一.散列表（Hash Table）
1.用来实现字典操作的一组有效数据结构
2.直接寻址表（直接寻址）：数组T[0...m-1]，可以存放动态集合的元素
1 class direct_address_table: 2 ‘‘‘直接寻址表‘‘‘ 3 def __init__(self, T=[], size=0): 4 if len(T) == 0: 5 self.T = [None for i in range(size)] 6 else: 7 self.T = T 8 self.size = size 9 ‘‘‘对于节点‘‘‘ 10 def search(self, k): 11 return self.T[k] 12 13 def insert(self, x): 14 self.T[x.key] = x 15 16 def delete(self, x): 17 self.T[x.key] = None 18 19 class Node: 20 def __init__(self, key): 21 self.key = key 22 23 T=[] 24 dat=direct_address_table(T,10) 25 x=Node(2) 26 print(dat.insert(x))
3.散列表：利用散列函数（hash function）h，把原来具有关键字k的元素存放在槽k中变成该元素放在h(k)中
冲突：两个关键字映射到同一个槽中
1 class chained_hash: 2 ‘‘‘链接法散列，查找和插入时都要判断槽中有没有元素‘‘‘ 3 def __init__(self, T=[], size=0): 4 if len(T) == 0: 5 self.T = [None for i in range(size)] 6 else: 7 self.T = T 8 self.size = size 9 def search(self, k): 10 if self.T[self.hash_h(k)] != None: 11 x = self.T[self.hash_h(k)].list_search(k) 12 return x 13 return None 14 def insert(self, x): 15 if self.T[self.hash_h(x.key)] == None: 16 self.T[self.hash_h(x.key)] = DoublyLinkedList(x) 17 else: 18 self.T[self.hash_h(x.key)].list_insert(x) 19 def delete(self, x): 20 self.T[self.hash_h(x.key)].list_delete(x) 21 def hash_h(self, key): 22 ‘‘‘hash函数‘‘‘ 23 return key % 12 24 25 class Node: 26 def __init__(self, key): 27 self.key = key 28 class DoublyNode: 29 def __init__(self, n_prev, n_next, key): 30 self.prev = n_prev 31 self.next = n_next 32 self.key = key 33 34 class DoublyLinkedList: 35 def __init__(self, head): 36 self.head = head 37 38 def list_search(self, k): 39 x = self.head 40 while x != None and x.key != k: 41 x = x.next 42 return x 43 44 def list_insert(self, x): 45 x.next = self.head 46 if self.head != None: 47 self.head.prev = x 48 self.head = x 49 x.prev = None 50 51 def list_delete(self, x): 52 if x.prev != None: 53 x.prev.next = x.next 54 else: 55 self.head = x.next 56 if x.next != None: 57 x.next.prev = x.prev 58 59 T=[] 60 x=DoublyNode(None,None,13) 61 ch=chained_hash(T,12) 62 ch.insert(x) 63 x=DoublyNode(None,None,25) 64 ch.insert(x) 65 y=ch.search(25) 66 print(y.key) 67 68 ch.delete(y) 69 print(ch.T[1].head) 70 print(ch.T[1].head.key) 71 print(ch.T[1].head.next) 72 ----------------------------------------- 73 25 74 <__main__.DoublyNode object at 0x039C78B0> 75 13 76 None
散列函数的选择：1）除法散列法：h(k)=k mod m ;2)乘法散列法：h(k)=[m(kA mod 1)] ; 3)全域散列法
（2）开放寻址法：所有元素都存放在散列表中，通过探查，找到空槽放置关键字
1 class open_address_hash: 2 ‘‘‘开放寻址散列，散列表T和一个关键字k‘‘‘ 3 def __init__(self, T=[], size=0): 4 if len(T) == 0: 5 self.T = [None for i in range(size)] 6 else: 7 self.T = T 8 self.size = size 9 10 def hash_insert(self, k): 11 ‘‘‘插入关键字k，返回k的插槽或已满标志‘‘‘ 12 i = 0 13 while i < self.size: 14 j = self.hash_h1_h2(k, i)#搜寻空槽并插入 15 if self.T[j] == None: 16 self.T[j] = k 17 return j 18 else: 19 i += 1 20 return "hash table overflow" 21 22 def hash_search(self, k): 23 ‘‘‘查找，如果槽j包含了关键字k，则返回j，否则返回NOne‘‘‘ 24 i = 0 25 j = self.hash_h1_h2(k, i) 26 while self.T[j] != None and i < self.size: 27 j = self.hash_h1_h2(k, i) 28 if self.T[j] == k: 29 return j 30 else: 31 i += 1 32 return None 33 34 def hash_h1_h2(self, k, i): 35 ‘‘‘hash 函数‘‘‘ 36 return ((k % self.size + i * (1 + k % (self.size - 2)))) % self.size 37 38 T=[] 39 oah=open_address_hash(T,13) 40 print(oah.hash_insert(79)) 41 print(oah.hash_insert(69)) 42 print(oah.hash_search(50)) 43 ------------------------------ 44 1 45 4 46 None
原文：https://www.cnblogs.com/yu-liang/p/9226447.html