dlabx 0.1.0

Dhruv's Lab - A Python library for algorithms and data structures

DLab - Dhruv's Lab

🧠 DLabX - Dhruv's Lab – Learn, Build, and Master Algorithms

DLabX (Dhruv’s Lab) is a comprehensive Python library for algorithms and data structures. It provides efficient and easy-to-use implementations for sorting, searching, dynamic programming, graph algorithms, backtracking, string matching, and more.

DLabXS is ideal for:

🎓 Students learning algorithms and data structures 🧩 Researchers and educators ⚡ Competitive programmers and developers

---

📑 Table of Contents

1. Installation
2. Usage
3. Sorting Algorithms
4. Searching Algorithms
5. Greedy Algorithms
6. Dynamic Programming
7. Backtracking
8. Brute Force
9. Divide and Conquer
10. Data Structures
11. String Matching
12. License
13. Author

Features

• Sorting Algorithms
• Searching Algorithms
• Greedy Algorithms
• Dynamic Programming
• Backtracking Algorithms
• Brute-force Algorithms
• Divide and Conquer Algorithms
• Data Structures(arrays, stacks, queues, linked lists, trees, graphs)
• String Matching Algorithms

---

🚀 Installation

pip install dlabx

🧩 How To Use Dlab:

Import the library: import dlabx as ds

⚙️ Sorting Algorithms Example

arr = [5, 2, 9, 1, 5] sorted_arr = ds.Bubble_Sort(arr) print("Bubble Sort:", sorted_arr)

ds.Bubble_Sort(arr) ds.Selection_Sort(arr) ds.Insertion_Sort(arr) ds.Quick_Sort(arr) ds.Merge_Sort(arr) ds.Heap_Sort(arr) ds.Counting_Sort(arr) ds.Radix_Sort(arr) ds.Shell_Sort(arr) ds.Cocktail_Shaker_Sort(arr) ds.Comb_Sort(arr) ds.Gnome_Sort(arr) ds.Cycle_Sort(arr)

🔍 Searching Algorithms Example

index = ds.Binary_Search([1,2,3,4,5], 3) print("Binary Search:", index)

arr = [1, 2, 3, 4, 5, 6, 7] target = 5

ds.Linear_Search(arr, target) ds.Binary_Search(arr, target) ds.Interpolation_Search(arr, target) ds.Exponential_Search(arr, target) ds.Jump_Search(arr, target) ds.Ternary_Search(arr, target) ds.Fibonacci_Search(arr, target)

Graph Searches

g = ds.Graph(3) g.add_edge(0, 1) g.add_edge(1, 2) ds.Bfs(g, 0) ds.Dfs(g, 0)

💰 Greedy Algorithm Example

edges = [(0,1,10), (0,2,6), (1,2,5)] mst = ds.Kruskal_Mst(3, edges) print("Kruskal MST:", mst)

edges = [(0,1,10), (0,2,6), (1,2,5)] ds.Kruskal_Mst(3, edges)

graph = [[0, 2, 0], [2, 0, 3], [0, 3, 0]] ds.Prim_Mst(graph)

graph = [[0, 4, 0], [4, 0, 8], [0, 8, 0]] ds.Dijkstra(graph, 0)

edges = [(0,1,4),(0,2,5),(1,2,-2)] ds.Bellman_Ford(3, edges, 0)

values = [60, 100, 120] weights = [10, 20, 30] capacity = 50 ds.Fractional_Knapsack(values, weights, capacity)

🧮 Dynamic Programming

ds.Longest_Common_Subsequence("AGGTAB","GXTXAYB")

ds.Longest_Palindromic_Subsequence("abacdfgdcaba")

ds.Edit_Distance("kitten","sitting")

ds.Knapsack_01([60,100,120],[10,20,30],50)

ds.Unbounded_Knapsack([60,100,120],[10,20,30],50)

ds.Subset_Sum([3,34,4,12,5,2], 9)

ds.Can_Partition([1,5,11,5])

ds.Unique_Paths(3,7)

ds.Min_Path_Sum([[1,3,1],[1,5,1],[4,2,1]])

ds.Longest_Increasing_Path([[9,9,4],[6,6,8],[2,1,1]])

ds.Matrix_Chain_Order([10,20,30,40])

ds.Optimal_Bst([10,12,20], [34,8,50], 3)

ds.Catalan_Numbers(5)

ds.Bell_Numbers(5)

ds.Count_Paths([[0,0,0],[0,0,0]])

♟️ Backtracking Algorithms

ds.N_Queens(4)

ds.Sudoku([[5,3,0,0,7,0,0,0,0], ...])

ds.Maze([...])

ds.Generate_Permutations([1,2,3])

ds.Generate_Combinations([1,2,3],2)

ds.Subset_Sum([1,2,3,4],5)

ds.Knights_Tour(8)

ds.Exist_Word([...],"word")

ds.Hamiltonian_Path([...])

ds.Graph_Coloring([...],3)

ds.Partition_Array([...])

ds.K_Coloring([...],3)

ds.Sum_Of_Subsets([...],10)

ds.Generate_Power_Set([1,2,3])

ds.Partition_Into_K_Subsets([1,2,3,4],2)

🧠 Brute-force Algorithms

ds.Generate_Permutations([1,2,3])

ds.Generate_Subsets([1,2,3])

ds.Naive_Search("pattern","text")

ds.Distance([...])

ds.Tsp_Brute_Force([...])

ds.Knapsack_Bruteforce([...])

⚡ Divide and Conquer Algorithms

ds.Strassen_Matrix_Multiplication([[1,2],[3,4]], [[5,6],[7,8]])

ds.Closest_Pair_Of_Points([...])

ds.Fft([...])

ds.Karatsuba(1234,5678)

ds.Convex_Hull([...])

ds.Maximum_Subarray([...])

🧱 Data Structures

Stack

stack = ds.Stack() stack.push(10) stack.pop()

Queue

queue = ds.Queue() queue.enqueue(1) queue.dequeue()

Linked Lists

sll = ds.SinglyLinkedList() dll = ds.DoublyLinkedList() cll = ds.CircularLinkedList()

Trees

bst = ds.BinarySearchTree() avl = ds.AVLTree() rbt = ds.RedBlackTree() trie = ds.Trie() nary = ds.NAryTree()

Graphs

graph = ds.Graph(3) weighted = ds.WeightedGraph(3) bipartite = ds.BipartiteGraph()

🔡 String Matching Algorithms

text = "ABABDABACDABABCABAB" pattern = "ABABCABAB"

ds.Kmp_Search(text, pattern)

ds.Rabin_Karp_Search(text, pattern)

ds.Boyer_Moore_Search(text, pattern)

ds.Boyer_Moore_Horspool_Search(text, pattern)

ds.Ahocorasick_Search([...], pattern)

ds.Bitap_Search(text, pattern)

ds.Finite_Automaton_Search(text, pattern)

ds.Z_Array_Search(text, pattern)

ds.Suffix_Array_Search(text, pattern)

ds.Suffix_Automaton_Search(text, pattern)

ds.Suffix_Tree_Search(text, pattern)

ds.Streaming_Pattern_Matcher_Search(text, pattern)

ds.Sunday_Search(text, pattern)

ds.Wumanber_Search(text, pattern)

🧾 License Licensed under the MIT License.

👨‍💻 Author Dhruv Sonani Creator of DLab - Dhruv’s Lab

📧 Email: [e-mail] 🌐 GitHub: https://github.com/dhruv-005