Roamr

Roamr is a social media application that allows users to share their travel experiences by posting their location and an image. Users can explore posts from around the world on an interactive globe.

Features

• Login/Signup: Users can sign up for an account and then use the same account to log in.
• Search for users: Users can search for other users on the platform using their username.
• Post Creation: Users can create posts by providing a city, country, description, and an image.
• Post Deletion: Users can delete any of their posts.
• Followers: Users can follow others on the platform.
• Interactive Globe: Users can view posts on a 3D interactive globe and explore locations based on who they follow.

Getting Started

Prerequisites

Make sure you have Docker installed and running.

Installation

1. Clone the repository:

   git clone https://github.com/danielyedaniel/Roamr.git
   cd Roamr

2. Run the application:

   • Build and start the Docker containers:

     docker-compose up

Usage

1. Open your web browser and go to localhost:3000.
2. Sign up or log in to your account.
3. Search for other users on the platform.
4. Create a new post by clicking the "New Post" button.
5. Fill in the country, city, description, and upload an image.
6. Click "Post" to share your experience.
7. Search for other users and follow them.
8. Explore the globe to see posts from other users you follow.

How It's Built

• Frontend: The frontend is developed with ReactJS. We use a third-party library for the interactive 3D globe.
• Backend: The backend is built with Go and serves to handle API requests from our frontend. It also uses GORM to interact with our database.
• Database: PostgreSQL is used as the database.
• Dockerized: The application is containerized using Docker. Running docker-compose up will start both the frontend and backend services and a local PostgreSQL database.

Database

Most SQL scripts are located within the sql_scripts directory. The create_tables.sql script is responsible for creating the necessary tables. The init.sql script populates all the tables with initial sample data. When you run docker-compose up, the database is set up and populated with the sample/production data (more on this later), so no extra work is needed to set it up. The command mounts the sql_scripts directory, a volume inside the PostgreSQL container, automatically running the init.sql script. The init.sql script calls create_tables.sql to create the tables and then populates them with data from the data directory.

Switching Between DBs: To switch between the sample and production databases, open docker-compose.yml in the root directory. Then go to line 40 and read the comment on switching between datasets. It loads different data into the DB on startup based on which init is called. Make sure to delete any volumes created to ensure the DB doesn't skip creating a new volume. The production DB is around 5x the size of the sample DB. The init_production.sql script is also found in the sql_scripts directory.

Sample DB Scripts

Additionally, there are five other query scripts that we have run over our sample DB and that we may use; they are in the sql_scripts directory:

• check_username_or_email.sql: This SQL file checks if a username or email has already been taken. It returns all users that use the username or email.
• find_following.sql: This SQL file finds all the users that a certain userID is following. It returns all users that this user follows.
• find_posts_from_following.sql: This SQL file finds all the posts from all the users they are following given a userID. It returns all posts that should show up in their feed.
• login.sql: This SQL file checks if a username and hashed password match a user within the DB. It returns all users that match the username and password.
• search_users.sql: This SQL file returns all users that begin with a certain string. It returns all users that have the string prefix.

The outputs of these queries are stored in the sql_out directory. Each output file has the same name as the corresponding SQL script but with a .out extension.

Production DB Scripts

There are also scripts we have run on the production DB in the production_sql_scripts directory:

• check_username_or_email.sql: This SQL file checks if a username or email has already been taken.

• create_comment.sql: This SQL file inserts a new comment into the database.

• create_location.sql: This SQL file inserts a new location into the database.

• create_post.sql: This SQL file inserts a new post into the database.

• create_rating.sql: This SQL file inserts a new rating into the database.

• delete_comment.sql: This SQL file deletes a comment from the database.

• delete_followers_unfollow_user.sql: This SQL file deletes the relationship of a user following another user. AKA unfollows a user.

• delete_post.sql: This SQL file deletes a post from the database.

• delete_rating.sql: This SQL file deletes a rating from the database.

• find_following.sql: This SQL file finds all the users that a certain userID is following. It returns all users that this user follows.

• find_posts_from_following.sql: This SQL file finds all the posts from all the users they are following given a userID. It returns all posts that should show up in their feed.

• follow_another_user.sql: This SQL file inserts a new follower relationship into the database.

• get_all_locations.sql: This SQL file retrieves all locations from the database. It returns all location records.

• get_comments_for_post.sql: This SQL file retrieves all comments for a given postID. It returns all comments associated with the specified post.

• location_id_by_city_and_country.sql: This SQL file retrieves the locationID for a given city and country. It returns the locationID that matches the specified city and country.

• login.sql: This SQL file checks if a username and hashed password match a user within the DB. It returns all users that match the username and password.

• most_rated_locations.sql: This SQL file retrieves the locations with the most number of ratings. It returns the most rated 25 locations.

• search_users.sql: This SQL file returns all users that begin with a certain string.

The outputs of these queries are stored in the production_sql_out directory. Each output file has the same name as the corresponding SQL script but with a .out extension.