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(1) 无序性
(2) 确定性
(3) 不重复性
内部进行 可迭代性的 for 循环
例子：
2.1.1 增
计算
安全
数据库
网络和加速
企业服务
add(self, *args, **kwargs)
copy(self, *args, **kwargs)# 1. 增
# Add an element to a set. This has no effect if the element is already present.
s = {1, 12, 32, "涟漪", "hello"}
s.add("good")
s.add(32)
print(s)
# Add an element to a set. This has no effect if the element is already present.
s = {1, 12, 32, "涟漪", "hello"}
c = s.copy()
print(c)结果：
2.1.1 删
clear(self, *args, **kwargs)
pop(self, *args, **kwargs)
remove(self, *args, **kwargs)
discard(self, *args, **kwargs)# 2. 删
# Remove all elements from this set.
s = {1, 12, 32, "涟漪", "hello"}
s.clear()
print(s)
# Remove and return an arbitrary set element. Raises KeyError if the set is empty.
s = {1, 12, 32, "涟漪", "hello"}
s.pop()
print(s)
# Remove an element from a set; it must be a member. If the element is not a member, raise a KeyError.
s = {1, 12, 32, "涟漪", "hello"}
s.remove(1)
# s.remove("good")
print(s)
# Remove an element from a set if it is a member. If the element is not a member, do nothing.
s = {1, 12, 32, "涟漪", "hello"}
s.discard(1)
s.discard("good")
print(s)结果：
pop() 是随机删除。
remove() 和 discard() 指定删除，但是指定不存在的元素时，remove() 会报错，而 discard() 不会报错
2.2.1 set 交集运算
# set 交集运算
x1 = ["a", "b", "c", "d", "e"]
x2 = ["c", "d", "e", "f", "g"]
x3 = []
for x in x1:
if x in x2:
x3.append(x)
print(x3)
s_x1 = set(x1)
s_x2 = set(x2)
inter = s_x1.intersection(s_x2)
print(inter)
# 交集符号运算
print(s_x1 & s_x2)
# update
s_x1.intersection_update(s_x2)
print(s_x1)结果：
2.2.2 set 并集运算
# set 并集运算
x1 = ["a", "b", "c", "d", "e"]
x2 = ["c", "d", "e", "f", "g"]
s_x1 = set(x1)
s_x2 = set(x2)
uni = s_x1.union(s_x2)
print(uni)
# 并集符号运算
print(s_x1 | s_x2)
# update
s_x1.update(s_x2)
print(s_x1)结果：
2.2.3 set 差集运算
# set 差集运算
x1 = ["a", "b", "c", "d", "e"]
x2 = ["c", "d", "e", "f", "g"]
s_x1 = set(x1)
s_x2 = set(x2)
dif_x1 = s_x1.difference(s_x2)
print(dif_x1)
dif_x2 = s_x2.difference(s_x1)
print(dif_x2)
# 差集符号运算
print(s_x1 - s_x2)
print(s_x2 - s_x1)
# update
s_x1.difference_update(s_x2)
print(s_x1)
s_x2.difference_update(s_x1)
print(s_x2)结果：
2.2.4 set 对称差集运算
# set 对称差集运算满足交换律：A△B = B△A
s_x1 = set(x1)
s_x2 = set(x2)
sym = s_x1.symmetric_difference(s_x2)
print(sym)
# 对称差集符号运算
print(s_x1 ^ s_x2)
print(s_x1 - s_x2 | s_x2 - s_x1)
print((s_x1 | s_x2) - (s_x2 & s_x1))
# update
s_x1.symmetric_difference_update(s_x2)
print(s_x1)结果：
2.2.5 set 逻辑判断运算
# 判断
# Return True if two sets have a null intersection.
x1 = {"a", "b", "c"}
x2 = {"e", "f", "g"}
inter = x1.isdisjoint(x2)
print(inter)
# Report whether another set contains this set.
x1 = {"a", "b", "c"}
x2 = {"a", "b", "c", "e", "f", "g"}
inter = x1.issubset(x2)
print(inter)
# Report whether this set contains another set.
x1 = {"a", "b", "c", "e", "f", "g"}
x2 = {"a", "b", "c"}
inter = x1.issuperset(x2)
print(inter)结果：
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原文链接：https://blog.csdn.net/YKenan/article/details/88357847
