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Easy Algorithm & Data Structure

Project description

Installation

pip3 install --upgrade ezcode

PyPi Releases

https://pypi.org/project/ezcode/#history

Tree

Binary Tree Printer

>>> class Node:
...     def __init__(self, v=None, l=None, r=None):
...         self.v = v
...         self.l = l
...         self.r = r
... 
>>> from ezcode.tree.printer import BinaryTreePrinter
>>> root = Node(0, Node(1, Node(3, r=Node(7)), Node(4)), Node(2, Node(5, Node(8), Node(9)), Node(6)))
>>> printer = BinaryTreePrinter(data_name="v", left_name="l", right_name="r")
>>> printer.print(root)

       ┌──────────(0)──────────┐       
 ┌────(1)────┐           ┌────(2)────┐ 
(3)─┐       (4)       ┌─(5)─┐       (6)
   (7)               (8)   (9)         

Random Binary Tree

>>> from ezcode.tree.binary_tree import RandomBinaryTree
>>> tree = RandomBinaryTree(size=10, lower_bound=-5, upper_bound=10)
>>> tree.print()

           ┌────────────(3)────────────┐           
    ┌────(-4)─────┐                   (5)─────┐    
 ┌─(8)         ┌─(6)                      ┌──(9)─┐ 
(6)          (-2)                        (2)    (2)

>>> tree.make_tree()
>>> tree.print()

        ┌────────────(6)────────────┐        
 ┌─────(7)─────┐             ┌─────(6)─────┐ 
(9)         ┌─(1)──┐        (9)        ┌──(3)
           (1)    (5)                (10)    

Algorithm

Traversals

>>> from ezcode.tree.binary_tree import BinaryTree
>>> root = Node(0, Node(1, Node(3, r=Node(7)), Node(4)), Node(2, Node(5, Node(8), Node(9)), Node(6)))
>>> tree = BinaryTree(root, data_name="v", left_name="l", right_name="r")
>>> tree.print()

       ┌──────────(0)──────────┐       
 ┌────(1)────┐           ┌────(2)────┐ 
(3)─┐       (4)       ┌─(5)─┐       (6)
   (7)               (8)   (9)         
     
>>> print(f" Pre-Order: {tree.traversal('pre-order')}")
>>> print(f"  In-Order: {tree.traversal('in-order')}")
>>> print(f"Post-Order: {tree.traversal('post-order')}")

 Pre-Order: [0, 1, 3, 7, 4, 2, 5, 8, 9, 6]
  In-Order: [1, 3, 7, 4, 0, 2, 5, 8, 9, 6]
Post-Order: [1, 3, 7, 4, 2, 5, 8, 9, 6, 0]

Lowest Common Ancestor

>>> from ezcode.tree.binary_tree import BinaryTree
>>> root = Node(0, Node(1, Node(3, r=Node(7)), Node(4)), Node(2, Node(5, Node(8), Node(9)), Node(6)))
>>> tree = BinaryTree(root, data_name="v", left_name="l", right_name="r")
>>> tree.print()

       ┌──────────(0)──────────┐       
 ┌────(1)────┐           ┌────(2)────┐ 
(3)─┐       (4)       ┌─(5)─┐       (6)
   (7)               (8)   (9)         

>>> n6, n7, n8 = root.r.r, root.l.l.r, root.r.l.l
>>> tree.node_data(tree.lowest_common_ancestor([n6, n8]))
2
>>> tree.node_data(tree.lowest_common_ancestor([n6, n7, n8]))
0

Subtree Stats

>>> from ezcode.tree.binary_tree import BinaryTree
>>> root = Node(-2, Node(8, Node(-4, l=Node(-2)), Node(3, l=Node(-1))), Node(-3, l=Node(2, Node(10), Node(7))))
>>> tree = BinaryTree(root, data_name="v", left_name="l", right_name="r")
>>> tree.print()

            ┌───────────(-2)────────────┐ 
     ┌─────(8)─────┐             ┌────(-3)
  ┌(-4)         ┌─(3)        ┌──(2)─┐     
(-2)          (-1)         (10)    (7)    

>>> print(f"Subtree Sum Min: {tree.subtree('sum-min')}")
>>> print(f"Subtree Sum Max: {tree.subtree('sum-max')}")
>>> print(f"Subtree Avg Min: {tree.subtree('avg-min')}")
>>> print(f"Subtree Avg Max: {tree.subtree('avg-max')}")

Subtree Sum Min: -6
Subtree Sum Max: 19
Subtree Avg Min: -3.0
Subtree Avg Max: 10.0

Max Path Sum

>>> from ezcode.tree.binary_tree import BinaryTree
>>> root = Node(-2, Node(8, Node(-4, l=Node(-2)), Node(3, l=Node(-1))), Node(-3, l=Node(2, Node(10), Node(7))))
>>> tree = BinaryTree(root, data_name="v", left_name="l", right_name="r")
>>> tree.print()

            ┌───────────(-2)────────────┐ 
     ┌─────(8)─────┐             ┌────(-3)
  ┌(-4)         ┌─(3)        ┌──(2)─┐     
(-2)          (-1)         (10)    (7)    

>>> tree.max_path_sum()
19

Depth & Balance

>>> from ezcode.tree.binary_tree import BinaryTree
>>> root = Node(0, Node(0, Node(0), Node(0, r=Node(0))), Node(0, Node(0), Node(0, r=Node(0, l=Node(0)))))
>>> tree = BinaryTree(root, data_name="v", left_name="l", right_name="r")
>>> tree.print()

             ┌──────────────────────(0)──────────────────────┐                   
 ┌──────────(0)──────────┐                       ┌──────────(0)──────────┐       
(0)                     (0)────┐                (0)                     (0)────┐ 
                              (0)                                           ┌─(0)
                                                                           (0)   

>>> [tree.depth(), tree.is_balanced()]
[5, False]

>>> root = Node(0, Node(0, Node(0, l=Node(0)), Node(0, r=Node(0))), Node(0, Node(0), Node(0, l=Node(0))))
>>> tree.root = root
>>> tree.print()

          ┌──────────(0)──────────┐       
    ┌────(0)────┐           ┌────(0)────┐ 
 ┌─(0)         (0)─┐       (0)       ┌─(0)
(0)               (0)               (0)   

>>> [tree.depth(), tree.is_balanced()]
[4, True]

Serialization & Deserialization

>>> from ezcode.tree.printer import BinaryTreePrinter
>>> from ezcode.tree.binary_tree import BinaryTree
>>> printer = BinaryTreePrinter(data_name="v", left_name="l", right_name="r")
>>> root = Node(1, Node(2), Node(3, Node(4), Node(5)))
>>> tree = BinaryTree(root, data_name="v", left_name="l", right_name="r")
>>> tree.print()

 ┌────(1)────┐    
(2)       ┌─(3)─┐ 
         (4)   (5)

>>> serialized = tree.serialize(delimiter=",")
>>> print(serialized)

1,2,3,None,None,4,5,None,None,None,None

>>> printer.print(tree.deserialize(formatter=int, string=serialized, delimiter=","))

 ┌────(1)────┐    
(2)       ┌─(3)─┐ 
         (4)   (5)

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