Metadata-Version: 2.1
Name: datastax
Version: 0.4.2
Summary: A python library to handle dataStructures
Home-page: https://github.com/warmachine028/datastax
Download-URL: https://pypi.python.org/pypi/datastax
Author: Pritam K
Author-email: pritamkundu771@gmail.com
Maintainer: Pritam Kundu
License: MIT
Project-URL: Bug Tracker, https://github.com/warmachine028/datastax/issues
Project-URL: Documentation, https://github.com/warmachine028/datastax#readme
Project-URL: Source Code, https://github.com/warmachine028/datastax
Platform: Windows
Platform: Linux
Platform: Solaris
Platform: Mac OS-X
Platform: Unix
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: End Users/Desktop
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.11
Classifier: Topic :: Documentation
Classifier: Topic :: Education :: Testing
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Software Development :: Documentation
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Software Development :: Testing :: Unit
Classifier: Typing :: Typed
Requires-Python: >3.11
Description-Content-Type: text/markdown
License-File: LICENSE

    updated: Thursday, 03rd August 2023

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# [dataStax](https://github.com/warmachine028/datastax)

## What's New?

- Refactored Trees
- Added Nodes SubPackage
- Separated TreeNodes into Nodes
- Added Tables SubPackage
- Added Colors and ColorCodes in Utils
- Refactored Lists
- Removed `__repr__` overrides
- Added Exceptions in Utils
- Added Warnings in Utils
- Added new workflows
- Added datastax.Wiki

## Table of Contents

- [What's New](#whats-new)
- [Introduction](#introduction)
- [Problem Statement](#problem-statement)
- [Benefits](#benefits)
- [Requirements](#requirements)
- [Installation](#installation)
- [Usage](#usage)
- [Documentation](#documentation)
- [License](#license)

## 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

1. Use the python package manager [pip](https://pip.pypa.io/en/stable/) to install datastax.

```bash
pip install datastax
```

## Usage

### Demo

- To get a demo of the library use the following command
    - **Windows**:

  ```bash
  > py -m datastax 
  ```
    - **Unix based systems**:

  ```bash
  $ python3 -m datastax
  ```
    - _Result_
  ```bash
  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

```bash
> 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**

![queue](https://github.com/warmachine028/datastax/assets/75939390/e62ba451-f499-45dc-bcb9-9e29ebfe6dbd)

![queue_output](https://github.com/warmachine028/datastax/assets/75939390/daecb209-d459-4374-96e0-816deb08dcde)

---------------------------------------------------

- **BinaryTree**

![binaryTree](https://github.com/warmachine028/datastax/assets/75939390/7228c4b4-def7-4c6b-9e29-e6e244c2c4c1)

![binaryTree_output](https://github.com/warmachine028/datastax/assets/75939390/2357fa58-3122-47ad-ac7f-f67d72ef6e8c)

---------------------------------------------------

- **MinHeapTree**

![mht](https://github.com/warmachine028/datastax/assets/75939390/1c00a207-9ea0-4965-898f-29e37883fac5)

![mht_output](https://github.com/warmachine028/datastax/assets/75939390/fcfe24d9-6b80-4b16-873c-3f5c3d808d70)

---------------------------------------------------

- **ThreadedBinaryTree**

![tbt](https://github.com/warmachine028/datastax/assets/75939390/ab2f2572-1474-4d82-9138-b8ee85869114)

![tbt_output](https://github.com/warmachine028/datastax/assets/75939390/9e77c5dc-082c-471b-90d5-33792673bdf3)

---------------------------------------------------

- **SumSegmentTree**

![sst](https://github.com/warmachine028/datastax/assets/75939390/7bdcfd6e-37ac-4421-b6d2-acd59cf4976c)

![sst_output](https://github.com/warmachine028/datastax/assets/75939390/3a3f1de2-72e8-4b1d-88c7-40e4dcc11215)

---------------------------------------------------

- **HuffmanTree**

![hft](https://github.com/warmachine028/datastax/assets/75939390/bab7da94-624f-40ac-b746-463157e84cdf)

![hft_output](https://github.com/warmachine028/datastax/assets/75939390/2de13da6-8eaa-4e62-a06a-8dbf91c008a2)

---------------------------------------------------

- **RedBlackTree**

![rbt](https://github.com/warmachine028/datastax/assets/75939390/8d924d6e-d63a-4891-bf9e-c7acdb3775ba)

![rbt_output](https://github.com/warmachine028/datastax/assets/75939390/3af4ceb6-1e68-4906-ba39-db84dbf274f0)

## Documentation

- For detailed documentation. See [documentation](https://github.com/warmachine028/datastax/wiki)
- (Still in progress) 

## License

- see [LICENSE]

**Pritam, 2023**

[license]: https://github.com/warmachine028/datastax/blob/main/LICENSE

<!-- 03/08/23 -->
