def check_parens(text):
parens = "()[]{}" # 括号字符
open_parens = "([{" # 开括号字符
opposite = {')' : '(', ']' : '[', '}' : '{'} # 表示匹配关系的字典
def parantheses(text):
# 括号生成器，每次调用返回text里的下一括号及其位置
i, text_len = 0, len(text)
while True:
# 从位置0开始扫描字符串，如果不是括号的符号就继续向后扫描
while i < text_len and text[i] not in parens:
i += 1
# 扫描完整个字符串，则结束
if i >= text_len:
return
# 以上都不符合，那么就是扫描到了括号，返回一个括号符号
yield text[i], i
i += 1 # 继续扫描下一个
st = SStack() # 保存括号的栈
for pr, i in parantheses(text): # 对text里的各括号和位置迭代
if pr in open_parens: # 从括号生成器中拿出来的括号符号是开括号，压进栈并继续
st.push(pr)
# 不是开括号就是闭括号，这时弹出栈里面的括号，看是否和当前括号匹配
elif st.pop() != opposite[pr]:
print('Unmatching is found at', i, 'for', pr)
return False
# else: # 成功的匹配，啥也不做，继续
print('All parentheses are correctly matched.')
return True
def pre_order_nr(tree, func):
s = SStack()
while tree or not s.is_empty():
while tree:
func(tree.root)
s.push(tree.right)
tree = tree.left
tree = s.pop()
def postorder_nonrec(t, proc):
s = SStack()
while t is not None or not s.is_empty():
while t is not None: #下行循环，直到栈顶的两子树空
s.push(t)
t = t.left if t.left is not None else t.right #能左就左否则向右
t = s.pop() #栈顶是应访问节点
proc(t.data)
if not s.is_empty() and s.top().left == t:
t = s.top().right #栈不空且当前节点是栈定左子节点
else: #没有右子树或右子树遍历完毕，强迫退栈
t = None
def postorder_nonrec(t_, proc):
s = SStack()
while t_ is not None or not s.is_empty():
while t_ is not None: # 下行循环，直到栈顶的两个树空
s.push(t_)
t_ = t_.left if t_.left is not None else t_.right # 注意这个条件表达式的意义：能左就左，否则向右一步
t_ = s.pop() # 栈顶是访问结点
proc(t_.dat)
if not s.is_empty() and s.top().left == t_:
t_ = s.top().right # 栈不空且当前结点是栈顶的左子结点
else:
t_ = None # 没有右子树或右子树遍历完毕，强迫退栈
def trans_infix_suffix(line):
st = SStack()
exp = [] # 记录转换得到的后缀表达式，采用项表的形式
for x in token(line):
if x not in infix_operatios:
pass
def preorder_elements(self):
t, s = self._root, SStack()
while t is not None or not s.is_empty():
while t is not None:
s.push(t.right)
yield t.dat
t = t.left
t = s.pop()
def DFS_graph(graph, v0):
vnum = graph.vertex_num()
visited = [0] * vnum
visited[v0] = 1
DFS_seq = [v0]
st = SStack()
st.push((0, graph.out_edges(v0)))
while not st.is_empty():
i, edges = st.pop()
if i < len(edges):
v, e = edges[i]
st.push((i+1, edges))
if not visited[v]:
DFS_seq.append(v)
visited[v] = 1
st.push((0, graph.out_edges(v)))
return DFS_seq
def DFS_graph_non_recursive(graph, v0): # 借用辅助栈 非递归实现
ver_num = graph.get_ver_num()
visited = [0] * ver_num
visited[v0] = 1
dfs_seq = [v0] #dfs序列
st = SStack()
st.push((0, graph.get_outedges(v0)))
while not st.is_empty():
i, edges = st.pop()
if i < len(edges):
v, w = edges[i]
st.push((i + 1, edges)) #回溯时访问i+1
if not visited[v]: #v未被访问，记录并继续dfs
dfs_seq.append(v)
visited[v] = 1
st.push((0, graph.get_outedges(v)))
return dfs_seq
def values(self):
t, s = self._root, SStack()
while t or not s.is_empty():
while t:
s.push(t)
t = t.left
t = s.pop()
yield t.data.key, t.data.value
t = t.right
def entries(self):
t, s = self._root, SStack()
while t is not None or not s.is_empty():
while t is not None:
s.push(t)
t = t.left
t = s.pop()
yield t.dat.key, t.dat.value
t = t.right
def dfs_non_recursive_traverse_postorder(t, proc): #dfs非递归 后根序
s = SStack()
while t is not None or not s.is_empty():
while t is not None:
s.push(t)
if t.left is not None:
t = t.left
else:
t = t.right
t = s.pop()
proc(t.data)
if not s.is_empty() and s.top().left == t:
t = s.top().right #这一步很关键
else:
t = None
def DFS_SpanTree(graph, v0):
vertex_num = graph.get_ver_num()
dfs_spantree = []
visited = [0] * vertex_num
visited[v0] = 1
st = SStack()
st.push((0, v0, graph.get_outedges(v0)))
while not st.is_empty():
i, prev_v, edges = st.pop()
if i < len(edges):
v, w = edges[i]
st.push((i + 1, prev_v, edges))
if not visited[v]:
visited[v] = 1
st.push((0, v, graph.get_outedges(v)))
dfs_spantree.append((prev_v, w, v))
return dfs_spantree
def preorder_elements(t_):
s = SStack()
while t_ is not None or not s.is_empty():
while t_ is not None:
s.push(t_.right)
yield t_.dat
t_ = t_.left
t_ = s.pop()
def preorder_nonrec(t, proc):
s = SStack()
while t is not None or not s.is_empty():
while t is not None:
proc(t.data)
s.push(t.right)
t = t.left
t = s.pop()
def preorder_elements(t):
s = SStack()
while t is not None or not s.is_empty():
while t is not None:
s.push(t.right)
yield t.data
t = t.left
t = s.pop()
def dfs(graph, s):
stack = SStack()
stack.push(s)
seen = set()
seen.add(s)
parent = {s: None}
while not stack.is_empty():
vertex = stack.pop()
nodes = graph[vertex]
for i in nodes:
if i not in seen:
stack.push(i)
seen.add(i)
parent[i] = vertex
print vertex
return parent
def norec_fact(n): # 自己管理栈，模拟函数调用过程
res = 1
st = SStack()
while n > 0:
st.push(n)
n -= 1
while not st.is_empty():
res *= st.pop()
return res
def dfs_non_recursive_traverse(t, proc): #dfs非递归 先根序
s = SStack()
while t is not None or not s.is_empty():
while t is not None:
proc(t.data)
s.push(t.right)
t = t.left
t = s.pop()
def preorder_nonrec(t_, proc):
"""
时间复杂性: O(n)
空间复杂性: O(log(n))
"""
s = SStack()
while t_ is not None or not s.is_empty():
while t_ is not None:
proc(t_.dat)
s.push(t_.right)
t_ = t_.left
t_ = s.pop()
def maze_solver(maze, start, end):
if start == end:
print(start)
return
st == SStack()
mark(maze, start)
st.push((start, 0))
while not st.is_empty():
pos, nxt = st.pop()
for i in range(nxt, 4):
nextp = pos[0] + dirs[i][0], pos[1] + dirs[i][1]
if nextp == end:
print_path(end, pos, st)
return
if passable(maze, nextp):
st.push((pos, i + 1))
mark(maze, nextp)
st.push((nextp, 0))
break
print("No path found.")
def delete(self, key):
p, q = self._root, None
parent_nodes = SStack() #记录所有父结点
#检索 并记录路径
while p is not None and key != p.data.key:
q = p
if key < p.data.key:
p = p.left
parent_nodes.push(q)
else:
p = p.right
parent_nodes.push(q)
#没有找到删除结点
if key != p.data.key:
return
assoc = p
#删除叶结点
if p.right == None and p.left == None:
DictAVL.del_adjustment_leaf(self._root, p, q, parent_nodes)
return assoc
# 只有左子树
if p.left is not None and p.right is None:
DictAVL.del_adjustment_ol(p, q, parent_nodes)
return assoc
# 只有右子树
if p.left is None and p.right is not None:
DictAVL.del_adjustment_or(p, q, parent_nodes)
return assoc
#左右子树都有
if p.left is not None and p.right is not None:
p_traverse, q_traverse = p, None
if p.bf == -1: #若右子树高
#找到右子树的最左结点 一定是一个叶结点
while p_traverse is not None:
q_traverse = p_traverse #q_traverse是p_traverse的父结点
p_traverse = p_traverse.right
parent_nodes.push(p_traverse)
p.data.key, p.data.value = p_traverse.data.key, p_traverse.data.value #进行交换
DictAVL.del_adjustment_leaf(self._root, p_traverse, q_traverse,
parent_nodes) #进行调整
return assoc
elif p.bf == 0: #两棵子树一样高 左子树最右 右子树最左都可以
#找到右子树的最左结点 一定是一个叶结点
while p_traverse is not None:
q_traverse = p_traverse #q_traverse是p_traverse的父结点
p_traverse = p_traverse.right
parent_nodes.push(p_traverse)
p.data.key, p.data.value = p_traverse.data.key, p_traverse.data.value #进行交换
DictAVL.del_adjustment_leaf(self._root, p, q, parent_nodes)
return assoc
else: #p.bf == 1
while p_traverse is not None:
q_traverse = p_traverse #q_traverse是p_traverse的父结点
p_traverse = p_traverse.left
parent_nodes.push(p_traverse)
p.data.key, p.data.value = p_traverse.data.key, p_traverse.data.value #进行交换
DictAVL.del_adjustment_leaf(self._root, p, q, parent_nodes)
return assoc
def trans_infix_suffix(line):
st = SStack()
exp = []
for x in tokens(line): # tokens是一个待定义的生成器
if x not in infix_operators: # 运算对象直接送出
exp.append(x)
elif st.is_empty() or x == '(': # 左括号进栈
st.push(x)
elif x == ')': # 处理右括号的分支
while not st.is_empty() and st.top() != '(':
exp.append(st.pop())
if st.is_empty(): # 没有找到左括号，就是不配对
raise SyntaxError('Missing "(".')
st.pop() # 弹出左括号，右括号也不进栈
else: # 处理运算符，运算符都看作左结合
while (not st.is_empty()) and priority[st.top()] >= priority[x]:
exp.append(st.pop())
st.push(x) # 算数运算符进栈
while not st.is_empty(): # 送出栈里剩下的运算符
if st.pop() == '(': # 如果还有左括号，就是不配对
raise SyntaxError('Extra "(".')
exp.append(st.pop())
return exp
def check_parens(text):
""" 括号匹配检查函数，text是被检查的正文串 """
parens = '()[]{}'
open_parens = '([{'
opposite = {')': '(', ']': '[', '}': '{'} # 表示配对关系的字典
st = SStack() # 保存括号的栈
st_i = SStack()
for pr, i in parentheses(text, parens): # 对text里各括号和位置迭代
if pr in open_parens: # 开括号，压进栈并继续
st.push(pr)
st_i.push(i)
elif st.is_empty() or st.pop() != opposite[pr]: # 不匹配就是失败，退出
if not st.is_empty():
st_i.pop()
print('Unmatching is found at', i, 'for', pr)
return False
else: # 这是一次括号配对成功，什么也不做，继续
st_i.pop()
if not st.is_empty():
'''
st_i_ = ''
st_ = ''
while not st.is_empty():
st_i_ = str(st_i.pop()) + st_i_
st_ = st.pop() + st_
print('Unmatching is found at', st_i_, 'for', st_)
'''
print('Unmatching is found at', st_i.pop(), 'for', st.pop())
return False
print('All parentheses are correctly matched.')
return True
def maze_solver(maze, start, end):
if start == end:
print(start)
return
st = SStack()
mark(maze, start)
st.push((start, 0)) # 入口和方向0的序对入栈
while not st.is_empty(): # 走不通时回退
pos, nxt = st.pop() # 取栈顶及其探查方向
for i in range(nxt, 4): # 依次检查未探查方向
nextp = (pos[0] + dirs[i][0], pos[1] + dirs[i][1]) # 算出下一位置
if nextp == end: # 到达出口打印路径
print(end, end=' ')
print(pos, end=' ')
while not st.is_empty():
print(st.pop()[0], end=' ')
return
if passable(maze, nextp): # 遇到未探查的新位置
st.push((pos, i + 1)) # 原位置和下一方向入栈
mark(maze, nextp)
st.push((nextp, 0)) # 新位置入栈
break # 退出内层循环，下次迭代将以新栈顶为当前位置继续
print('No path found.') # 找不到路径
