A python library to handle dataStructures
Project description
updated: Wednesday, 12th July 2023
dataStax
What's New?
- Refactored Array Contents
- Added AbstractArray SubModule to abstract print logic
- Added more test cases for Queues
- Type Checked Arrays and Lists with mypy
Table of Contents
Introduction
- This library offers a simple yet powerful solution for implementing common abstract data structures.
- With a pure Python implementation, it provides representations of tree, linked list, and array-based data structures accessible through a basic command prompt interface.
- The package includes visualization features that enhance the understanding of each data structure.
- Students can greatly benefit from utilizing this package for their learning and educational purposes.
- Please note that this project is currently a work in progress and undergoing active development.
Problem Statement
- Many CS students encounter difficulties in comprehending the intricate internal architecture of complex Abstract Data Types (ADTs) during the initial stages of their B.Tech course.
- When attempting to solve coding challenges that involve writing test cases using these ADTs, it becomes excessively burdensome to manually create these data structures from scratch.
- Furthermore, while developing programs that implement these ADTs, numerous errors are encountered due to the inability to visualize and understand the underlying processes of these data structures.
Benefits
- Swift installation process
- Efficient and prompt updates
- Minimal disk space usage due to its small size
- No additional modules or dependencies needed
- Developed entirely from scratch
- Upcoming user-friendly documentation
- Command line demonstration for easy usage
Requirements
- Runs on latest Python 3.11+
- (Suggesting you to always update to the latest python version)
Installation
- Use the python package manager pip to install datastax.
pip install datastax
Usage
Demo
-
To get a demo of the library use the following command
- Windows:
> py -m datastax
- Unix based systems:
$ python3 -m datastax
- Result
Available modules are: 1. LinkedLists 2. Trees 3. Arrays Usage > py datastax <data-structure> [data] Data Structures: -> trees Hierarchical DS -> linkedlists Linear DS -> arrays Fixed Size Linear DS
-
Then follow as the instruction guides
> py -m datastax linkedlist 1 2 3 4
Visuals for LinkedLists:
1. Singly Linked List:
HEAD TAIL
┌─────╥────┐ ┌─────╥────┐ ┌─────╥────┐ ┌─────╥────┐
│ 1 ║ ----->│ 2 ║ ----->│ 3 ║ ----->│ 4 ║ -----> NULL
└─────╨────┘ └─────╨────┘ └─────╨────┘ └─────╨────┘
2. Doubly Linked List:
HEAD TAIL
┌────╥─────╥────┐ ┌────╥─────╥────┐ ┌────╥─────╥────┐ ┌────╥─────╥────┐
NULL <----- ║ 1 ║ <-------> ║ 2 ║ <-------> ║ 3 ║ <-------> ║ 4 ║ -----> NULL
└────╨─────╨────┘ └────╨─────╨────┘ └────╨─────╨────┘ └────╨─────╨────┘
...
Practical Usage
- Queue
- BinaryTree
- MinHeapTree
- ThreadedBinaryTree
- SumSegmentTree
- HuffmanTree
- RedBlackTree
What's Next
- Enhanced Documentation
- Better TestCases for Huffman Tree
- Better TestCases for Segment Trees
- Test Cases for Fibonacci Tree
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