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All things Beer! Beer Educator and Recommender Web App | Deployed on GCP > https://alegorithm-fxljyqhslq-uc.a.run.app/ | UT Data Analysis and Visualization Nov 2019 - May 2020.

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sheetalbongale/ALE-gorithm

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ALE-gorithm - Drink Good Beer

Recommender Web-app & Educational Dashboard for all things beer!🍺

beers gif

Group Members:

+ Barry Haygood - Project manager
+ Sheetal Bongale - Lead Developer
+ Cathy Egboh
+ Maya Saeidi
+ Michelle Brucato
+ Sahar Mohammadi
Project Requirements - Click the drop down! 🔽
  • Proposal

    • Must submit a one page proposal before starting
  • Core App

    • Must use HTML and CSS
    • Must use a database (not Sqlite)
    • Must use Flask
  • Routes

    • Must have at least 5 routes
    • Must have 1 home route that uses a Jinja template
    • Must at least 1 route that uses Plotly or D3 for visualization in a Jinja template
    • Must at least 1 route that access and filter and serves data from the database as a json
    • (May have a route the dynamically filters and displays data to the UI)
    • (May have a route that serves a model, returning result as json)
    • (May have a route that serves a model trough the UI)
  • Testing

    • Must use Postman with at least one request for each route
  • Deployment

    • Must be deployed (exceptions made for ML projects)
    • Must use Pipenv
  • Repo

    • The repo must have properly formatted a README.md
    • Code must be formatted with Black
    • Must have at least 5 GitHub Issues
  • Presentation

    • Prepare a 10-minute presentation
  • Individual

    • Every member must make at least 5 commits that are eventually merged to master
    • Every member must write code that solves at least one meaningful Issue

Role assignment is recommended to accomplish specific tasks and delegate responsibilities! Here are some example roles:

- Project manager: Barry Haygood
- Lead Developer: Sheetal Bongale
- Frontend Developer
- Backend Developer 
- Tester

What is ALE-gorithm?

Have you ever wandered down the beer aisle feeling overwhelmed by options? Do you have a thirst for deliciously brewed craft beer, but don’t know which to choose? Then you’ve come to the right place! The goal of the ALE-gorithm web application & dashboard is to educate consumers on the craft beer space including styles, flavor profiles.

Features

🟡 Beer Recommender: Are you a beer connoisseur? Or even new to the #beerlife experience? No matter what your level of expertise is, if you love to partake in a nice "cold one", then check out the recommender page. We have scanned over a million beers and will match you to the top beers that best suit your palette.

🟡 Dashboard: Want to learn more about your favorite beers? Our interactive dashboard offers information about beers and breweries to both novice and seasoned beer lovers a like.

🟡 Find breweries near you: Looking for a fun beer night or taste some new craft beers? Search to find all the breweries around you or any city around the world!

Technologies used to build ALE-gorithm:

- App Back-End: Python Flask | SQLAlchemy
- Database: MySQL | Google Cloud Platform (GCP) 
- Data Visualization: Javascript | Plotly.js | D3.js | AnyChart.js
- Front-End: HTML | Bootstrap | CSS
- Web-Scraping: Requests, Beautiful Soup
- Testing: Postman

Deployment:

ALE-gorithm is deployed on GCP > Click here!

Data Sources:

Additional Data Resources:

Cheers! 🍻

Copyright

Team Ale-gorithm © 2020 | UT Data Analysis and Visualization Nov 2019 - May 2020