Metadata-Version: 2.4
Name: dsatantra
Version: 0.5.0
Summary: A package containing C++ code implementations for common DSA problems
Home-page: https://github.com/GitUtk/dsa-pkg-pypi
Author: Utkarsh
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Dynamic: author
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: requires-python
Dynamic: summary

# dsatantra

A Python package that provides C++ implementations for common Data Structures and Algorithms (DSA) problems. Useful for competitive programming, template generation, and educational learning.

## Installation

```bash
pip install dsatantra
```

## Usage

```python
from dsatantra import *

# 1. List all available DSA problems in numerical order
dsatantra_search()

# 2. Retrieve C++ implementation for a specific problem number (e.g. 33)
code = dsatantra_get(33)
```

## Available Problems

1. Binary Search (Basic Iterative with Sorting)
2. Merge Sort (Basic)
3. Quick Sort (Basic)
4. Binary Search using Divide and Conquer
5. First and Last Occurrence of Element in a Sorted Array
6. Merge Sort with Recursion & Comparison Tracking
7. Inversion Pairs Count using Merge Sort
8. Quick Sort with Calls & Comparison Tracking
9. Contiguous Subarray with Largest Sum (Kadane's Algorithm)
10. Kth Largest Element in an Array (Min Heap)
11. Missing Number of the Sequence
12. Merge Sorted Array
13. Longest Binary Subarray after K Flips
14. Sorting by Set Bit Count using Divide and Conquer
15. Book Allocation with Minimum Maximum Load
16. Minimum Element in Rotated Sorted Array
17. Search in Rotated Sorted Array
18. Koko Eating Bananas
19. Single Number
20. Kth Missing Positive Number
21. Merge Two Sorted Linked Lists
22. Basic Hash Table Implementation
23. Hash Table with Double Hashing
24. Hash Table with Linear Probing
25. Hash Table with Quadratic Probing
26. Count Frequencies of Elements using Hashing
27. Check Nearby Duplicates using Hashing
28. Check for Pair with Given Sum using Hashing
29. Count Distinct Elements in Every Window of Size K
30. Top K Frequent Elements
31. Group Anagrams
32. Find Pair of Numbers with Target Sum
33. Hash Table with Separate Chaining
