Restaurant Rater

This project is a clone of the popular business directory service and crowd-sourced review forum, Yelp. It is built using the PERN stack which includes PostgreSQL, Express, React, and Node.js.
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Features

• CRUD Operations: Implement full CRUD operations for managing restaurant data and reviews.
• Search Functionality: Search for restaurants based on various criteria.
• Rating System: Users can rate restaurants using a star rating system, and view average ratings.
• Review System: Users can write reviews for restaurants and view reviews from other users.
• Responsive Design: The web application is designed to be responsive for a variety of devices and screen sizes.
• RESTful API: Utilize RESTful API conventions for server routing to handle client requests and manage database operations.
• Data Visualization: Visual representation of restaurant ratings and other relevant data.
• Error Handling: Implement error handling to provide feedback on failed operations like incorrect data entry.

Technologies Used

• Backend: Express, Node.js
• Database: PostgreSQL
• Frontend: React
• State Management: React Context API
• Routing: React Router

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Video Walkthrough

Here's a walkthrough of implemented required features:

GIF created with GIPHY Capture for macOS

Getting Started

1. Clone the repository:

   git clone https://github.com/josegonz115/restaurant-rater.git
   cd pern-yelp-clone

2. Install dependencies:

   Make sure to cd to both directories client/ and server/ and enter

   npm install

3. Setup the database:

   • Install PostgreSQL and create a database
   • Create a database for the project.
   • Setup the necessary tables using the provided schema file in the database folder.

4. Configure environment variables:

   • In server/ create an .env file with your PostgreSQL connection information.

   PORT=0000
   
   PGUSER=name
   PGHOST=postgres
   PGPASSWORD=password
   PGDATABASE=database_name
   PGPORT=5432

5. Start the server:

   In server/ and then client\

   npm start

6. Visit the application:

   • Open your web browser and visit http://localhost:3000.

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