Python MyHashTable类:带有线性探测的搜索方法
我需要帮助为我的“MyHashTable”类实现一个方法: 该方法应使用线性探测来处理碰撞分辨率。如果search_键位于哈希表中,则该方法返回包含该search_键的插槽的插槽号。如果搜索键不在哈希表中,则该方法返回-1 我的班级是这样的:Python MyHashTable类:带有线性探测的搜索方法,python,class,hashtable,linear-probing,Python,Class,Hashtable,Linear Probing,我需要帮助为我的“MyHashTable”类实现一个方法: 该方法应使用线性探测来处理碰撞分辨率。如果search_键位于哈希表中,则该方法返回包含该search_键的插槽的插槽号。如果搜索键不在哈希表中,则该方法返回-1 我的班级是这样的: class MyHashTable: def __init__(self, capacity): self.capacity = capacity self.slots = [None] * self.capacity def __st
class MyHashTable:
def __init__(self, capacity):
self.capacity = capacity
self.slots = [None] * self.capacity
def __str__(self):
return str(self.slots )
def __len__(self):
count = 0
for i in self.slots:
if i != None:
count += 1
return count
def hash_function(self, key):
i = key % self.capacity
return i
def insert(self, key):
slot = self.hash_function(key)
orig = slot
while True:
if self.slots[slot] is None:
self.slots[slot] = key
return slot
if self.slots[slot] == key:
return -2
slot = (slot + 1) % self.capacity
if slot == orig:
return -1
def search(self, search_key):
任何帮助或教程链接都会很棒。
感谢您只使用一个列表来存储所有值,如果您想要一个哈希表,您可以使用一个列表列表,其中每个列表都是一个bucket,但是如果您只想用自己的代码检查元素是否在哈希表中:
def search(self, search_key):
hsh = self.hash_function(search_key)
if self.slots[hsh] is None:
return -1
while hsh < self.capacity:
if self.slots[hsh] == search_key:
return hsh
hsh += 1
return -1
第一个while循环将一次探测一个值,但是如果我们从多个冲突中环绕列表,它将在开始时丢失元素,因此使用range
和mod=(hsh+i)%self。capacity
确保我们检查所有条目,如下面的示例所示
m = MyHashTable(5)
m.insert(13) # 13 % 5 = 3
m.insert(73) # 83 % 5 = 3
m.insert(93) # 93 & 5 = 3
print(m.search(13)) # 3
print(m.search(73)) # 4
print(m.search(93)) # 0
print(m.search(2)) # -1
通过跟踪向哈希表添加唯一值的时间,您可以创建len方法O(1)
。此外,还有一个很好的wiki页面,您可以将其应用到代码中,它将帮助您创建键到值的正确映射,并在需要时调整哈希表的大小。如果您想存储的不仅仅是数字,您需要使用不同的哈希函数,我只使用哈希函数,但您可以使用任何您喜欢的函数。当哈希表已满且密钥不存在时,在中使用,也会导致无限循环,因此需要处理这种情况:
class MyHashTable:
def __init__(self, capacity):
self.capacity = capacity
self.slots = [None] * self.capacity
self.count = 0
def __str__(self):
return str(self.slots)
def __contains__(self, item):
return self.search(item) != -1
def __len__(self):
return self.count
def hash_function(self, key):
return hash(key) % self.capacity
def find_slot(self, key):
slot = self.hash_function(key)
while self.slots[slot] is not None and self.slots[slot] != key:
slot = (slot + 1) % self.capacity
return slot
def insert(self, key):
slot = self.find_slot(key)
if self.slots[slot] != key:
self.slots[slot] = key
self.count += 1
def search(self, key):
i = self.find_slot(key)
if self.slots[i] is not None:
return i
return -1
添加\uuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu
m = MyHashTable(5)
m.insert("foo")
m.insert(73)
m.insert(93)
m.insert(1)
print(m.search(73))
print(m.search(93))
print(m.search(1))
print(m.search("foo"))
m.insert(73)
print(m.slots)
print(len(m))
print("foo" in m)
print(5 in m)
输出:
3
4
1
0
['foo', 1, None, 73, 93]
4
True
False
m = MyHashTable(5)
m.insert("foo")
m.insert(73)
m.insert(93)
m.insert(1)
print(m.search(73))
print(m.search(93))
print(m.search(1))
print(m.search("foo"))
m.insert(73)
print(m.slots)
print(len(m))
print("foo" in m)
print(5 in m)
3
4
1
0
['foo', 1, None, 73, 93]
4
True
False