A simple example demonstrating the construction of binary trees.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 | # A binary ordered tree example
class CNode:
left , right, data = None, None, 0
def __init__(self, data):
# initializes the data members
self.left = None
self.right = None
self.data = data
class CBOrdTree:
def __init__(self):
# initializes the root member
self.root = None
def addNode(self, data):
# creates a new node and returns it
return CNode(data)
def insert(self, root, data):
# inserts a new data
if root == None:
# it there isn't any data
# adds it and returns
return self.addNode(data)
else:
# enters into the tree
if data <= root.data:
# if the data is less than the stored one
# goes into the left-sub-tree
root.left = self.insert(root.left, data)
else:
# processes the right-sub-tree
root.right = self.insert(root.right, data)
return root
def lookup(self, root, target):
# looks for a value into the tree
if root == None:
return 0
else:
# if it has found it...
if target == root.data:
return 1
else:
if target < root.data:
# left side
return self.lookup(root.left, target)
else:
# right side
return self.lookup(root.right, target)
def minValue(self, root):
# goes down into the left
# arm and returns the last value
while(root.left != None):
root = root.left
return root.data
def maxDepth(self, root):
if root == None:
return 0
else:
# computes the two depths
ldepth = self.maxDepth(root.left)
rdepth = self.maxDepth(root.right)
# returns the appropriate depth
return max(ldepth, rdepth) + 1
def size(self, root):
if root == None:
return 0
else:
return self.size(root.left) + 1 + self.size(root.right)
def printTree(self, root):
# prints the tree path
if root == None:
pass
else:
self.printTree(root.left)
print root.data,
self.printTree(root.right)
def printRevTree(self, root):
# prints the tree path in reverse
# order
if root == None:
pass
else:
self.printRevTree(root.right)
print root.data,
self.printRevTree(root.left)
if __name__ == "__main__":
# create the binary tree
BTree = CBOrdTree()
# add the root node
root = BTree.addNode(0)
# ask the user to insert values
for i in range(0, 5):
data = int(raw_input("insert the node value nr %d: " % i))
# insert values
BTree.insert(root, data)
print
BTree.printTree(root)
print
BTree.printRevTree(root)
print
data = int(raw_input("insert a value to find: "))
if BTree.lookup(root, data):
print "found"
else:
print "not found"
print BTree.minValue(root)
print BTree.maxDepth(root)
print BTree.size(root)
|
It's a toy example written years ago to implement a binary tree in Python. Useful for newbies or for a base for something else
Tags: algorithms
Small suggestion. Nice example. IMHO you should just change the B-Tree comment to binary tree, although this code can hold multiple info per node, it does not implement a B-Tree structure neither has its properties (like being balanced, having a maximum number of buckets per node and short in height).
Fixed. thanks :)
I can see, by running the example, that zero (0) is always a node. Can we get rid of it? How could it be done?
Why cannt feed letters (or texts) into the binary tree?
Thank you
If you're looking for an API similar to that provided by a binary search tree, check out the sortedcontainers module. It implements sorted list, sorted dict, and sorted set data types in pure-Python and is fast-as-C implementations (even faster!). Learn more about sortedcontainers, available on PyPI and github.