list dict 性能测试

from random import randint


def load_list_data(total_nums, target_nums):
    """
    从文件中读取数据,以list的方式返回
    :param total_nums: 读取的数量
    :param target_nums: 需要查询的数据的数量
    """
    all_data = []
    target_data = []
    file_name = "fbobject_idnew.txt"
    with open(file_name, encoding="utf8", mode="r") as f_open:
        for count, line in enumerate(f_open):
            if count < total_nums:
                all_data.append(line)
            else:
                break

    for x in range(target_nums):
        random_index = randint(0, total_nums)
        if all_data[random_index] not in target_data:
            target_data.append(all_data[random_index])
            if len(target_data) == target_nums:
                break

    return all_data, target_data

def load_dict_data(total_nums, target_nums):
    """
    从文件中读取数据,以dict的方式返回
    :param total_nums: 读取的数量
    :param target_nums: 需要查询的数据的数量
    """
    all_data = {}
    target_data = []
    file_name = "fbobject_idnew.txt"
    with open(file_name, encoding="utf8", mode="r") as f_open:
        for count, line in enumerate(f_open):
            if count < total_nums:
                all_data[line] = 0
            else:
                break
    all_data_list = list(all_data)
    for x in range(target_nums):
        random_index = randint(0, total_nums-1)
        if all_data_list[random_index] not in target_data:
            target_data.append(all_data_list[random_index])
            if len(target_data) == target_nums:
                break

    return all_data, target_data


def find_test(all_data, target_data):
    #测试运行时间
    test_times = 100
    total_times = 0
    import time
    for i in range(test_times):
        find = 0
        start_time = time.time()
        for data in target_data:
            if data in all_data:
                find += 1
        last_time = time.time() - start_time
        total_times += last_time
    return total_times/test_times


if __name__ == "__main__":
    # all_data, target_data = load_list_data(10000, 1000)
    # all_data, target_data = load_list_data(100000, 1000)
    # all_data, target_data = load_list_data(1000000, 1000)


    # all_data, target_data = load_dict_data(10000, 1000)
    # all_data, target_data = load_dict_data(100000, 1000)
    # all_data, target_data = load_dict_data(1000000, 1000)
    all_data, target_data = load_dict_data(2000000, 1000)
    last_time = find_test(all_data, target_data)

    #dict查找的性能远远大于list
    #在list中随着list数据的增大 查找时间会增大
    #在dict中查找元素不会随着dict的增大而增大
    print(last_time)
不可变对象 都是可hash的, str, fronzenset, tuple,自己实现的类 __hash__
dict的内存花销大,但是查询速度快, 自定义的对象 或者python内部的对象都是用dict包装的

查找效率:set>dict>list

单次查询中:看来list 就是O(n)的;而set做了去重,本质应该一颗红黑树(猜测,STL就是红黑树),复杂度O(logn);dict类似对key进行了hash,然后再对hash生成一个红黑树进行查找,其查找复杂其实是O(logn),并不是所谓的O(1)。O(1)只是理想的实现,实际上很多hash的实现是进行了离散化的。dict比set多了一步hash的过程,so 它比set慢,不过差别不大。

posted @ 2019-06-24 08:55  Richie`  阅读(...)  评论(... 编辑 收藏