6.1 collections中的abc

from collections.abc import Mapping, MutableMapping #dict屬于mapping類型a = {} print (isinstance(a, MutableMapping)) # True

6.2 dict的常見用法

a = {"lewen1": {"company": "imooc"},"lewen2": {"company": "imooc2"}} # clear Remove all items from D. # a.clear() # pass ? # copy, 返回淺拷貝 new_dict = a.copy() new_dict["lewen1"]["company"] = "imooc3" # 淺拷貝，只是拷貝了指向。這里修改會修改了a 中原來的值 print(new_dict) print(a) ? ?--- {'lewen1': {'company': 'imooc3'}, 'lewen2': {'company': 'imooc2'}} {'lewen1': {'company': 'imooc3'}, 'lewen2': {'company': 'imooc2'}} --- import copy a = {"lewen1": {"company": "imooc"},"lewen2": {"company": "imooc2"}} new_dict = copy.deepcopy(a) # 深拷貝，開辟獨立的內存空間，并復制值 new_dict["lewen1"]["company"] = "imooc3" # 這里修改，并不會影響字典a的值 print(new_dict) print(a) --- {'lewen1': {'company': 'imooc3'}, 'lewen2': {'company': 'imooc2'}} {'lewen1': {'company': 'imooc'}, 'lewen2': {'company': 'imooc2'}} --- ? # formkeys new_list = ["lewen1", "lewen2"] new_dict = dict.fromkeys(new_list, {"company": "imooc"}) print(new_dict) ? # new_dict["kevin"] # KeyError 不存在會拋異常 ret = new_dict.get("kevin","None") # print(ret) ? # items 方法 for key,value in new_dict.items():print(key,value)ret_set = new_dict.setdefault("kevin","new mem") # 不存在key,就設置并返回值 print(ret_set) print(new_dict) ? ?new_dict.update( # update() 括號里面添加為可迭代對象(("lewen", "imooc"),)) --- {'lewen1': {'company': 'imooc'}, 'lewen2': {'company': 'imooc'}} None lewen1 {'company': 'imooc'} lewen2 {'company': 'imooc'} new mem {'lewen1': {'company': 'imooc'}, 'lewen2': {'company': 'imooc'}, 'kevin': 'new mem'} ?

6.3 dict的子類

#不建議繼承list和dict class Mydict(dict):def __setitem__(self, key, value):super().__setitem__(key, value*2)my_dict = Mydict(one=1) # value*2 沒有生效 # my_dict["one"] = 1 # 生效了 print (my_dict) {'one': 1} --- from collections import UserDict class Mydict(UserDict):def __setitem__(self, key, value):super().__setitem__(key, value*2)my_dict = Mydict(one=1) # my_dict["one"] = 1 print (my_dict) {'one': 2} --- # defaultdict from collections import defaultdict my_dict = defaultdict(dict) my_value = my_dict["bobby"] # 沒有則返回空字典 print(my_value) {}

6.4 set和frozenset

#set 集合 fronzenset (不可變集合) 無序， 不重復 s = set('abcdee') print(s)s2 = set(['a','b','c','d','e']) print(s2)s3 = {'a','b', 'c'} print(type(s3))s = frozenset("abcde") #frozenset 不可變，以作為dict的key# 不能添加值 print(s) # --- {'a', 'e', 'c', 'd', 'b'} {'a', 'e', 'c', 'd', 'b'} <class 'set'> frozenset({'a', 'e', 'c', 'd', 'b'}) # --- #向set添加數據 s = set('abcdee') another_set = set("cef") s.update(another_set) print(s)re_set = s.difference(another_set) # {'b', 'd', 'a'} re_set = s - another_set # {'b', 'd', 'a'} re_set = s & another_set # {'c', 'f', 'e'} re_set = s | another_set # {'a', 'f', 'c', 'e', 'd', 'b'}#set性能很高 # | & - #集合運算 print(re_set)print (s.issubset(re_set)) if "c" in re_set:print ("i am in set") # --- {'a', 'f', 'e', 'c', 'd', 'b'} {'a', 'f', 'c', 'e', 'd', 'b'} True i am in set

6.5 dict和set實現原理

from random import randintdef load_list_data(total_nums, target_nums):"""從文件中讀取數據，以list的方式返回:param total_nums: 讀取的數量:param target_nums: 需要查詢的數據的數量"""all_data = []target_data = []file_name = "D:\電子書\Python面試寶典Version8.1.pdf"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:breakfor 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:breakreturn all_data, target_datadef load_dict_data(total_nums, target_nums):"""從文件中讀取數據，以dict的方式返回:param total_nums: 讀取的數量:param target_nums: 需要查詢的數據的數量"""all_data = {}target_data = []file_name = "D:\電子書\Python面試寶典Version8.1.pdf"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] = 0else:breakall_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:breakreturn all_data, target_datadef find_test(all_data, target_data):#測試運行時間test_times = 100total_times = 0import timefor i in range(test_times):find = 0start_time = time.time()for data in target_data:if data in all_data:find += 1last_time = time.time() - start_timetotal_times += last_timereturn total_times/test_timesif __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) view #dict查找的性能遠遠大于list#在list中隨著list數據的增大 查找時間會增大#在dict中查找元素不會隨著dict的增大而增大print(last_time)#1.dict的key或者set的值 都必須是可以hash的 #不可變對象 都是可hash的， str， fronzenset， tuple，自己實現的類 __hash__ #2. dict的內存花銷大(有大量空余的表元)，但是查詢速度快， 自定義的對象 或者python內部的對象都是用dict包裝的 # 3. dict的存儲順序和元素添加順序有關 # 4. 添加數據有可能改變已有數據的順序

哈希沖突后重新計算位置

在剩余空間小于三分之一時，申請更大的空間，然后數據搬遷，有可能會改變順序

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