如何在 Visual Studio 代码中查看 运行 我的程序所花费的时间?

How do I see the time it took to run my program in Visual Studio Code?

有没有办法查看脚本在 VS Code 中 execute/complete 花费了多长时间?

我正在寻找这样的消息:

Program finished in 30ms

实现此目的的最简单方法是纯粹编码时间来编程。

from time import time

start_time = time()

main() # n staffs

passed_time = time() - start_time

print(f"It took {passed_time}")

使用'time'

脚本启动时:

import time
start_time = time.time()

do something # here your actual code/routine

print("Process finished --- %s seconds ---" % (time.time() - start_time))

您可以创建一个简单的装饰器函数来为您的函数计时。

import time

def decoratortimer(decimal):
    def decoratorfunction(f):
        def wrap(*args, **kwargs):
            time1 = time.monotonic()
            result = f(*args, **kwargs)
            time2 = time.monotonic()
            print('{:s} function took {:.{}f} ms'.format(f.__name__, ((time2-time1)*1000.0), decimal ))
            return result
        return wrap
    return decoratorfunction

@decoratortimer(2)
def callablefunction(name):
    print(name)
print(callablefunction('John'))

我建议使用time.monotonic(这是一个不会倒退的时钟)来提高准确性。

为了找到你的函数 运行 时间更喜欢 time.perf_counter() 而不是 time.time()。 详情见下方link

Understanding time.perf_counter() and time.process_time()

您可以使用类似这样的方法创建您自己的自定义计时器

from time import perf_counter

def f(a1,a2):
    return a1 * a2

def timer(f,*args):
    start = perf_counter()
    f(*args)
    return (1000 * (perf_counter()-start)) # this returns time in ms 

a1 = np.random.rand(100)
a2 = np.random.rand(100)

np.mean([timer(f,a1,a2) for _ in range(100)]) # average out result for 100 runs

如果您使用的是 jupyter notebook,请使用以下命令

%%timeit
f(a1,a2)