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rish-0-0/README.md

Hey! Rishabh here πŸ‘‹

Software developer from Bangalore. Graduated with Computer Science '21 from BITS Pilani, Goa. Believe in the power of education and a big fan of opensource development.

My NPM Packages

Neo-Flow-Viz

It is a Neo4j Graph visualization Library for React Projects, written in Typescript. It uses ReactFlow as the underlying Graph Library and the response and Query Format it builds on is for Neo4j.

npm install --save neo-flow-viz

Astroreha

Astrological Calculations and Chart Generating Library. Got 10 ⭐s

npm install --save astroreha
  • πŸ”­ I'm currently learning ThreeJS. Some 3d animation has struck my interest.
  • βš™οΈ I have 4y of Software Development Experience working in a ☁️ Cloud / Data / Privacy Security.
  • πŸ”₯ My major strength would be the ability to learn very quickly.
  • 🌱 I’m currently learning elixir, golang, rust and webassembly.
  • πŸ‘― I'm a big fastify fan. Shotout @mcollina. I have written a fastify CRUD generator. Currently privated.
  • πŸ’¬ Ask me about anything react. It's my favourite choice for developing websites.
  • πŸ“« How to reach me: rishabhanand42@gmail.com
  • ⚑ Fun fact: GraphQL has nothing to do with Graph Databases πŸ˜‚
  • 😠 I like redux, but would do anything to get around it πŸ˜‚

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  1. neo-flow-viz Public

    React Flow based Neo4j Graph Vizualization Library written in TypeScript

    TypeScript

  2. astroreha Public

    Astrology npm package for Reha (a Dating App based on Astrology). Can calculate Birth Chart, D9 Chart and provide compatibility info.

    JavaScript 10 10

  3. astrocharts Public

    React Native App (Android and iOS) to get your Birth Chart and Navamsa Chart along with the nakshatras

    JavaScript 1 1

  4. express-graphql-subscriptions Public

    Express graphql and subscriptions template with docker for realtime graphql

    JavaScript

  5. planets Public

    Testing out newtonian and other models of gravity using ThreeJS

    TypeScript

  6. For streaming your android phone's p...
    1
    # conda create -n env python=3.6
    2
    # pip install opencv-python # this is important because you need ffmpeg enabled
    3
    
                  
    4
    import cv2
    5
    import numpy as np