Gui Score: Web Application

Description

The purpose of this web application is to provide users with a composite score for the top restaurants in the area, with the user providing their zip code and price range desired (optional).

Service Url: http://www.guiscore.online/

Currently for San Francisco Only

Environment

• OS: Ubuntu 14.04 LTS
• frontend-language: Reactjs v16.0
• backend-language: Python 3.4.3
• web server: nginx/1.4.6
• application server: Flask v0.12.2
• web server gateway: gunicorn (version 19.7.1)
• database: mongod v3.4.9
• module_bunlder: webpack v3.8.1
• react_compiler: babel v1.4.0

Repository Breakdown

Summary of what repository contains:

Item	Decription
README.md	Readme file
package.json	contains requirements and configuration for Reactjs v16 frontend
.babelrc	contains configuration for Babel
web_flask	contain flask application to run mongodb database
src	contains React scripts for for front-end
dist	contains static directory, bundle.js and index.html
backend	contains backend modules in Python 3.4
install_scripts	contains script to install all dependencies and packages

Environment Setup

To setup the proper environment to deploy this application, run the following scripts:

Data Flow

Web Flask Files

search.py - contains all routes for web application:

• /search/<zip_code> -> returns all records with the provied zip code
• /search/<zip_code>/<price> -> returns all records with the provide price range under the provided zip code

Src Files

scripts.js - Reactjs code that pulls from RESTful API created by Flask and displays the content dynamtically.

Dist Files

Static Directory:

• CSS directory with stylesheets
• SCSS directory with scss stylesheets
• img directory with all images
• Js directory with bootstrap css functionality
• Vendor directory with bootstrap style dependencies

Other Files:

• index/html - HTML markup file
• bundle.js - script file that contains the bundle created with webpack

Backend

• database.py - Functionn that takes in what was returned from new_yelp.py and creates a database
• foursquare_remove_trucks.py - Function that calls the FourSquare Api and returns a list of restaurants to pass to match_list.py(currently does not support food trucks with no location)
• match_list.py - Function that takes in both lists from FourSquare and Zomato to find a match, returns a list to pass to new_yelp.py
• new_yelp.py - Function that takes in the matched list, calls the yelp api to create a new composite score
• price_coord_passer.py - Function that takes in the arguments passed by the user (zip code and price) to pass to FourSquare API
• query_listing.py - Function that queries the database based on the user's inputs: Either just a zip code or if they included price
• zomato_name_addr.py - Function that calls the Zomato API and returns a list of restaurants to pass to match_list.py
• zomato_tips.py - Function that calls the Zomato API and grabs the tips provided in regards to the zip code

Install_Scripts

• install_packages.sh - script to install all packages necessary

To use the script, run it like so

./install_packages.sh

Testing

To be added

Notes

This project is for educational purposes only

To-Dos

User Authentication

Known Bugs

There are no known bugs at the time.

Authors

• Kimberly Wong, kjowong | @kjowong | Email
• Spencer Cheng, spencerhcheng | @spencerhcheng | Email

Feedback and contributors welcomed. Reach out to either authors.