python中的二叉树模块内容:

BinaryTree:非平衡二叉树
 AVLTree:平衡的AVL树
 RBTree:平衡的红黑树
以上是用python写的,相面的模块是用c写的,并且可以做为Cython的包。

FastBinaryTree
 FastAVLTree
 FastRBTree
特别需要说明的是:树往往要比python内置的dict类慢一些,但是它中的所有数据都是按照某个关键词进行排序的,故在某些情况下是必须使用的。

安装和使用

安装方法

安装环境:

ubuntu12.04, python 2.7.6

安装方法

下载源码,地址:https://bitbucket.org/mozman/bintrees/src
进入源码目录,看到setup.py文件,在该目录内运行   

python setup.py install

安装成功,ok!下面就看如何使用了。

应用

bintrees提供了丰富的API,涵盖了通常的多种应用。下面逐条说明其应用。

– 引用

如果按照一般模块的思路,输入下面的命令引入上述模块

>>> import bintrees

 
错了,这是错的,出现如下警告:(×××不可用,用×××)

  Warning: FastBinaryTree not available, using Python version BinaryTree.

  Warning: FastAVLTree not available, using Python version AVLTree.

  Warning: FastRBTree not available, using Python version RBTree.

正确的引入方式是:

  >>> from bintrees import BinaryTree   #只引入了BinartTree
  >>> from bintrees import *       #三个模块都引入了

– 实例化

看例子:

>>> btree = BinaryTree()
  >>> btree
  BinaryTree({})
  >>> type(btree)
  

  
– 逐个增加键值对: .__setitem__(k,v) .复杂度O(log(n))(后续说明中,都会有复杂度标示,为了简单,直接标明:O(log(n)).)

看例子:

>>> btree.__setitem__(\"Tom\",\"headmaster\")
 >>> btree
 BinaryTree({\'Tom\': \'headmaster\'})
 >>> btree.__setitem__(\"blog\",\"http://blog.csdn.net/qiwsir\")
 >>> btree
 BinaryTree({\'Tom\': \'headmaster\', \'blog\': \'http://blog.csdn.net/qiwsir\'})

  
– 批量添加: .update(E)  E是dict/iterable,将E批量更新入btree. O(E*log(n))

看例子:

>>> adict = [(2,\"phone\"),(5,\"tea\"),(9,\"scree\"),(7,\"computer\")]
  >>> btree.update(adict)
  >>> btree
  BinaryTree({2: \'phone\', 5: \'tea\', 7: \'computer\', 9: \'scree\', \'Tom\': \'headmaster\', \'blog\': \'http://blog.csdn.net/qiwsir\'})

  
– 查找某个key是否存在: .__contains__(k)  如果含有键k,则返回True,否则返回False. O(log(n))

看例子:

>>> btree
 BinaryTree({2: \'phone\', 5: \'tea\', 7: \'computer\', 9: \'scree\', \'Tom\': \'headmaster\', \'blog\': \'http://blog.csdn.net/qiwsir\'})
 >>> btree.__contains__(5)
 True
 >>> btree.__contains__(\"blog\")
 True
 >>> btree.__contains__(\"qiwsir\")
 False
 >>> btree.__contains__(1)
 False

  
– 根据key删除某个key-value: .__delitem__(key), O(log(n))

看例子:

>>> btree
  BinaryTree({2: \'phone\', 5: \'tea\', 7: \'computer\', 9: \'scree\', \'Tom\': \'headmaster\', \'blog\': \'http://blog.csdn.net/qiwsir\'})
  >>> btree.__delitem__(5)    #删除key=5的key-value,即:5:\'tea\' 被删除.
  >>> btree
  BinaryTree({2: \'phone\', 7: \'computer\', 9: \'scree\', \'Tom\': \'headmaster\', \'blog\': \'http://blog.csdn.net/qiwsir\'})

– 根据key值得到该kye的value: .__getitem__(key)

看例子:

>>> btree
 BinaryTree({2: \'phone\', 7: \'computer\', 9: \'scree\', \'Tom\': \'headmaster\', \'blog\': \'http://blog.csdn.net/qiwsir\'})
 >>> btree.__getitem__(\"blog\")
 \'http://blog.csdn.net/qiwsir\'
 >>> btree.__getitem__(7)
 \'computer\'
 >>> btree._getitem__(5)  #在btree中没有key=5,于是报错。
 Traceback (most recent call last):
 File \"\", line 1, in 
 AttributeError: \'BinaryTree\' object has no attribute \'_getitem__\'

– 迭代器: .__iter__()

看例子:

>>> btree 
 BinaryTree({2: \'phone\', 7: \'computer\', 9: \'scree\', \'Tom\': \'headmaster\', \'blog\': \'http://blog.csdn.net/qiwsir\'})
 >>> aiter = btree.__iter__()
 >>> aiter
  at 0xb7416dec>
 >>> aiter.next() #注意:next()一个之后,该值从list中删除
 2
 >>> aiter.next()
 7
 >>> list(aiter)
 [9, \'Tom\', \'blog\']
 >>> list(aiter)  #结果是空
 []
 >>> bool(aiter)  #but,is True
 True

– 树的数据长度: .__len__(),返回btree的长度。O(1)

看例子:

>>> btree
  BinaryTree({2: \'phone\', 7: \'computer\', 9: \'scree\', \'Tom\': \'headmaster\', \'blog\': \'http://blog.csdn.net/qiwsir\'})
  >>> btree.__len__()
  5

– 找出key最大的k-v对: .__max__(),按照key排列,返回key最大的键值对。

– 找出key最小的键值对: .__min__()

看例子:

>>> btree
 BinaryTree({2: \'phone\', 7: \'computer\', 9: \'scree\'})
 >>> btree.__max__()
 (9, \'scree\')
 >>> btree.__min__()
 (2, \'phone\')

– 两棵树的关系运算

看例子:

>>> other = [(3,\'http://www.jb51.net\'),(7,\'qiwsir\')]
 >>> bother = BinaryTree()  #再建一个树
 >>> bother.update(other) #加入数据

 >>> bother
 BinaryTree({3: \'http://www.jb51.net\', 7: \'qiwsir\'})
 >>> btree
 BinaryTree({2: \'phone\', 7: \'computer\', 9: \'scree\'})
 
 >>> btree.__and__(bother)  #重叠部分部分
 BinaryTree({7: \'computer\'})

 >>> btree.__or__(bother) #全部
 BinaryTree({2: \'phone\', 3: \'http://www.jb51.net, 7: \'computer\', 9: \'scree\'})

 >>> btree.__sub__(bother)  #btree不与bother重叠的部分
 BinaryTree({2: \'phone\', 9: \'scree\'})
 
 >>> btree.__xor__(bother)  #两者非重叠部分
 BinaryTree({2: \'phone\', 3: \'http://www.jb51.net, 9: \'scree\'})

– 输出字符串模样,注意仅仅是输出的模样罢了: .__repr__()

看例子:

>>> btree
  BinaryTree({2: \'phone\', 7: \'computer\', 9: \'scree\'})
  >>> btree.__repr__()
  \"BinaryTree({2: \'phone\', 7: \'computer\', 9: \'scree\'})\"

– 清空树中的所有数据 :.clear(),O(log(n))

看例子:

>>> bother  
 BinaryTree({3: \'http://blog.csdn.net/qiwsir\', 7: \'qiwsir\'})
 >>> bother.clear()
 >>> bother
 BinaryTree({})
 >>> bool(bother)
 False

– 浅拷贝: .copy(),官方文档上说是浅拷贝,但是我做了操作实现,是下面所示,还不是很理解其“浅”的含义。O(n*log(n))

看例子:

>>> btree
 BinaryTree({2: \'phone\', 7: \'computer\', 9: \'scree\'})
 >>> ctree = btree.copy()
 >>> ctree
 BinaryTree({2: \'phone\', 7: \'computer\', 9: \'scree\'})

 >>> btree.__setitem__(\"github\",\"qiwsir\") #增加btree的数据
 >>> btree
 BinaryTree({2: \'phone\', 7: \'computer\', 9: \'scree\', \'github\': \'qiwsir\'})
 >>> ctree
 BinaryTree({2: \'phone\', 7: \'computer\', 9: \'scree\'}) #这是不是在说明属于深拷贝呢?
 
 >>> ctree.__delitem__(7) #删除ctree的一个数据
 >>> ctree
 BinaryTree({2: \'phone\', 9: \'scree\'})
 >>> btree
 BinaryTree({2: \'phone\', 7: \'computer\', 9: \'scree\', \'github\': \'qiwsir\'})

  

– 移除树中的一个数据: .discard(key),这个功能与.__delitem__(key)类似.两者都不反悔值。O(log(n))

看例子:

>>> ctree
 BinaryTree({2: \'phone\', 9: \'scree\'})
 >>> ctree.discard(2) #删除后,不返回值,或者返回None
 >>> ctree
 BinaryTree({9: \'scree\'})
 >>> ctree.discard(2) #如果删除的key不存在,也返回None
 >>> ctree.discard(3)
 >>> ctree.__delitem__(3) #但是,.__delitem__(key)则不同,如果key不存在,会报错。
 Traceback (most recent call last):
  File \"\", line 1, in 
  File \"/usr/local/lib/python2.7/site-packages/bintrees/abctree.py\", line 264, in __delitem__
  self.remove(key)
  File \"/usr/local/lib/python2.7/site-packages/bintrees/bintree.py\", line 124, in remove
  raise KeyError(str(key))
  KeyError: \'3\'

– 根据key查找,并返回或返回备用值: .get(key[,d])。如果key在树中存在,则返回value,否则如果有d,则返回d值。O(log(n))

看例子:

>>> btree
 BinaryTree({2: \'phone\', 7: \'computer\', 9: \'scree\', \'github\': \'qiwsir\'})
 >>> btree.get(2,\"algorithm\")
 \'phone\'
 >>> btree.get(\"python\",\"algorithm\") #没有key=\'python\'的值,返回\'algorithm\'
 \'algorithm\'
 >>> btree.get(\"python\") #如果不指定第二个参数,若查不到,则返回None
 >>>

– 判断树是否为空: is_empty().根据树数据的长度,如果数据长度为0,则为空。O(1)

看例子:

>>> ctree
 BinaryTree({9: \'scree\'})
 >>> ctree.clear()  #清空数据
 >>> ctree
 BinaryTree({})
 >>> ctree.is_empty()
 True
 >>> btree
 BinaryTree({2: \'phone\', 7: \'computer\', 9: \'scree\', \'github\': \'qiwsir\'})
 >>> btree.is_empty()
 False

– 根据key、value循环从树中取值:

>>.items([reverse])–按照(key,value)结构取值;

>>.keys([reverse])–key

>>.values([reverse])–value. O(n)

>>.iter_items(s,e[,reverse]–s,e是key的范围,也就是生成在某个范围内的key的迭代器 O(n)

看例子:

>>> btree
 BinaryTree({2: \'phone\', 7: \'computer\', 9: \'scree\', \'github\': \'qiwsir\'})
 >>> for (k,v) in btree.items():
 ... print k,v
 ...
 2 phone
 7 computer
 9 scree
 github qiwsir
 >>> for k in btree.keys():
 ... print k
 ...
 2
 7
 9
 github
 >>> for v in btree.values():
 ... print v
 ...
 phone
 computer
 scree
 qiwsir
 >>> for (k,v) in btree.items(reverse=True): #反序
 ... print k,v
 ...
 github qiwsir
 9 scree
 7 computer
 2 phone

 >>> btree
 BinaryTree({2: \'phone\', 5: None, 7: \'computer\', 8: \'eight\', 9: \'scree\', \'github\': \'qiwsir\'})
 >>> for (k,v) in btree.iter_items(6,9): #要求迭代6<=key<9的键值对数据
 ... print k,v
 ...
 7 computer
 8 eight
 >>>

      

– 删除数据并返回该值:

>>.pop(key[,d]), 根据key删除树的数据,并返回该value,但是如果没有,并也指定了备选返回的d,则返回d,如果没有d,则报错;

>>.pop_item(),在树中随机选择(key,value)删除,并返回。

看例子:

>>> ctree = btree.copy()
 >>> ctree
 BinaryTree({2: \'phone\', 7: \'computer\', 9: \'scree\', \'github\': \'qiwsir\'})

 >>> ctree.pop(2) #删除key=2的数据,返回其value
 \'phone\'
 >>> ctree.pop(2) #删除一个不存在的key,报错
 Traceback (most recent call last):
  File \"\", line 1, in 
  File \"/usr/local/lib/python2.7/site-packages/bintrees/abctree.py\", line 350, in pop
  value = self.get_value(key)
  File \"/usr/local/lib/python2.7/site-packages/bintrees/abctree.py\", line 557, in get_value
  raise KeyError(str(key))
  KeyError: \'2\'
 
 >>> ctree.pop_item()  #随机返回一个(key,value),并已删除之
 (7, \'computer\')
 >>> ctree
 BinaryTree({9: \'scree\', \'github\': \'qiwsir\'})
 
 >>> ctree.pop(7,\"sing\") #如果没有,可以返回指定值
 \'sing\'

– 查找数据,并返回value: .set_default(key[,d]),在树的数据中查找key,如果存在,则返回该value。如果不存在,当指定了d,则将该(key,d)添加到树内;当不指定d的时候,添加(key,None). O(log(n))

看例子:

>>> btree
 BinaryTree({2: \'phone\', 7: \'computer\', 9: \'scree\', \'github\': \'qiwsir\'})
 >>> btree.set_default(7) #存在则返回
 \'computer\'
 
 >>> btree.set_default(8,\"eight\") #不存在,则返回后备指定值,并加入到树
 \'eight\'
 >>> btree
 BinaryTree({2: \'phone\', 7: \'computer\', 8: \'eight\', 9: \'scree\', \'github\': \'qiwsir\'})
 
 >>> btree.set_default(5) #如果不指定值,则会加入None
 >>> btree
 BinaryTree({2: \'phone\', 5: None, 7: \'computer\', 8: \'eight\', 9: \'scree\', \'github\': \'qiwsir\'})

 >>> btree.get(2) #注意,.get(key)与.set_default(key[,d])的区别
 \'phone\'
 >>> btree.get(3,\"mobile\")  #不存在的 key,返回但不增加到树
 \'mobile\'
 >>> btree
 BinaryTree({2: \'phone\', 7: \'computer\', 8: \'eight\', 9: \'scree\', \'github\': \'qiwsir\'})

– 根据key删除值

>>.remove(key),删除(key,value)

>>.remove_items(keys),keys是一个key组成的list,逐个删除树中的对应数据

看例子:

>>> ctree
 BinaryTree({2: \'phone\', 5: None, 7: \'computer\', 8: \'eight\', 9: \'scree\', \'github\': \'qiwsir\'})
 >>> ctree.remove_items([5,6])  #key=6,不存在,报错
 Traceback (most recent call last):
  File \"\", line 1, in 
  File \"/usr/local/lib/python2.7/site-packages/bintrees/abctree.py\", line 271, in remove_items
  self.remove(key)
  File \"/usr/local/lib/python2.7/site-packages/bintrees/bintree.py\", line 124, in remove
  raise KeyError(str(key))
  KeyError: \'6\'
 
 >>> ctree
 BinaryTree({2: \'phone\', 7: \'computer\', 8: \'eight\', 9: \'scree\', \'github\': \'qiwsir\'})
 >>> ctree.remove_items([2,7,\'github\']) #按照 列表中顺序逐个删除
 >>> ctree
 BinaryTree({8: \'eight\', 9: \'scree\'})

   
##以上只是入门的基本方法啦,还有更多内容,请移不到到文章开头的官方网站