我如何使用timeit来比较我自己的函数(如“insertion_sort”和“tim_sort”)的性能?


当前回答

# Генерация целых чисел

def gen_prime(x):
    multiples = []
    results = []
    for i in range(2, x+1):
        if i not in multiples:
            results.append(i)
            for j in range(i*i, x+1, i):
                multiples.append(j)

    return results


import timeit

# Засекаем время

start_time = timeit.default_timer()
gen_prime(3000)
print(timeit.default_timer() - start_time)

# start_time = timeit.default_timer()
# gen_prime(1001)
# print(timeit.default_timer() - start_time)

其他回答

内置的timeit模块在IPython命令行中工作得最好。

为模块内的函数计时:

from timeit import default_timer as timer
import sys

def timefunc(func, *args, **kwargs):
    """Time a function. 

    args:
        iterations=3

    Usage example:
        timeit(myfunc, 1, b=2)
    """
    try:
        iterations = kwargs.pop('iterations')
    except KeyError:
        iterations = 3
    elapsed = sys.maxsize
    for _ in range(iterations):
        start = timer()
        result = func(*args, **kwargs)
        elapsed = min(timer() - start, elapsed)
    print(('Best of {} {}(): {:.9f}'.format(iterations, func.__name__, elapsed)))
    return result

让我们在以下每个语句中设置相同的字典并测试执行时间。

setup参数基本上是设置字典

编号是运行代码1000000次。不是设置,而是stmt

当你运行这个时,你会发现index比get快得多。您可以多次运行它来查看。

这段代码基本上是试图从字典中获取c的值。

import timeit

print('Getting value of C by index:', timeit.timeit(stmt="mydict['c']", setup="mydict={'a':5, 'b':6, 'c':7}", number=1000000))
print('Getting value of C by get:', timeit.timeit(stmt="mydict.get('c')", setup="mydict={'a':5, 'b':6, 'c':7}", number=1000000))

这是我的结果,你的结果会有所不同。

按索引:0.20900007452246427

get: 0.54841166886888

如果你想在交互式Python会话中使用timeit,有两个方便的选项:

Use the IPython shell. It features the convenient %timeit special function: In [1]: def f(x): ...: return x*x ...: In [2]: %timeit for x in range(100): f(x) 100000 loops, best of 3: 20.3 us per loop In a standard Python interpreter, you can access functions and other names you defined earlier during the interactive session by importing them from __main__ in the setup statement: >>> def f(x): ... return x * x ... >>> import timeit >>> timeit.repeat("for x in range(100): f(x)", "from __main__ import f", number=100000) [2.0640320777893066, 2.0876040458679199, 2.0520210266113281]

# Генерация целых чисел

def gen_prime(x):
    multiples = []
    results = []
    for i in range(2, x+1):
        if i not in multiples:
            results.append(i)
            for j in range(i*i, x+1, i):
                multiples.append(j)

    return results


import timeit

# Засекаем время

start_time = timeit.default_timer()
gen_prime(3000)
print(timeit.default_timer() - start_time)

# start_time = timeit.default_timer()
# gen_prime(1001)
# print(timeit.default_timer() - start_time)

如果你想快速比较两个代码/函数块,你可以这样做:

import timeit

start_time = timeit.default_timer()
func1()
print(timeit.default_timer() - start_time)

start_time = timeit.default_timer()
func2()
print(timeit.default_timer() - start_time)