easydsi 2.0.1

A Python library that helps developers implement data structures & algorithms easily.

📌 easydsi 2.0.1

🚀 easydsi is a Python library designed to simplify Data Structures and Algorithms (DSA), allowing users to focus on coding without worrying about implementation details.

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📂 Features

• Heap
  • MinHeap()
  • MaxHeap()
• Queue
• Stack
• Tree
  • BinaryTree()
  • BinarySearchTree()

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📦 Heap

🛠️ Initialization

• MinHeap() or MinHeap([list]) - Creates a MinHeap.
• MaxHeap() or MaxHeap([list]) - Creates a MaxHeap.
• Heap(data=None, max_heap=False) - Creates a generic heap that can be a MinHeap or MaxHeap.

This module provides utility functions for performing various operations on a Heap object, including retrieving statistics, sorting, merging, and clearing the heap.

📌 Methods and Descriptions

• heapify_list(data, max_heap=False)
  Converts a list into a MinHeap or MaxHeap.

• merge_heaps(heap1, heap2, max_heap=False)
  Merges two heaps into a new MinHeap or MaxHeap.

• is_heap_sorted(heap, max_heap=False)
  Checks if a given heap is sorted.

• get_top_n(heap, n=1)
  Retrieves the top n elements from a MinHeap or MaxHeap.

• heap_sort(data, descending=False)
  Sorts a list using Heap Sort.

• contains(heap, element)
  Checks if an element exists in the heap.

• clear_heap(heap)
  Removes all elements from the heap.

• size(heap)
  Returns the number of elements in the heap.

• sum_heap(heap)
  Computes the sum of all elements in the heap.

• max_in_heap(heap)
  Returns the maximum element in the heap.

• min_in_heap(heap)
  Returns the minimum element in the heap.

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📦 Stack

🛠️ Initialization

• Stack() - Creates a stack.

📌 Methods and Descriptions

• reverse_stack()
  Reverses the order of elements in a stack.

• sort_stack()
  Sorts a stack in ascending order.

• duplicate_stack()
  Creates a duplicate of a stack without modifying the original.

• sum_stack()
  Computes the sum of all elements in a stack.

• max_in_stack()
  Finds the maximum value in a stack.

• min_in_stack()
  Finds the minimum value in a stack.

• merge_stacks()
  Merges two stacks into one, maintaining order.

• is_balanced()
  Checks if a given expression has balanced parentheses.

• remove_duplicates()
  Removes duplicate elements from a stack while maintaining order.

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📦 Queue

🛠️ Initialization

• Queue() or Queue([list]) - Creates a queue.

This module provides utility functions for performing various operations on a Queue object, including retrieving statistics, sorting, reversing, and clearing the queue.

📌 Methods and Descriptions

• get_max(queue, visualize=False)
  Returns the maximum numerical value in the queue.

• get_min(queue, visualize=False)
  Returns the minimum numerical value in the queue.

• get_sum(queue, visualize=False)
  Computes the sum of all numerical values in the queue.

• get_avg(queue, visualize=False)
  Computes the average of all numerical elements in the queue.

• reverse_queue(queue, inplace=False, visualize=False)
  Reverses the order of elements in the queue.

• sort_queue(queue, descending=False, inplace=False, visualize=False)
  Sorts the queue in ascending order by default. Use descending=True for descending order.

• clear_queue(queue, visualize=False)
  Removes all elements from the queue.

• contains(queue, item, visualize=False)
  Checks if a specific item exists in the queue.

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🌳 Tree

🛠️ Initialization

• BinaryTree() or BinaryTree(root_value) - Creates a Binary Tree with an optional root value.
• BinarySearchTree() or BinarySearchTree(root_value) - Creates a Binary Search Tree with an optional root value.

This module provides utility functions for performing various operations on a Tree object, including retrieving statistics, searching, traversing, and modifying the tree.

📌 Methods and Descriptions

• contains(tree, value)
  Checks if a tree contains a specific value.

• sum_tree(tree)
  Returns the sum of all elements in the tree.

• max_in_tree(tree)
  Returns the maximum value in the tree.

• min_in_tree(tree)
  Returns the minimum value in the tree.

• count_nodes(tree)
  Returns the total number of nodes in the tree.

• count_leaves(tree)
  Returns the number of leaf nodes in the tree.

• get_height(tree)
  Returns the height of the tree.

• inorder(tree)
  Returns the in-order traversal of the tree (Left, Root, Right).

• preorder(tree)
  Returns the pre-order traversal of the tree (Root, Left, Right).

• postorder(tree)
  Returns the post-order traversal of the tree (Left, Right, Root).

• levelorder(tree)
  Returns the level-order traversal of the tree (Breadth-First Traversal).

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📥 Installation

Run the following command to install:

pip install easydsi

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🚀 Quick Start

Import the library into your project:

from easydsi.tree.binary_tree import BinaryTree, BinarySearchTree
from easydsi.tree.tree_utils import max_in_tree, sum_tree

🎯 Working with Tree

🔹 Initialize a tree

bt = BinaryTree([3, 5, 1, 7, 2])
print(bt)

Output:

    __3
   /   \
  5     1
 / \
7   2

🔹 Get maximum value in Binary Search Tree

bst = BinarySearchTree([10, 5, 15, 2, 7])
print(max_in_tree(bst))

Output:

15

🔹 Get all elements after adding 6

bt.add(6)
print(bt.get_elements())

Output:

[3, 5, 1, 7, 2, 6]

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📊 Statistics