iterative binary search python
def binary_search(a, key):
	low = 0
	high = len(a) - 1
	while low < high:
		mid = (low + high) // 2
		if key == a[mid]:
			return True
		elif key < mid:
			high = mid - 1
		else:
			low = mid + 1
	return Falseiterative binary search python
def binary_search(a, key):
	low = 0
	high = len(a) - 1
	while low < high:
		mid = (low + high) // 2
		if key == a[mid]:
			return True
		elif key < mid:
			high = mid - 1
		else:
			low = mid + 1
	return Falsepython binary search
def binary_search(arr, item):
	first = 0
	last = len(arr) - 1
	while(first <= last):
		mid = (first + last) // 2
		if arr[mid] == item :
			return True
		elif item < arr[mid]:
			last = mid - 1
		else:
			first = mid + 1	
	return Falsepython code for binary search tree
#Complete Binary Search Tree Using Python 3
class node:
    def  __init__(self,data):
        self.data=data
        self.left=None
        self.right=None
class binarytree:
    def __init__(self):
        self.root=None
#INSERT
    def insert(self,data):
        if self.root==None:				
            self.root=node(data)
        else:
            self._insert(data,self.root)
    def _insert(self,data,cur_node):
        if data<cur_node.data:
            if cur_node.left==None:			
                cur_node.left=node(data)
            else:
                self._insert(data,cur_node.left) 
        elif data>cur_node.data:			
            if cur_node.right==None:
                cur_node.right=node(data)
            else:
                self._insert(data,cur_node.right)
        else:
            print('Data In Treee Already')
#REMOVE
    def remove(self,data):
        if self.root!=None:
            self._remove(data,self.root)
    def _remove(self,data,cur_node):
        if cur_node == None:
            return cur_node
        if data<cur_node.data:
            cur_node.left=self._remove(data,cur_node.left)
        elif data>cur_node.data:
            cur_node.right=self._remove(data,cur_node.right)
        else:
            if cur_node.left is None and cur_node.right is None:
                print('Removing Leaf Node')
                if cur_node==self.root:
                    self.root=None
                del cur_node
                return None
            if cur_node.left is None:
                print('Removing None with Right Child')
                if cur_node==self.root:
                    self.root=cur_node.right
                tempnode=cur_node.right
                del cur_node
                return tempnode
            elif cur_node.right is None:
                print('Removing None with Left Child')
                if cur_node==self.root:
                    self.root=cur_node.left
                tempnode=cur_node.left
                del cur_node
                return tempnode
            print('Removing Node with 2 Children')
            tempnode=self.getpred(cur_node.left)
            cur_node.data=tempnode.data
            cur_node.left=self._remove(cur_node.data,cur_node.left)
        return cur_node
    def getpred(self,cur_node):
        if cur_node.right!=None:
            return self.getpred(cur_node.right)
        return cur_node
#INORDER TRAVERSAL
    def inorder(self):
        if self.root!=None:
            self._inorder(self.root)
    def _inorder(self,cur_node):
        if cur_node!=None:
            self._inorder(cur_node.left)
            print(cur_node.data)
            self._inorder(cur_node.right)
#PREORDER TRAVERSAL
    def preorder(self):
        if self.root!=None:
            self._preorder(self.root)
    def _preorder(self,cur_node):
        if cur_node!=None:
            print(cur_node.data)
            self._preorder(cur_node.left)
            self._preorder(cur_node.right)
#POSTORDER TRAVERSAL
    def postorder(self):
        if self.root!=None:
            self._postorder(self.root)
    def _postorder(self,cur_node):
        if cur_node!=None:
            self._postorder(cur_node.left)
            self._postorder(cur_node.right)
            print(cur_node.data)
#MINIMUM VALUE
    def minval(self):
        if self.root!=None:
            return self._minval(self.root)
    def _minval(self,cur_node):
        if cur_node.left!=None:
            return self._minval(cur_node.left)
        return cur_node.data
#MAXIMUM VALUE
    def maxval(self):
        if self.root!=None:
            return self._maxval(self.root)
    def _maxval(self,cur_node):
        if cur_node.right!=None:
            return self._maxval(cur_node.right)
        return cur_node.data
tree=binarytree()
tree.insert(100)
tree.insert(90)					#			 100
tree.insert(110)				#			/	\
tree.insert(95)					#          90   110
tree.insert(30)					#		  /  \
								#		30    95 
tree.remove(110)
tree.remove(90)
tree.inorder()
#tree.preorder()
#tree.postorder()
print(tree.minval())
print(tree.maxval())binary search python
# This is real binary search
# this algorithm works very good because it is recursive
def binarySearch(arr, min, max, x):
    if max >= min:
        i = int(min + (max - min) / 2) # average
        if arr[i] == x:
            return i
        elif arr[i] < x:
            return binarySearch(arr, i + 1, max, x)
        else:
            return binarySearch(arr, min, i - 1, x)binary search python
#binary search python
def binaryy(ar, ele):
    low = 0 
    high = len(ar)-1
    if ele not in ar:
        return "Not Found"
    while low <= high:
        mid = (low + high) // 2
        if ar[mid] < ele:
            low = mid + 1
        elif ar[mid] > ele:
            high = mid - 1
        else:
            return mid
ar = [10, 20, 30, 40, 50]
ele = 55
print(binaryy(ar, ele))python binary search
#blog.icodes.tech
def binary_search(item,my_list):
    found=False
    first=0
    last=len(my_list)-1
    while first <=last and found==False:
        midpoint=(first+last)//2
        if my_list[midpoint]==item:
            found=True
        else:
            if my_list[midpoint]<item:
                first=midpoint+1
            else:
                last=midpoint-1
    return foundCopyright © 2021 Codeinu
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