Great places are chosen by great chowists 😎

Scrape and display Tyler Cowen's current favorite restaurants

A project in the agricultural sector that checks the protein consumption of consumers like meat in a particular abattoir by issuing certificates which has the details of the slaughtered animal. In turn consumers can scan the certificate at every restaurant or outlet to verify the authenticity of the protein food.

Applying machine learning techniques to Yelp and Los Angeles City health violations data to restaurants.

Unofficial Python SDK written for Zomato API

Georgia Health Scores is a Python script designed for scraping latest restaurant health inspection data for the state of Georgia. This project was solely created for practicing asyncio in Python.

[Deprecated] Tripadvisor restaurant web scraper

A Python wrapper around IFood API.

A multipurpose Discord Bot coded in Python using the discord.py library that performs multiple advanced functions from providing weather reports to fetching restaurant information based on their location.

Restaurant suggestion project for opening a new restaurant

FastTrack Sales Forecaster leverages ARIMA models for advanced time series analysis in fast food sales. It efficiently predicts future trends from historical data, aiding in strategic planning and market analysis. This tool is essential for data-driven decision-making in the fast food industry.

Restaurant order management system built with Python, PyQt6, and SQLite.

Data Scraper for Downtown Lawrence

This is a simple program that you give an address and a location and it gives you an html map of surrounding restaurants based on a list of cuisines you can edit in the Restaurant_Mapper file. All you need is a Google API key with Geolocating and Places enabled.

a US taco restaurant finding Flask app

At the intersection of delivery and in-house dining, Weat makes preparing restaurant-quality food quick, easy, and fun.

🏙️ OpenStreetMap import tool for restaurants from um.warszawa.pl

A basic F&B sales dashboard using Python, Dash, Docker, and deployed on Render or AWS. Includes a Python module to generate simulated data for testing. Uses parquet files and can run on top of a relational database.

Gathering monthly must-try restaurants from websites such as Eater and The Infatuation before compiling them into a dataset and automatically sending them to users via email.