datastax 0.1.0

A python library to handle dataStructures

updated: Wednesday, 29th December 2021

Simplicity meets intelligence

dataStax

What's New?

• Included Priority Queue
• Replaced Bad Implementation of max heap with arrays to true tree implementation
• Added Proper MinHeap DataStructure
• OverFlow and UnderFlow Errors

Table of Contents

• Introduction
• Problem Statement
• Benefits
• Requirements
• Installation
• Usage
• Whats Next

Introduction

• This is a very simple yet powerful project to implement day to day abstract data structures.

• A pure implementation of Python in representing Trees and Linkedlists in basic command prompt

• It helps visualize each data structure for better understanding

• Students can be beneficial in using this Package

• This project is still under construction

Problem Statement

• Often in the beginning CS students face problems in understanding the internal architecture of ADTs
• While solving coding challenges locally where test cases have to be written using these ADTs, it becomes really cumbersome to write these data structures from scratch.
• Often while writing a programs implementing these ADS we encounter lots of errors just because we are unable to preview what's actually going on under the hood.

Benefits

• Instant installation
• Quick Updates
• Very small size
• No extra modules required
• Written purely from scratch
• Easy Documentation [Upcoming]
• Command Line Demo

Requirements

• Runs on latest Python 3.7+
• This Library requires no extra modules

Installation

1. 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:

  $ python -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:
  Node[1] -> Node[2] -> Node[3] -> Node[4] -> NULL

  2. Doubly Linked List:
  NULL <-> Node[1] <-> Node[2] <-> Node[3] <-> Node[4] <-> NULL
  ...

Practical Usage

from datastax.trees import BinaryTree

bt = BinaryTree([1, 2, 3, 4, 5])
print(bt)

## OUTPUT:
"""
            1           
      ┌─────┴─────┐     
      2           3     
   ┌──┴──┐              
   4     5              
"""
---------------------------------------------------
from datastax.trees import MinHeapTree

MiHT = MinHeapTree([1, 2, 4, 2, 6, 5, 9, 18, 3, 2])
print(MiHT)
## OUTPUT
"""
                        1                       
            ┌───────────┴───────────┐           
            2                       4           
      ┌─────┴─────┐           ┌─────┴─────┐     
      2           2           5           9     
   ┌──┴──┐     ┌──┘                             
  18     3     6                                
"""

What's Next

• Implementation of Sum Segment Tree, Expression Tree
• Proper tests using UnitTest Lib
• Enhanced Documentation
• Implementation of Other Abstract data types like LRU_CACHE, LFU_CACHE, SKIP_LIST
• If things go accordingly I am planning to implement threaded binary tree. Seems a completely impossible task to show threads nut I'll try my best
• Beautification of README.md

Upcoming

from datastax.trees import ThreadedBinaryTree as Tbt

tbt = Tbt(['a', 'b', 'c', 'd', 'e'])
"""
Example 3:                    
                                a
                          ┌─────┴─────┐
                          b    │ └────c
                       ┌──┴──┐ │
                       d─┘ └─e─┘
"""