Swiggy Clone Using React.js.

It was a Round 2 assignment given by the Swiggy Hiring Team for the ASDE role, designed to evaluate your LLD, code scalability, modularity, and maintainability of the code.

"MUNCH: A pioneering web app tailored for college students, MUNCH redefines campus dining. Seamlessly order delicious meals from your hostel, customize your preferences, and enjoy hassle-free transactions. Real-time tracking, dietary accommodations, and record maintenance ensure a delightful experience. Explore the future of food convenience!"

The script scrapes restaurant information from the Swiggy website. Users can customize location parameters, and the script retrieves details such as restaurant ID, name, ratings, and cost for two. The collected data is stored in a CSV file for further analysis.

Just a UI clone of Swiggy Landing page

Portfolio Project: Swiggy Clone Mock SQL Database - Case Study

In this project we will dive deep into UICompositional Layouts and alot of new concepts.

Data Science Project

Simple library to enable anyone who manages a restaurant on Swiggy to listen into order updates and run custom code or logic in Python

Performed product dissection on the Swiggy Food Delivery App, designing the schema and establishing relationships between entities. I also used MySQL to create the database and tables, transforming my conceptual model into a practical ERD.

Analyse your swiggy orders 🍔

Analyzing Swiggy's restaurant data in Bangalore to provide management with valuable insights for informed decision-making.

Welcome to Foodie, a robust food delivery platform developed with React.js, Tailwind CSS, and various other technologies. Foodie offers a seamless food ordering experience, with access to thousands of restaurants, real-time weather information, and precise geolocation features

A clone of online food ordering site swiggy.

In this project, we conducted an analysis of Bangalore restaurant cuisines using data collected from Swiggy, a popular food delivery platform. We utilized Python and MS Excel to gather, organize, and analyze the data.

the 'Swiggy Restaurant Recommendation Model,' simplifies decision-making by using data science and machine learning. It offers personalized restaurant suggestions to users based on their cuisine and location preferences. The process involves data scraping, cleaning, machine learning, and the creation of an interactive web app for an enhanced dining

this project is food scraper of different restaurant in swiggy website

Fetch, analyze and visualize your Swiggy order history!

Online Food Ordering App built using Html, CSS and Pure JS without any framework.

A Swiggy-like video streaming app using React, Redux & Tailwind CSS.