Flatiron Data Science Capstone Project. Enter your favorite cigar and my application will return 10 similar cigars. My app is a website, no need to download anything. The application uses an algorithm that has over 100 features and 1600 cigars that I scraped from the web. For example, there are over 20 different types of wrappers, many more combinations of filler, ratings, keywords, etc. The programming language I used is Python and the model is K Nearest Neighbors with a weighted Minkowski metric. You can also search by profile notes and it will return matches, for example, strong, leather, chocolate, spice, etc. I used Streamlit to build the app and Heroku to host it. I like to think of my app as the Craigslist of cigars due to its minimalist design. The simple design and my stretch goal of matching cigars to spirits and beers makes my app different from other cigar recommenders. This will be an affiliate website.