计时。

它在Python文档26.6中有详细的文档和示例。timeit-测量小代码片段的执行时间。

首先，以管理员身份打开命令提示符（CMD）并在那里键入，安装人性化的软件包-pip安装人性化

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：

我尝试使用以下脚本找到时间差。

import time

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