dsa-daa-kit 0.1.0

A clean, modern, and DAA-friendly Python library that implements all major Data Structures and Algorithms (DSA) with tracing, operation counters, and benchmarking utilities.

DAA-Kit

A Modern Python Library for Data Structures & Algorithm Analysis

Designed by Venu Enugula

🚀 Overview

DAA-Kit is a modern, minimal, production-grade Python library that implements:

• Core Data Structures
• All major DSA algorithms
• Complete DAA syllabus algorithms
• Optional tracing, complexity counters, and state-wise execution logs
• Tools for benchmarking, experimenting, and visualizing algorithms

This makes it perfect for:

• ✅ DAA Lab programs
• ✅ Engineering semester exams
• ✅ Competitive programming
• ✅ Interview preparation
• ✅ Teaching & research
• ✅ Algorithm experimentation & analysis

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📦 Key Features

1. Clean, readable implementations

Every algorithm is written with clarity, type hints, and clean code.

2. DAA-friendly tracing

Most algorithms support:

• return_trace=True
• Step-by-step execution logs
• Operation counters (comparisons, swaps, relaxations, recursive calls)

3. Unified API

Consistent naming across the library: binary_search, merge_sort, dijkstra, knapsack_01, etc.

4. Built-in experiment tools

• Time complexity measurement
• Input-scaling experiments
• Auto-plotting (optional)

5. Modular structure

• Arrays
• Trees
• Graphs
• Dynamic Programming
• Greedy
• Backtracking
• Branch & Bound

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📁 Repository Structure

src/
  dsa_daa_kit/
    arrays.py
    greedy.py
    graphs.py
    dp.py
    backtracking.py
    branch_bound.py
    ...
tests/
  test_arrays.py
  test_graphs.py
  test_dp.py

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⚡ Installation

After uploading to PyPI:

pip install dsa-daa-kit

Or from source:

pip install -e .

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✨ Quick Examples

Binary Search with tracing

from dsa_daa_kit.arrays import binary_search

index, trace = binary_search([1,3,5,7,9], 7, return_trace=True)

print(index)   # 3
print(trace)   # dumps all search steps

0/1 Knapsack (DP)

from dsa_daa_kit.dp import knapsack_01

value = knapsack_01([10, 20, 30], [60, 100, 120], 50)
print(value)

Dijkstra

from dsa_daa_kit.graphs import dijkstra

dist = dijkstra(graph, source=0)
print(dist)

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📚 Included Algorithms

Arrays & Searching

• Linear Search
• Binary Search (iterative & recursive)
• Merge Sort
• Quick Sort
• Bubble, Insertion, Selection Sort

Linked Lists

• Singly, Doubly
• Insert, delete, reverse

Trees

• BST (insert, search, delete)
• Traversals (inorder, preorder, postorder)
• Heap + HeapSort

Graphs

• BFS, DFS
• Dijkstra, Bellman-Ford
• Kruskal, Prim
• Topological Sort

Greedy

• Activity Selection
• Fractional Knapsack
• Huffman Coding

Dynamic Programming

• 0/1 Knapsack
• Unbounded Knapsack
• LIS
• Matrix Chain Multiplication
• Coin Change

Backtracking

• N-Queens
• Subset Sum
• Sudoku Solver
• TSP (backtracking version)

Branch & Bound

• 0/1 Knapsack
• TSP
• Job Assignment Problem

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🔍 Tracing & Complexity Tools

from dsa_daa_kit.utils.tracing import OperationCounter

counter = OperationCounter()

binary_search(arr, x, counter=counter)

print(counter.comparisons)

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🧪 Testing

pytest

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📜 License

This project is licensed under the MIT License.

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👤 Author

Venu Enugula Python • ML • Systems • Algorithms