[Ballerina] Social Media Service

The sample is based on a simple API written for a social-media site (like twitter) which has users, associated posts and followers. Following is the high level component diagram.

Following is the entity relationship diagram.

Following is the service description.

type SocialMedia service object {
    *http:Service;

    // users resource
    resource function get users() returns User[]|error;
    resource function get users/[int id]() returns User|UserNotFound|error;
    resource function post users(NewUser newUser) returns http:Created|error;
    resource function delete users/[int id]() returns http:NoContent|error;

    // posts resource
    resource function get users/[int id]/posts() returns PostMeta[]|UserNotFound|error;
    resource function post users/[int id]/posts(NewPost newPost) returns http:Created|UserNotFound|PostForbidden|error;
};

Following are the features covered by the scenario.

1. Writing REST APIs with verbs, URLs, data binding and status codes
2. Accessing databases
3. Configurability
4. Data transformation with the data mapper
5. HTTP client
6. Resiliency - Retry
7. Writing tests
8. Using connectors - Slack
9. OpenAPI specification, client stubs and central
10. Adding validations
11. Security - OAuth2
12. Error handlers
13. Ballerina concurrency
14. Integrating a message broker

Setup environment

With Docker Compose

1. Checkout the code base and move to the root folder
2. Execute build-docker-images.sh script to generate the necessary docker images.
3. Execute docker compose up

Note: When trying out feature 11 use port 9098 for the sentiment analysis endpoint.

Without Docker Compose

To complete up to feature 4

1. Setup a MySQL database
2. Execute the script init.sql in db-setup

To complete up to feature 7

1. Move to sentiment-analysis-service and execute bal run to start sentiment analysis service

To complete up to feature 11

1. Move to sts-service and execute bal run to start the Security Token Service (STS) service. The URL of the service is https://localhost:9445/oauth2/token

2. Move to sentiment-analysis-service-secured and execute bal run to start secured sentiment analysis service. Following are the OAuth2 details.

   clientId: FlfJYKBD2c925h4lkycqNZlC2l4a
   clientSecret: PJz0UhTJMrHOo68QQNpvnqAY_3Aa
   scope: admin

Note: When trying out feature 11 use port 9098 for the sentiment analysis endpoint.

To complete up to feature 14

1. Setup a NATS server

Try out

• To start the completed setup run docker compose up -f docker-compose-complete.yml
• To send request open social-media-request.http file using VS Code with REST Client extension