如何在Python中实现通用树?这有内置的数据结构吗?
当前回答
我已经在我的网站https://web.archive.org/web/20120723175438/www.quesucede.com/page/show/id/python_3_tree_implementation上发布了一个Python 3树的实现
代码如下:
import uuid
def sanitize_id(id):
return id.strip().replace(" ", "")
(_ADD, _DELETE, _INSERT) = range(3)
(_ROOT, _DEPTH, _WIDTH) = range(3)
class Node:
def __init__(self, name, identifier=None, expanded=True):
self.__identifier = (str(uuid.uuid1()) if identifier is None else
sanitize_id(str(identifier)))
self.name = name
self.expanded = expanded
self.__bpointer = None
self.__fpointer = []
@property
def identifier(self):
return self.__identifier
@property
def bpointer(self):
return self.__bpointer
@bpointer.setter
def bpointer(self, value):
if value is not None:
self.__bpointer = sanitize_id(value)
@property
def fpointer(self):
return self.__fpointer
def update_fpointer(self, identifier, mode=_ADD):
if mode is _ADD:
self.__fpointer.append(sanitize_id(identifier))
elif mode is _DELETE:
self.__fpointer.remove(sanitize_id(identifier))
elif mode is _INSERT:
self.__fpointer = [sanitize_id(identifier)]
class Tree:
def __init__(self):
self.nodes = []
def get_index(self, position):
for index, node in enumerate(self.nodes):
if node.identifier == position:
break
return index
def create_node(self, name, identifier=None, parent=None):
node = Node(name, identifier)
self.nodes.append(node)
self.__update_fpointer(parent, node.identifier, _ADD)
node.bpointer = parent
return node
def show(self, position, level=_ROOT):
queue = self[position].fpointer
if level == _ROOT:
print("{0} [{1}]".format(self[position].name,
self[position].identifier))
else:
print("\t"*level, "{0} [{1}]".format(self[position].name,
self[position].identifier))
if self[position].expanded:
level += 1
for element in queue:
self.show(element, level) # recursive call
def expand_tree(self, position, mode=_DEPTH):
# Python generator. Loosly based on an algorithm from 'Essential LISP' by
# John R. Anderson, Albert T. Corbett, and Brian J. Reiser, page 239-241
yield position
queue = self[position].fpointer
while queue:
yield queue[0]
expansion = self[queue[0]].fpointer
if mode is _DEPTH:
queue = expansion + queue[1:] # depth-first
elif mode is _WIDTH:
queue = queue[1:] + expansion # width-first
def is_branch(self, position):
return self[position].fpointer
def __update_fpointer(self, position, identifier, mode):
if position is None:
return
else:
self[position].update_fpointer(identifier, mode)
def __update_bpointer(self, position, identifier):
self[position].bpointer = identifier
def __getitem__(self, key):
return self.nodes[self.get_index(key)]
def __setitem__(self, key, item):
self.nodes[self.get_index(key)] = item
def __len__(self):
return len(self.nodes)
def __contains__(self, identifier):
return [node.identifier for node in self.nodes
if node.identifier is identifier]
if __name__ == "__main__":
tree = Tree()
tree.create_node("Harry", "harry") # root node
tree.create_node("Jane", "jane", parent = "harry")
tree.create_node("Bill", "bill", parent = "harry")
tree.create_node("Joe", "joe", parent = "jane")
tree.create_node("Diane", "diane", parent = "jane")
tree.create_node("George", "george", parent = "diane")
tree.create_node("Mary", "mary", parent = "diane")
tree.create_node("Jill", "jill", parent = "george")
tree.create_node("Carol", "carol", parent = "jill")
tree.create_node("Grace", "grace", parent = "bill")
tree.create_node("Mark", "mark", parent = "jane")
print("="*80)
tree.show("harry")
print("="*80)
for node in tree.expand_tree("harry", mode=_WIDTH):
print(node)
print("="*80)
其他回答
我已经在我的网站https://web.archive.org/web/20120723175438/www.quesucede.com/page/show/id/python_3_tree_implementation上发布了一个Python 3树的实现
代码如下:
import uuid
def sanitize_id(id):
return id.strip().replace(" ", "")
(_ADD, _DELETE, _INSERT) = range(3)
(_ROOT, _DEPTH, _WIDTH) = range(3)
class Node:
def __init__(self, name, identifier=None, expanded=True):
self.__identifier = (str(uuid.uuid1()) if identifier is None else
sanitize_id(str(identifier)))
self.name = name
self.expanded = expanded
self.__bpointer = None
self.__fpointer = []
@property
def identifier(self):
return self.__identifier
@property
def bpointer(self):
return self.__bpointer
@bpointer.setter
def bpointer(self, value):
if value is not None:
self.__bpointer = sanitize_id(value)
@property
def fpointer(self):
return self.__fpointer
def update_fpointer(self, identifier, mode=_ADD):
if mode is _ADD:
self.__fpointer.append(sanitize_id(identifier))
elif mode is _DELETE:
self.__fpointer.remove(sanitize_id(identifier))
elif mode is _INSERT:
self.__fpointer = [sanitize_id(identifier)]
class Tree:
def __init__(self):
self.nodes = []
def get_index(self, position):
for index, node in enumerate(self.nodes):
if node.identifier == position:
break
return index
def create_node(self, name, identifier=None, parent=None):
node = Node(name, identifier)
self.nodes.append(node)
self.__update_fpointer(parent, node.identifier, _ADD)
node.bpointer = parent
return node
def show(self, position, level=_ROOT):
queue = self[position].fpointer
if level == _ROOT:
print("{0} [{1}]".format(self[position].name,
self[position].identifier))
else:
print("\t"*level, "{0} [{1}]".format(self[position].name,
self[position].identifier))
if self[position].expanded:
level += 1
for element in queue:
self.show(element, level) # recursive call
def expand_tree(self, position, mode=_DEPTH):
# Python generator. Loosly based on an algorithm from 'Essential LISP' by
# John R. Anderson, Albert T. Corbett, and Brian J. Reiser, page 239-241
yield position
queue = self[position].fpointer
while queue:
yield queue[0]
expansion = self[queue[0]].fpointer
if mode is _DEPTH:
queue = expansion + queue[1:] # depth-first
elif mode is _WIDTH:
queue = queue[1:] + expansion # width-first
def is_branch(self, position):
return self[position].fpointer
def __update_fpointer(self, position, identifier, mode):
if position is None:
return
else:
self[position].update_fpointer(identifier, mode)
def __update_bpointer(self, position, identifier):
self[position].bpointer = identifier
def __getitem__(self, key):
return self.nodes[self.get_index(key)]
def __setitem__(self, key, item):
self.nodes[self.get_index(key)] = item
def __len__(self):
return len(self.nodes)
def __contains__(self, identifier):
return [node.identifier for node in self.nodes
if node.identifier is identifier]
if __name__ == "__main__":
tree = Tree()
tree.create_node("Harry", "harry") # root node
tree.create_node("Jane", "jane", parent = "harry")
tree.create_node("Bill", "bill", parent = "harry")
tree.create_node("Joe", "joe", parent = "jane")
tree.create_node("Diane", "diane", parent = "jane")
tree.create_node("George", "george", parent = "diane")
tree.create_node("Mary", "mary", parent = "diane")
tree.create_node("Jill", "jill", parent = "george")
tree.create_node("Carol", "carol", parent = "jill")
tree.create_node("Grace", "grace", parent = "bill")
tree.create_node("Mark", "mark", parent = "jane")
print("="*80)
tree.show("harry")
print("="*80)
for node in tree.expand_tree("harry", mode=_WIDTH):
print(node)
print("="*80)
如果有人需要一个更简单的方法，树只是一个递归嵌套的列表(因为set是不可哈希的):
[root, [child_1, [[child_11, []], [child_12, []]], [child_2, []]]]
每个分支都是一对:[object， [children]] 每个叶子是一对:[object， []]
但是如果你需要一个带有方法的类，你可以使用任何树。
您可以使用Python中的dataclasses模块创建Tree数据结构。
iter方法可用于使树可迭代，允许您通过改变yield语句的顺序来遍历树。
contains方法可用于检查树中是否存在特定值。
from dataclasses import dataclass
# A
# / \
# B C
# / \ \
# D E F
# / \
# G H
@dataclass
class Node:
data: str
left: Node = None
right: Node = None
def __iter__(self):
if self.left:
yield from self.left
yield self
if self.right:
yield from self.right
def __contains__(self, other):
for node in self:
if node.data == other:
return True
return False
t = Node(
'A',
Node(
'B',
Node(
'D',
Node('G'),
Node('H'),
),
Node('E'),
),
Node(
'C',
right=Node('F'),
),
)
assert ('A' in t) is True
assert ('I' in t) is not True
for node in t:
print(node.data, ' -> ', end='')
# G -> D -> H -> B -> E -> A -> C -> F ->
我推荐任何树(我是作者)。
例子:
from anytree import Node, RenderTree
udo = Node("Udo")
marc = Node("Marc", parent=udo)
lian = Node("Lian", parent=marc)
dan = Node("Dan", parent=udo)
jet = Node("Jet", parent=dan)
jan = Node("Jan", parent=dan)
joe = Node("Joe", parent=dan)
print(udo)
Node('/Udo')
print(joe)
Node('/Udo/Dan/Joe')
for pre, fill, node in RenderTree(udo):
print("%s%s" % (pre, node.name))
Udo
├── Marc
│ └── Lian
└── Dan
├── Jet
├── Jan
└── Joe
print(dan.children)
(Node('/Udo/Dan/Jet'), Node('/Udo/Dan/Jan'), Node('/Udo/Dan/Joe'))
anytree也有一个强大的API:
简单的树创建 简单树修改 预序树迭代 后序树迭代 解析相对节点路径和绝对节点路径 从一个节点移动到另一个节点。 树渲染(参见上面的例子) 节点连接/分离连接
你可以试试:
from collections import defaultdict
def tree(): return defaultdict(tree)
users = tree()
users['harold']['username'] = 'hrldcpr'
users['handler']['username'] = 'matthandlersux'
建议在这里:https://gist.github.com/2012250
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