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some interview problems
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25
src/extra_interview_problems/abstract/queue_with_stack.py
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25
src/extra_interview_problems/abstract/queue_with_stack.py
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class Queue():
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def __init__(self):
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self.in_ = []
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self.out = []
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def enqueue(self, item):
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self.in_.append(item)
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def deque(self):
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if not self.out:
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while self.in_:
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self.out.append(self.in_.pop())
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return self.out.pop()
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q = Queue()
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for i in range(10):
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q.enqueue(i)
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for i in range(10):
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print(q.deque())
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9
src/extra_interview_problems/abstract/stack_with_minumum.txt
Executable file
9
src/extra_interview_problems/abstract/stack_with_minumum.txt
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Another way:
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Store two stacks, one of which contains all of the items in the stack and one of which is a stack of minima.
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To push an element, push it onto the first stack. Check whether it is smaller than the top item on the second stack, if so, push it onto the second stack.
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To pop an item, pop it from the first stack. If it is the top element, simply return the element on the top of the second stack.
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O(1)...
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33
src/extra_interview_problems/bit/bitwise.txt
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src/extra_interview_problems/bit/bitwise.txt
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BITWISE
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----------------------
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1. To find a number:
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11000101 is 2^0+2^2+2^6+2^7 = 197
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2. Left shifting:
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0010 1011 << 4 ---> 1011 000
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3. Right shifting:
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0010 1011 >> 4 ---> 0000 0010
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or it can be filled with the copy of the first bit, instead of 0:
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1011 0010 >> 4 ---> 1111 1011
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4. XOR can cancels out:
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15 ^ 12 ^ 15 = 12
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5. 2^x:
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left-shift 1 by x:
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0000 0001 << x
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so if x = 2, 2^2 = 4 -> 100
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0000 0001 << 2 ---> 0000 0100
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6. Is power of 2?
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just do x&(x-1).
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if 0 --> yes!
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21
src/extra_interview_problems/design/design_pattern.txt
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src/extra_interview_problems/design/design_pattern.txt
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DESIGN PATTERNS
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------------------------
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LISTENER/OBSERVER:
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-----------------
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- Example: a GUI as a listener to several objects. For any change in the state, it would update the display.
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SINGLETON PATTERN:
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-----------------
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- To make sure that there is exactly one instance of something in the program.
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MODEL-VIEW-CONTROLLER:
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----------------------
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- Design commonly used in user interfaces. The goal is to keep the data separate from the interface.
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- Separate programming entities to store the data (model), display the data (view) and modify the data (controlle).
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- The view usually makes heavy use of listeners to listen to changes and events in the model or controller.
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8
src/extra_interview_problems/design/design_text_editor.txt
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src/extra_interview_problems/design/design_text_editor.txt
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DESIGN A TEXT EDITOR
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-------------------------------------
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- Classes to set up the text editor: classes for the GUI, formatting, saving/loading files, handling input.
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- Use inheritance where it makes sense.
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- Use design patterns (such as MVC, listener, singleton).
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73
src/extra_interview_problems/trees_paths/binary_search_tree.py
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src/extra_interview_problems/trees_paths/binary_search_tree.py
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#!/usr/bin/python
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__author__ = "bt3"
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__email__ = "bt33gl@gmail.com"
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from binary_tree import NodeBT, BinaryTree
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class NodeBST(NodeBT):
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def __init__(self, item=None, level=0):
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self.item = item
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self.level = level
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self.left = None
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self.right = None
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def _addNextNode(self, value, level_here=1):
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new_node = NodeBST(value, level_here)
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if not self.item:
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self.item = new_node
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else:
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if value > self.item:
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self.right = self.right and self.right._addNextNode(value, level_here+1) or new_node
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elif value < self.item:
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self.left = self.left and self.left._addNextNode(value, level_here+1) or new_node
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else:
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print("BSTs do not support repeated items.")
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return self # this is necessary!!!
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def _searchForNode(self, value):
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if self.item == value:
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return self
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elif self.left and value < self.item:
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return self.left._searchForNode(value)
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elif self.right and value > self.item:
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return self.right._searchForNode(value)
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else:
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return False
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class BinarySearchTree(BinaryTree):
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def __init__(self):
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self.root = None
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def addNode(self, value):
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if not self.root:
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self.root = NodeBST(value)
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else:
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self.root._addNextNode(value)
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if __name__ == '__main__':
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bst = BinarySearchTree()
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print "Adding nodes 1 to 10 in the tree..."
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for i in range(1, 10):
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bst.addNode(i)
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print "Is 8 a leaf? ", bst.isLeaf(8)
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print "Whats the level of node 8? ", bst.getNodeLevel(8)
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print "Is node 10 a root? ", bst.isRoot(10)
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print "Is node 1 a root? ", bst.isRoot(1)
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print "Whats the tree height? ", bst.getHeight()
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print "Is this tree BST? ", bst.isBST()
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print "Is this tree balanced? ", bst.isBalanced()
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206
src/extra_interview_problems/trees_paths/binary_tree.py
Executable file
206
src/extra_interview_problems/trees_paths/binary_tree.py
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#!/usr/bin/python
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__author__ = "bt3"
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__email__ = "bt33gl@gmail.com"
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''' Implementation of a binary tree and its properties. For example, the following bt:
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1 ---> level 0
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2 3 ---> level 1
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4 5 ---> level 2
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6 7 ---> level 3
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8 9 ---> level 4
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has the following properties:
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- SIZE OR NUMBER OF NODES: n = 9
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- NUMBER OF BRANCHES OR INTERNAL NODES: b = n-1 = 8
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- VALUE OF ROOT = 1
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- MAX_DEPTH OR HEIGHT: h = 4
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- IS BALANCED? NO
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- IS BST? NO
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'''
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class NodeBT(object):
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def __init__(self, item=None, level=0):
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self.item = item
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self.level = level
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self.left = None
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self.right = None
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def __repr__(self):
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return '{}'.format(self.item)
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def _addNextNode(self, value, level_here=1):
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new_node = NodeBT(value, level_here)
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if not self.item:
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self.item = new_node
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elif not self.left:
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self.left = new_node
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elif not self.right:
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self.right = new_node
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else:
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self.left = self.left._addNextNode(value, level_here+1)
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return self ## this is important, because the node return to the main
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def _searchForNode(self, value):
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if self.item == value:
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return self
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else:
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found = None
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if self.left:
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found = self.left._searchForNode(value)
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if self.right:
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found = found or self.right._searchForNode(value)
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return found
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def _isLeaf(self):
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return not self.right and not self.left
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def _getMaxHeight(self):
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''' Get the max height at the node, O(n)'''
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levelr, levell = 0, 0
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if self.right:
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levelr = self.right._getMaxHeight() + 1
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if self.left:
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levell = self.left._getMaxHeight() + 1
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return max(levelr, levell)
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def _getMinHeight(self, level=0):
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''' Get the min height at the node, O(n)'''
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levelr, levell = -1, -1
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if self.right:
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levelr = self.right._getMinHeight(level +1)
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if self.left:
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levell = self.left._getMinHeight(level +1)
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return min(levelr, levell) + 1
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def _isBalanced(self):
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''' Find whether the tree is balanced, by calculating heights first, O(n2) '''
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if self._getMaxHeight() - self._getMinHeight() < 2:
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return False
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else:
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if self._isLeaf():
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return True
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elif self.left and self.right:
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return self.left._isBalanced() and self.right._isBalanced()
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elif not self.left and self.right:
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return self.right._isBalanced()
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elif not self.right and self.left:
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return self.left._isBalanced()
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def _isBST(self, mintree=None, maxtree=None):
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''' Find whether the tree is a BST, inorder '''
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if self.item:
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if not mintree:
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mintree = self.item
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if not maxtree:
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maxtree = self.item
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if self._isLeaf():
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return True
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elif self.left:
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if self.left.item < self.item and mintree > self.left.item:
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mintree = self.left.item
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return self.left._isBST(mintree, maxtree)
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else:
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return False
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elif self.right:
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if self.right.item > self.item and maxtree < self.right.item:
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maxtree = self.right.item
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return self.right._isBST(mintree, maxtree)
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else:
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return False
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else:
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print('Tree is empty')
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class BinaryTree(object):
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def __init__(self):
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self.root = None
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def addNode(self, value):
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if not self.root:
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self.root = NodeBT(value)
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else:
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self.root._addNextNode(value)
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def isLeaf(self, value):
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node = self.root._searchForNode(value)
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if node:
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return node._isLeaf()
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else:
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print "Node not found."
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def getNodeLevel(self, item):
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node = self.root._searchForNode(item)
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if node:
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return node.level
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else:
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print('Node not found')
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def isRoot(self, value):
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return self.root.item == value
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def getHeight(self):
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return self.root._getMaxHeight()
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def isBalanced(self):
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return self.root._isBalanced()
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def isBST(self):
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return self.root._isBST()
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def preorder(self):
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current = self.root
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nodes, stack = [], []
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while stack or current:
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if current:
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nodes.append(current.item) # thats what change
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stack.append(current)
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current = current.left
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else:
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current = stack.pop()
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current = current.right
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return nodes
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if __name__ == '__main__':
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bt = BinaryTree()
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print "Adding nodes 1 to 10 in the tree..."
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for i in range(1, 10):
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bt.addNode(i)
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print "Is 8 a leaf? ", bt.isLeaf(8)
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print "Whats the level of node 8? ", bt.getNodeLevel(8)
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print "Is node 10 a root? ", bt.isRoot(10)
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print "Is node 1 a root? ", bt.isRoot(1)
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print "Whats the tree height? ", bt.getHeight()
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print "Is this tree BST? ", bt.isBST()
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print "Is this tree balanced? ", bt.isBalanced()
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print (bt.preorder())
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65
src/extra_interview_problems/trees_paths/check_whether_bst.py
Executable file
65
src/extra_interview_problems/trees_paths/check_whether_bst.py
Executable file
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__author__ = "bt3"
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__email__ = "bt33gl@gmail.com"
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""" need to keep track of min and max!!!"""
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from binary_tree import BinaryTree, NodeBT
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from binary_search_tree import BinarySearchTree, NodeBST
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## my solution
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def isBST(bt, mintree=None, maxtree=None):
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if not bt.item:
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|
return True
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|
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if not mintree:
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mintree = bt.item
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if not maxtree:
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maxtree = bt.item
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left, right = False, False
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|
if bt.left:
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|
if bt.left.item > bt.item and bt.left.item < mintree:
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return False
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else:
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|
mintree = bt.left.item
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||||||
|
left = isBST(bt.left, mintree, maxtree)
|
||||||
|
else:
|
||||||
|
left = True
|
||||||
|
if bt.right:
|
||||||
|
if bt.right.item < bt.item and bt.right.item > maxtree:
|
||||||
|
return False
|
||||||
|
else:
|
||||||
|
maxtree = bt.right.item
|
||||||
|
right = isBST(bt.right, mintree, maxtree)
|
||||||
|
else:
|
||||||
|
right = True
|
||||||
|
|
||||||
|
return left or right
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == '__main__':
|
||||||
|
bt = BinaryTree()
|
||||||
|
print "Adding nodes 1 to 10 in the tree..."
|
||||||
|
for i in range(1, 10):
|
||||||
|
bt.addNode(i)
|
||||||
|
|
||||||
|
print(isBST(bt.root))
|
||||||
|
|
||||||
|
bst = BinarySearchTree()
|
||||||
|
print "Adding nodes 1 to 10 in the tree..."
|
||||||
|
for i in range(1, 10):
|
||||||
|
bst.addNode(i)
|
||||||
|
|
||||||
|
print(isBST(bst.root))
|
||||||
|
print(bst.isBST())
|
48
src/extra_interview_problems/trees_paths/lowest_common_ancestor.py
Executable file
48
src/extra_interview_problems/trees_paths/lowest_common_ancestor.py
Executable file
@ -0,0 +1,48 @@
|
|||||||
|
#!/usr/bin/python
|
||||||
|
|
||||||
|
__author__ = "bt3"
|
||||||
|
__email__ = "bt33gl@gmail.com"
|
||||||
|
|
||||||
|
|
||||||
|
from binary_tree import BinaryTree
|
||||||
|
|
||||||
|
|
||||||
|
def inorder(node, path=None):
|
||||||
|
if node:
|
||||||
|
path = path or []
|
||||||
|
path.append(node.item)
|
||||||
|
inorder(node.left, path)
|
||||||
|
inorder(node.right, path)
|
||||||
|
return path
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
def lowest_commom_ancestor(node, node1, node2):
|
||||||
|
path = inorder(node.root)
|
||||||
|
i1, i2 = 0, 0
|
||||||
|
for i,n in enumerate(path):
|
||||||
|
if n == node1:
|
||||||
|
i1 = i
|
||||||
|
if n == node2:
|
||||||
|
i2 = i
|
||||||
|
return path[i1:i2+1]
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == '__main__':
|
||||||
|
bt = BinaryTree()
|
||||||
|
l = [10, 6, 14, 3, 7, 11, 15]
|
||||||
|
for i in l:
|
||||||
|
bt.addNode(i)
|
||||||
|
|
||||||
|
print(l)
|
||||||
|
print(lowest_commom_ancestor(bt, 10, 6))
|
||||||
|
print(lowest_commom_ancestor(bt, 10, 14))
|
||||||
|
print(lowest_commom_ancestor(bt, 10, 3))
|
||||||
|
print(lowest_commom_ancestor(bt, 10, 7))
|
||||||
|
print(lowest_commom_ancestor(bt, 10, 11))
|
||||||
|
print(lowest_commom_ancestor(bt, 10, 15))
|
||||||
|
|
45
src/extra_interview_problems/trees_paths/transversal_BST_ancestor.py
Executable file
45
src/extra_interview_problems/trees_paths/transversal_BST_ancestor.py
Executable file
@ -0,0 +1,45 @@
|
|||||||
|
#!/usr/bin/python
|
||||||
|
|
||||||
|
__author__ = "bt3"
|
||||||
|
__email__ = "bt33gl@gmail.com"
|
||||||
|
|
||||||
|
|
||||||
|
''' find the lowest ancestor in a BST '''
|
||||||
|
|
||||||
|
from transversal_BST_recursively import BSTwithTransversalRecursively
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
def find_ancestor(path, low_value, high_value):
|
||||||
|
while path:
|
||||||
|
current_value = path[0]
|
||||||
|
if current_value < low_value:
|
||||||
|
try:
|
||||||
|
path = path[2:]
|
||||||
|
except:
|
||||||
|
return current_value
|
||||||
|
elif current_value > high_value:
|
||||||
|
try:
|
||||||
|
path = path[1:]
|
||||||
|
except:
|
||||||
|
return current_value
|
||||||
|
elif low_value <= current_value <= high_value:
|
||||||
|
return current_value
|
||||||
|
else:
|
||||||
|
return None # this is probably never touched
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == '__main__':
|
||||||
|
bst = BSTwithTransversalRecursively()
|
||||||
|
l = [10, 5, 15, 1, 6, 11, 50]
|
||||||
|
for i in l:
|
||||||
|
bst.addNode(i)
|
||||||
|
path = bst.preorder()
|
||||||
|
print("The path inorder: ", path)
|
||||||
|
|
||||||
|
print("The path between 1 and 6 is :", find_ancestor(path, 1, 6))
|
||||||
|
print("The path between 1 and 11 is: ", find_ancestor(path, 1, 11))
|
||||||
|
print("The path between 11 and 50 is: ", find_ancestor(path, 11, 50))
|
||||||
|
print("The path between 5 and 15 is: ", find_ancestor(path, 5, 15))
|
Loading…
x
Reference in New Issue
Block a user