python应用中一个具体问题的效率对比

"""在处理撮合的逻辑中，有这样一个问题：以买入委托队列为例：需要维护一个价格由高到低的价格顺序。对这个价格顺序下有以下两种方案：1. 使用list2. 使用deque"""import randomimport timeitfrom collections import dequedef random_int_list(start, stop, length):    start, stop = (int(start), int(stop)) if start <= stop else (int(stop), int(start))    length = int(abs(length)) if length else 0    random_list = []    for i in range(length):        random_list.append(random.randint(start, stop))    return random_list    def test_list(_p_list):    """    List方案, 完全使用list，不借助其它手段    """    p_list = []    for p_in in _p_list:        if p_in not in p_list:            idx = 0            for p in p_list:                if p_in > p:                    break                idx += 1            p_list.insert(idx, p_in)        pass    return p_list        def test_list_withset(_p_list):    """    List方案，借助一个set，来加速 if not in判断    """    p_list = []    p_set = set()    for p_in in _p_list:        if p_in not in p_set:            idx = 0            for p in p_list:                if p_in > p:                    break                idx += 1            p_list.insert(idx, p_in)            p_set.add(p_in)        pass    return p_listdef test_list_withset_next(_p_list):    """    List方案，借助一个set，来加速if not in判断；使用next函数来查找第一个符合条件的元素    参考http://stackoverflow.com/questions/2361426/what-is-the-best-way-to-get-the-first-item-from-an-iterable-matching-a-condition    中提到的first_index = next(index for index, value in enumerate(the_iterable) if condition(value))    """    p_list = []    p_set = set()    for p_in in _p_list:        if p_in not in p_set:            first_index = next((index for index, value in enumerate(p_list) if p_in > value), len(p_list))            p_list.insert(first_index, p_in)            p_set.add(p_in)        pass    return p_list    def test_list_withset_sort(_p_list):    """    List方案    不自己维护排序，借助一个set，来加速if not in判断； 每次插入都排序    """    p_list = []    p_set = set()    for p_in in _p_list:        if p_in not in p_set:            p_list.append(p_in)            p_list.sort(reverse=True)            p_set.add(p_in)        pass    return p_list        def test_queue(_p_list):    """    deque方案    """    p_queue = deque()    for p_in in _p_list:        if p_in not in p_queue:            idx = 0            for p in p_queue:                if p_in > p:                    break                idx += 1            p_queue.insert(idx, p_in)        pass    return p_queue    def test_queue_withset(_p_list):    """    deque方案    """    p_queue = deque()    p_set = set()    for p_in in _p_list:        if p_in not in p_set:            idx = 0            for p in p_queue:                if p_in > p:                    break                idx += 1            p_queue.insert(idx, p_in)            p_set.add(p_in)        pass    return p_queue    if __name__=='__main__':    # 模拟价格区间在9~11元的随机值    random_price_list = random_int_list(90000, 110000, 10000)        p_list = test_list(random_price_list)    p_list2 = test_list(random_price_list)    p_queue = test_queue(random_price_list)        print(p_list[0], p_list[-1], p_list2[0], p_list2[-1], p_queue[0], p_queue[-1])        print(timeit.timeit('test_list(random_price_list)', number=10, globals=globals()))    print(timeit.timeit('test_list_withset(random_price_list)', number=10, globals=globals()))    print(timeit.timeit('test_list_withset_next(random_price_list)', number=10, globals=globals()))    print(timeit.timeit('test_list_withset_sort(random_price_list)', number=10, globals=globals()))        print(timeit.timeit('test_queue(random_price_list)', number=10, globals=globals()))    print(timeit.timeit('test_queue_withset(random_price_list)', number=10, globals=globals()))    

以下是输出结果：

109999 90000 109999 90000 109999 90000
22.2045529369317
16.38033776747557
15.252241216916637
8.420866390707168
26.823208546270322
18.25433301937217

可以看出使用test_list_withset_sort是最快的！

也请大家帮忙看看是否还有更好的方案，谢谢！