Python3-笔记-B-002-数据结构-字典dict{ }

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def dics():
    # --- 字典 ----
    # 创建(由 键值对(key:value) 组成)
    dics = {1: "a", 2: "b", 3: "c"}
    dics = dict()  # 创建空字典
    dics = dict([(1, "a"), (2, "b")])  # (序列)转为字典 (列表序列: dict([[1, "a"], [2, "b"]]); 元组列表: dict(((1, "a"), (2, "b"))))
    dics = dict(a=1, b=2)  # (注: 格式固定, 字母 = 数字, 字母不能加"号) # => {‘a‘: 1, ‘b‘: 2}
    dics = {chr(x): x for x in range(65, 80)}

    # 获取
    dics = {1: "a", 2: "b", 3: "c"}
    strs = dics[1]  # 按key取value, 没有对应key时抛异常(注意)
    strs = dics.get(1)  # 按key获取value
    strs = dics.get(5, -1)  # -1 为没有该key的返回
    strs = dics.setdefault(50)  # 按key取value, key不存在则添加,value为None
    strs = dics.setdefault(12, -1)  # -1为不存在key时,添加的value为-1 {1: ‘a‘, 2: ‘b‘, 3: ‘c‘, 50: None, 12: -1}
    keys = dics.keys()  # 所有key, dict_keys([1, 2, 3, 50, 12])
    values = dics.values()  # 所有value, dict_values([‘a‘, ‘b‘, ‘c‘, None, -1])
    kevaList = dics.items() # 获取(key,value)列表,格式为[(key1, value1), (key2, value2)], dict_items([(1, ‘a‘), (2, ‘b‘), (3, ‘c‘), (50, None), (12, -1)])
    dics2 = dics.copy()  # 浅拷贝
    dics3 = dics.fromkeys(dics)  # 根据字典所有key创建新字典,value为None, {1: None, 2: None, 3: None, 50: None, 12: None}
    dics4 = dics.fromkeys(dics, -1)  # -1为创建的新字典,value为-1, {1: -1, 2: -1, 3: -1, 50: -1, 12: -1}

    # 查找
    key = min(dics)  # 最小键
    key = max(dics)  # 最大键

# 添加
dics.update({4: "d", 5: "f"})  # 添加字典 {1: ‘a‘, 2: ‘b‘, 3: ‘c‘, 50: None, 12: -1, 4: ‘d‘, 5: ‘f‘}


# 修改
dics[1] = "c"  # {1: ‘c‘, 2: ‘b‘, 3: ‘c‘, 50: None, 12: -1, 4: ‘d‘, 5: ‘f‘}

# 删除
del dics[1]  # 删除 键1 (注意)
dics4.clear()  # 清空
strs = dics.pop(3)  # 删除,返回被删的元素(注意:同key同时删)
strs = dics.pop(5, -1)  # -1 为没有该key时的返回
pul = dics.popitem()  # 删除键值对,返回被删的元组(末尾起删)

# 统计
length = len(dics)  # 字典长度

# 判断
boolean = 1 in dics  # 该key是否在字典中存在
boolean = 1 not in dics  # 该key是否不在字典中存在

# 遍历

for key, value in dics.items(): 　　
　　print("key:%d value:%s" % (key, value))

# 排序
lists = sorted(dics)  # 注:返回排序后的键列表

Python3-笔记-B-002-数据结构-字典dict{ }

标签：ems   span   none   获取   不能   val   soft   字典   数字   

原文地址：http://www.cnblogs.com/vito13/p/7729951.html