This is a microservice that allows user to create comments, edit comments and also flags comment. Users can also reply comments, flag reply and also upvote and downvote comments and replies. Also, origin of these comments are tracked.

For quick navigation:

• Getting Started
• Linting Your Code
• Testing Your Code
• Contributing Your Code
• Endpoints Documentation
• Schema Design Explanation

Ensure that your local machine has all the required software, listed below, before setting up your local environment.

• Node

You will first need to setup your local environment and ensure that all configuration files are correctly configured.

1. Fork the repo.
2. Clone your forked repo to you local environment.
3. In your terminal, run npm install.
4. In your terminal, run cp .env.example .env.
5. In your terminal, run npm run startDev.

1. Run npm run lint:fix to fix all fixable errors in source code and format with prettier
2. Run npm run lint to find errors that still remain in your code syntax/format
3. Ensure you fix any remaining linting errors displayed. Run npm run test:ci to ensure your code matches the test

1. Run npm run test to ensure your code passes all tests

Ensure that you lint and test your code before submitting a pull request (PR). For more information on the contributing guidelines and tips on certain implementation details, please see the contributing documentation.

There are two options that you can choose from when you would like to view the endpoints' Swagger documentation.

The first option is online and should be your first go to as this will be the live server with the most trustworthy documentation.

The second option is local and should be used as a last resort when the online option is unavailable.

Visit the online server to see the live Swagger documentation.

After setting up your local environment (see above), please visit the localhost:4000 or the localhost:4000/documentation route to see the local Swagger documentation.

This model contains the following fields

comment_body: string (the body of the comment)
comment_origin: string ( the origin of the comment; Bot or Reports from FE)
isFlagged: boolean( if the comment has been flagged for sensitive words)
upVotes: number
downVotes:  number
user: schema ref ( the details of the person that commented);

This model contains the following fields

reply_body: string (the body of the comment)
comment_id: schema ref ( the id of the comment)
isFlagged: boolean( if the comment has been flagged for sensitive words)
upVotes: number
downVotes:  number

This model contains the following fields

name: string (name of the person comment)
email: string (email address of the person commenting)

MIT License

Copyright (c) 2020, Team Justice League. All rights reserved.