Datastructures-Algorithms 0.0.1

Implementation of data structures and algorithms in python

This library is created to understand and implement Data Structures and Algorithms in python. Since most courses on data structure and algorithm uses programming lanugages such as c and c++ which contains pointers and python does not so to implement data structures and algorithms in python remains quite unintiutive to most of the students. This library is also useful to implement some custom algorithm without worrying about implementation of fundamental data structures and run of the mill algorithms. ____________________________________________________________________________________________________________________________________ Documentation ____________________________________________________________________________________________________________________________________

ARRAYS Arrays implementation here is to mimic static arrays used in c and c++ along with implementation some of the methods are also available such as insertion, deletion, access, update and lenght.

# Creating a list using class Lists list1 = Lists(size=size)

# Inserting 5 elements in array list1.insert(element=3) list1.insert(element=7) list1.insert(element=9) list1.insert(element=2) list1.insert(element=1)

# Inserting an element at specified location list1.insert(element=5, index=2)

# Deleting from index of the array list1.delete(2)

# Deleting from end of the array list1.delete()

# update index list1.update(element=5, index=4)

# accesing a single element list1.access(1)

# accesing all elements # accesing a single element list1.access() =============================================================================================================================

LINKED LIST Since python does not contain pointers implementation of linked list is not trivial hence it confuses students the most. Here linked lists is similar to c implementation. It also contains some generic methods for Linked lists such as insertion, deletion, access and length.

# Initializing a linked list head = linkedList()

# Inserting some elements in linked list head.insert(10) head.insert(5) head.insert(6)

# Inserting elements at end of list head.insert(4, -1)

# Displaying all elements of the list head.access()

# Number of elements in the list head.length() =============================================================================================================================

QUEUE Queue is one of the most basic and important data structure in computer science and its implementation is quite straight forward but time consuming this library intends to cut focus from making queues form scratch instead make algorithms from it. It comes with some most useful methods such as head, tail, enqueue, dequeue and access.

# Initializing a queue q = Queue()

# Inserting some elements in queue q.enqueue(50) q.enqueue(59) q.enqueue(41) q.enqueue(5) q.enqueue(1)

# Deleting an element q.dequeue()

# accessing by index q.access(2)

# accessing all elements q.access()

# Position of head q.head()

# Position of tail q.tail() ============================================================================================================================

STACK Stack is most famous and widely used data structure and its implementation is easier than queue and even more easy in python. This library poses this data structure too. Happy first in first out. This library contains push, pop, n_elements, top_element.

# Initializing Stack stack1 = Stack()

# Inserting elements in stack stack1.push(150) stack1.push(5) stack1.push(8) stack1.push(1)

# deleting an element from stack stack1.pop()

# Number of elements in stack stack1.n_elements()

# Element at top of stack stack1.top_element() ============================================================================================================================

Binary Search Tree Binary search tree is one of most complicated data structure to understand and implementat especially in python due to lack of pointers. This package tries to cover all the nuances of BST such as insertion, deletion, max element, min element, height of tree, traversals such as breadth first, depth first including preorder, inorder and postorder traversala and a function to check whether given tree is BST or not.

# Initializing tree tree = BinarySearchTree()

# Inserting element at root root = tree.insert(6)

# Inserting elemnts root.insert(12) root.insert(4)

# Maximum value in tree root.max_element()

# Minimun value in tree root.min_element()

# height of tree root.height()

# Bfs traversal root.bfs_traversal([root])

# Pre order depth first traversal root.pre_order_dfs()

# Inorder traversal root.in_order_dfs()

# Post order traversal root.post_order_dfs()

# Checking whether a tree is BST or not root.isBST()

# Deleting value from tree root.delete(8) ============================================================================================================================

SORTING ALGORITHMS Currently this library contains few sorting algorithms such as insertion sort, bubble sort, merge sort and heap sort. In future revision more will be added.

# Instertion sort insertion_sort(array)

# Bubble sort bubble_sort(array)

# Merge sort merge_sort(array)

# Heap sort heap_sort(array) ============================================================================================================================

More algorithms and data structures in future updates.

Change Log

0.0.1 (5/04/2021)

First release.