dsaedge 0.3.0

A comprehensive Python package for various data structures and algorithms implementations.

dsaedge: Data Structures and Algorithms in Python

A comprehensive collection of various data structures and algorithms implemented in Python.

Installation

You can install this package using pip:

pip install dsaedge

Usage

Here are some examples of how to use the implemented data structures and algorithms:

Linked Lists

from dsaedge.linked_lists.singly_linked_list import LinkedList

ll = LinkedList()
ll.append(10)
ll.prepend(5)
print(ll)

Sorting Algorithms

from dsaedge.sorting.sorting_algorithms import Sorting

arr = [64, 34, 25, 12, 22, 11, 90]
sorted_arr = Sorting.bubble_sort(arr[:])
print(sorted_arr)

Searching Algorithms

from dsaedge.searching.searching_algorithms import Searching

arr = [1, 5, 2, 8, 3]
index = Searching.linear_search(arr, 8)
print(f"Element found at index: {index}")

Graph Algorithms

from dsaedge.graphs.graph_representation import Graph

graph = Graph()
graph.add_edge('A', 'B', weight=4)
graph.add_edge('A', 'C', weight=2)

# Example BFS
bfs_result = graph.bfs('A')
print(f"BFS Traversal: {bfs_result}")

# Example Dijkstra
distances, predecessors = graph.dijkstra('A')
print(f"Dijkstra distances from A: {distances}")

Implemented Data Structures and Algorithms

The dsaedge package is organized into several modules, each focusing on a specific category of data structures or algorithms.

Data Structures

• advanced_data_structures
  • disjoint_set_union.py: Disjoint Set Union (DSU)
  • fenwick_tree.py: Fenwick Tree (Binary Indexed Tree)
  • segment_tree.py: Segment Tree
  • trie.py: Trie (Prefix Tree)
• hash_tables
  • hash_table.py: Hash Table (with chaining)
• heaps
  • min_heap.py: Min-Heap
• linked_lists
  • circular_singly_linked_list.py: Circular Singly Linked List
  • doubly_linked_list.py: Doubly Linked List
  • singly_linked_list.py: Singly Linked List
• trees
  • avl_tree.py: AVL Tree
  • binary_search_tree.py: Binary Search Tree (BST)
  • binary_tree.py: Generic Binary Tree (with traversals)

Algorithms

• algorithmic_paradigms
  • kmp_search.py: Knuth-Morris-Pratt (KMP) string searching
  • knapsack_problem.py: Knapsack Problem (Dynamic Programming)
  • longest_common_subsequence.py: Longest Common Subsequence (Dynamic Programming)
  • n_queens.py: N-Queens Problem (Backtracking)
  • sudoku_solver.py: Sudoku Solver (Backtracking)
• graphs
  • bellman_ford.py: Bellman-Ford Algorithm
  • floyd_warshall.py: Floyd-Warshall Algorithm
  • graph_representation.py: Graph Representation (Adjacency List) and common graph algorithms (BFS, DFS, Dijkstra, Prim, A*, Cycle Detection, SCC)
  • kruskal_algorithm.py: Kruskal's Algorithm
  • topological_sort.py: Topological Sort
• searching
  • searching_algorithms.py: Linear Search, Binary Search, Jump Search, Exponential Search
• sorting
  • sorting_algorithms.py: Bubble Sort, Selection Sort, Insertion Sort, Merge Sort, Quick Sort, Heap Sort, Counting Sort, Radix Sort

Contributing

Contributions are welcome! Please feel free to open issues or submit pull requests.

License

This project is licensed under the MIT License - see the LICENSE file for details.