import time
from functools import reduce
def performance(f):
def fn(*args, **kw):
a1 = time.time()
t1 = time.clock()
r = f(*args, **kw)
t2 = time.clock()
a2 = time.time()
print('call %s() in %fs' % (f.__name__,(t2 - t1)))
print('test time.time: %fs' % (a2 - a1))
return r
return fn
print('*'*20)
@performance
def factorial(n):
return reduce(lambda x,y: x*y, range(1, n+1))
print(factorial(10000))
一，两个函数的文档： 1，time.time(): time.time() Return the time in seconds since the epoch as a floating point number. Note that even though the time is always returned as a floating point number, not all systems provide time with a better precision than 1 second. While this function normally returns non-decreasing values, it can return a lower value than a previous call if the system clock has been set back between the two calls. time.time() 返回从（1970.1.1）至今的秒数。虽然这个函数的返回值永远为浮点数，但并不是所有系统提供的秒数都会精确到小数点以后。一般情况下这个函数的返回值不会小于它上一次被调用的返回值，除非在两次调用之间发生了重置。 2，time.clock(): time.clock() On Unix, return the current processor time as a floating point number expressed in seconds. The precision, and in fact the very definition of the meaning of “processor time”, depends on that of the C function of the same name, but in any case, this is the function to use for benchmarking Python or timing algorithms. On Windows, this function returns wall-clock seconds elapsed since the first call to this function, as a floating point number, based on the Win32 function QueryPerformanceCounter(). The resolution is typically better than one microsecond. time.clock() 在Unix 中，将当前的处理器时间以浮点数的形式返回，单位为秒。它的精确度（准确地说是“处理器时间”的精确度）取决于同名的C函数，无论如何，这个函数是python关于时间计算的标尺。 WINDOWS中，第一次调用，返回的是进程运行的实际时间。而第二次之后的调用是自第一次调用以后到现在的运行时间。（实际上是以WIN32上QueryPerformanceCounter()为基础，它比表示更为精确） 二，用法及总结 1，在Windows中，time.clock()更精确； 2，这两个函数不可以混合使用