Examples of binary tree algorithm and KMP algorithm implemented by python

It mainly includes: preorder traversal, middle order traversal, post-order traversal, hierarchical traversal, non-recursive preorder traversal, non-recursive in-order traversal, and non-recursive post-order traversal

#!/usr/bin/env python
#-*- coding:utf8 -*-

class TreeNode(object):
    def __init__(self, data=None, left=None, right=None):
        self.data = data
        self.left = left
        self.right = right

class Tree(object):
    def __init__(self, root=None):
        self.root = None
    def makeTree(self, data, left, right):
        self.root = TreeNode(data, left, right)
    def is_empty(self):
        """ Whether is empty  """
        if self.root is None:
            return True
        return False
    def preOrder(self, r):
        """ The former sequence traversal  """
        if not r.is_empty():
            print r.root.data
            if r.root.left is not None:
                r.preOrder(r.root.left)
            if r.root.right is not None:
                r.preOrder(r.root.right)
    def inOrder(self, r):
        """ In the sequence traversal  """
        if not r.is_empty():
            if r.root.left is not None:
                r.preOrder(r.root.left)
            print r.root.data
            if r.root.right is not None:
                r.preOrder(r.root.right)
    def postOrder(self, r):
        """ Subsequent traversal  """
        if not r.is_empty():
            if r.root.left is not None:
                r.preOrder(r.root.left)
            print r.root.data
            if r.root.right is not None:
                r.preOrder(r.root.right)
    def levelOrder(self, r):
        """ Level traversal  """
        if not r.is_empty():
            s = [r]
            while len(s) > 0:
                temp = s.pop(0)  #  First pop first append To the point 
                if temp and temp.root is not None:
                    print temp.root.data
                    if temp.root.left is not None:
                        s.append(temp.root.left)
                    if self.root.right is not None:
                        s.append(temp.root.right)
    def preOrder1(self, r):
        """ non-recursive   The former sequence traversal  """
        stack = []
        current = r
        while len(stack) > 0 or (current and not current.is_empty()):
            while current and not current.is_empty():
                print current.root.data
                stack.append(current)
                current = current.root.left
            if len(stack) > 0:
                current = stack.pop()
                current = current.root.right
    def inOrder1(self, r):
        """ non-recursive   In the sequence traversal  """
        stack = []
        current = r
        while len(stack) > 0 or (current and not current.is_empty()):
            while current and not current.is_empty():
                stack.append(current)
                current = current.root.left
            if len(stack) > 0:
                current = stack.pop()
                print current.root.data
                current = current.root.right
    def postOrder1(self, r):
        """ non-recursive   Subsequent traversal  """
        stack = []
        current = r
        pre = None
        while len(stack) > 0 or (current and not current.is_empty()):
            if current and not current.is_empty():
                stack.append(current)
                current = current.root.left
            elif stack[-1].root.right != pre:
                current = stack[-1].root.right
                pre = None
            else:
                pre = stack.pop()
                print pre.root.data
    def leaves_count(self, r):
        """ Find the number of leaf nodes  """
        if r.is_empty():
            return 0
        elif (not r.root.left) and (not r.root.right):
            return 1
        else:
            return r.root.left.leaves_count(r.root.left) + r.root.right.leaves_count(r.root.right)

if __name__ == '__main__':
    """ Binary tree """
    ra, rb, rc, rd, re, rf = Tree(), Tree(), Tree(), Tree(), Tree(), Tree()
    ra.makeTree("a", None, None)
    rb.makeTree("b", None, None)
    rc.makeTree("c", None, None)
    rd.makeTree("d", None, None)
    re.makeTree("e", None, None)
    rf.makeTree("f", None, None)
    r1, r2, r3, r4, r = Tree(), Tree(), Tree(), Tree(), Tree()
    r1.makeTree("-", rc, rd)
    r2.makeTree("*", rb, r1)
    r3.makeTree("+", ra, r2)
    r4.makeTree("/", re, rf)
    r.makeTree("-", r3, r4)
    r.preOrder(r)
    r.inOrder(r)
    r.postOrder(r)
    r.levelOrder(r)
    print r.leaves_count(r)

I learned KMP algorithm when I was in college, but I found that I forgot it when I read it recently, so I went to read the book again and wrote down the algorithm in python:

def kmp(text, pattern):
    """kmp algorithm  """
    pattern = list(pattern)
    next = [-1] * len(pattern)
    #next  function 
    i, j = 1, -1
    for i in range(1, len(pattern)):
        j = next[i - 1]
        while True:
            if pattern[i - 1] == pattern[j] or j == -1:
                next[i] = j + 1
                break
            else:
                j = next[j]
    # Cycle comparison 
    i, j = 0, 0
    while i < len(text) and j < len(pattern):
        if text[i] == pattern[j] or j == -1:
            i += 1
            j += 1
        else:
            j = next[j]
    # Returns the result   If it matches, return the matching location, otherwise -1
    if j == len(pattern):
        print i  �  j
    else:
        print -1