ek-data-structures 0.0.2

A Python package that implements common data structures such as Array, Stack, Queue, Linked List, Binary Tree, and Graph.

Data Structure Package

This package provides implementations of several common data structures and their basic operations. The package includes:

• Array
• Linked List
• Stack
• Queue
• Binary Tree
• Graph

Each data structure is implemented with a set of core methods, providing users with the ability to manipulate and interact with the data structures in a straightforward way. Below is an overview of each data structure and the operations available.

Table of Contents

1. Array Class
2. Stack Class
3. Queue Class
4. Linked List Class
5. Binary Tree Class
6. Graph Class
7. Installation
8. Usage

---

Array Class

The Array class provides basic operations on dynamic arrays, allowing for efficient management and manipulation of array data.

Supported Operations:

• length() - Returns the number of elements in the array.
• append(item) - Adds an item to the end of the array.
• insert(index, item) - Inserts an item at a specific index.
• remove(item) - Removes the first occurrence of the item.
• contains(item) - Checks if an item exists in the array.
• clear() - Clears all elements in the array.
• is_equal(other_array) - Compares if two arrays are equal.
• concatenate(other_array) - Concatenates another array to the current one.
• pop() - Removes the last item from the array by default else you can specify index.
• delete(index) - Removes an item at a specific index.

Example:

arr = Array()
arr.append(10)
arr.append(20)
arr.insert(1, 15)
print(arr.length())  # Output: 3
arr.remove(15)
print(arr.contains(10))  # Output: True

---

Stack Class

The Stack class provides a LIFO (Last In First Out) data structure to push and pop items.

Supported Operations:

• push(item) - Adds an item to the top of the stack.
• pop() - Removes and returns the top item.
• top() - Returns the top item without removing it.
• size() - Returns the number of items in the stack.
• is_empty() - Checks if the stack is empty.
• display_stack() - Displays the elements in the stack.

Example:

s = Stack()
s.push(10)
s.push(20)
s.push(30)
s.push(40)
s.display_stack() #[10, 20, 30, 40]
print(s.top())    # Output: 40
s.pop()           # Output: 40
print(s.size())   # Output: 3
s.display_stack() #[10, 20, 30]

---

Queue Class

The Queue class provides a FIFO (First In First Out) data structure with operations to add, remove, and inspect items in the queue.

Supported Operations:

• enqueue(item) - Adds an item to the rear/end of the queue.
• dequeue() - Removes and returns the front item.
• peek() / front()` - Returns the front item without removing it.
• rear() - Returns the rear/end item.
• is_full() - Checks if the queue is full.
• is_empty() - Checks if the queue is empty.
• display_queue() - Displays the elements in the queue.

Example:

q = Queue()
q.enqueue(10)
q.enqueue(20)
q.enqueue(30)
q.enqueue(40) 
q.display_queue() #[10, 20, 30, 40]
print(q.rear())  # Output: 40
q.dequeue()
q.display_queue() #[20, 30, 40]
print(q.front())  # Output: 20

---

Linked List Class

The LinkedList class implements a single linked list with methods to add, remove, and access elements in the list.

Supported Operations:

• insert_start(item) - Inserts an item at the beginning of the list.
• insert_after(item, index) - Inserts an item after a specific node.
• insert_end(item) - Inserts an item at the end of the list.
• delete_item(index) - Deletes the item at specific index.
• display() / traverse() - Displays the entire list.
• search(item) - Searches for an item in the list and returns True if it exist else False.
• get_length() - Returns the number of nodes in the list.
• access(index) - Accesses the node at a specific index.
• update(index, item) - Updates the node at a specific index with a new item.

Example:

ll = LinkedList()
ll.insert_start(10)
ll.insert_end(20)
ll.insert_after(15,0)
ll.display()  # Output: 10 -> 15 -> 20 -> None

---

Binary Tree Class

The BinaryTree class implements a binary tree, offering methods for traversal and modification of the tree.

Supported Operations:

• insert(item) - Inserts an item into the tree.
• search(item) - Searches for an item in the tree returns True if exists else False.
• delete(item) - Deletes an item from the tree.
• in_order() - Traverses the tree in-order (left, root, right).
• pre_order() - Traverses the tree pre-order (root, left, right).
• post_order() - Traverses the tree post-order (root, right, left).

Example:

r"""
      3
    /   \
   1     4
    \
     2
     """
bt = BinaryTree()
bt.insert("3")
bt.insert("1")
bt.insert("2")
bt.insert("4")
bt.in_order()  # Output: 1 -> 2 -> 3 -> 4 (left root right)
bt.pre_order()  # Output: 3 -> 1 -> 2 -> 4 (root left right)
bt.post_order()  # Output: 3 -> 4 -> 1 -> 2 (root right left)

---

Graph Class

The Graph class implements an undirected graph using an adjacency list. This class includes various methods for adding and removing vertices and edges, as well as performing DFS and BFS traversals.

Supported Operations:

• add_vertex(vertex) - Adds a vertex to the graph.
• add_edge(vertex1, vertex2) - Adds an undirected edge between two vertices.
• remove_vertex(vertex) - Removes a vertex and all edges associated with it.
• remove_edge(vertex1, vertex2) - Removes the edge between two vertices.
• has_edge(vertex1, vertex2) - Checks if an edge exists between two vertices.
• dfs(start_vertex, visited) - Performs Depth-First Search from a starting vertex.
• bfs(start_vertex) - Performs Breadth-First Search starting from a given vertex.
• find_path(start, end, path) - Finds a path from start to end using DFS.
• search(vertex) - Searches for a vertex in the graph. Returns True if found, else False.
• display_graph() - Displays the adjacency list of the graph.

Example:

g = Graph()
g.add_vertex("A")
g.add_vertex("B")
g.add_vertex("C")
g.add_edge("A", "B")
g.add_edge("B", "C")
g.display_graph()
# Output:
# A: ['B']
# B: ['A', 'C']
# C: ['B']

g.dfs("A", visited=set())  # Output: A B C
g.bfs("A")  # Output: A B C
g.find_path("A", "C", path=[])  # Output: A -> B -> C

---

Installation

To install the package directly from PyPI using:

pip install ek-data-structures

---

Usage

After installation, you can import the data structures into your Python code:

from ek_data_structures import Array, LinkedList, Queue, Stack, BinaryTree

# Example usage
arr = Array()
arr.append(5)
print(arr.length())