feat: merge branch 'main' into user-refactor

- **Administrator Control**: Only administrators have the authority to create, update, or remove movies from the catalogue, ensuring that the database is well-maintained and up-to-date.

## Technologies Used

- Docker

- Spring Boot

- PostgreSQL

- MapStruct

- Grafana

- Prometheus

## Team Members

- Lukas Chudicek (team lead)

- Daniel Nemec

- Mario Straus

- Ecenur Sezer

## Modules

The information about each specific module can be found in the README.md file of each module.

- note that you might need to clear the old images (if any present)

To observe the metrics of the system after the docker containers are up, please visit [Grafana UI](<localhost:3000>) with default credentials _admin:admin_.

To observe the metrics of the system after the docker containers are up, please visit [Grafana UI](https://localhost:3000) with default credentials _admin:admin_.

![Main dashboard](image.png)

A [screenshot](documentation/grafana-dashboard.png) of grafana board is also provided in documentation.

# client

# Client Project

This project is here just to get the user token

This project provides the token to access the endpoints.

## Running

u know

Execute the following command to run the project.

```shell

mvn clean install -DskipTests && mvn spring-boot:run

- go to <http://localhost:8080>

- login with `muni`

- -> `yes continue` button

- at this point there should be a bunch of uninteresting mess in the console

- click the `go to my calendar interface` button

- even though the backend is not running, the token is dumped into the console

- it is what it is

- even though the backend is not running, the token is available at the console.

## Using the token

- i recommend

```shell

export TOKEN=the_token

```

version: '3.8'

services:

  #  movie_recommender_db:

  #    image: postgres:16.2

  #    container_name: movie-recommender-postgres

  #    environment:

  #      POSTGRES_USER: ${MOVIE_RECOMMENDER_POSTGRES_USER}

  #      POSTGRES_PASSWORD: ${MOVIE_RECOMMENDER_POSTGRES_PASSWORD}

  #      POSTGRES_DB: ${MOVIE_RECOMMENDER_POSTGRES_DB}

  #    ports:

  #      - "${MOVIE_RECOMMENDER_POSTGRES_PORT}:5432"

  #    volumes:

  #      - movie-recommender-postgres-data:/var/lib/postgresql/data

  prometheus:

    image: prom/prometheus:v2.43.0

    volumes:

      - movie-recommender-service

  grafana:

    image: grafana/grafana

    image: grafana/grafana:8.5.5

    volumes:

      - ./grafana/dashboards:/var/lib/grafana/dashboards

      - ./grafana/provisioning/dashboards.yml:/etc/grafana/provisioning/dashboards/dashboards.yml

  user-service:

    build:

      context: ./user-microservice # Assumes Dockerfile is in the same directory as docker-compose.yml

      dockerfile: Dockerfile # Name of the Dockerfile

      context: ./user-microservice

      dockerfile: Dockerfile

    container_name: user-microservice

    ports:

      - "${USER_PORT}:${USER_PORT}"

  movie-service:

    build:

      context: ./movie-microservice # Assumes Dockerfile is in the same directory as docker-compose.yml

      dockerfile: Dockerfile # Name of the Dockerfile

      context: ./movie-microservice

      dockerfile: Dockerfile

    container_name: movie-microservice

    ports:

      - "${MOVIE_PORT}:${MOVIE_PORT}"

  rating-service:

    build:

      context: ./rating-microservice # Assumes Dockerfile is in the same directory as docker-compose.yml

      dockerfile: Dockerfile # Name of the Dockerfile

      context: ./rating-microservice

      dockerfile: Dockerfile

    container_name: rating-microservice

    ports:

      - "${RATING_PORT}:${RATING_PORT}"

  movie-recommender-service:

    build:

      context: ./movie-recommender-microservice # Assumes Dockerfile is in the same directory as docker-compose.yml

      dockerfile: Dockerfile # Name of the Dockerfile

      context: ./movie-recommender-microservice

      dockerfile: Dockerfile

    container_name: movie-recommender-microservice

    ports:

      - "${MOVIE_RECOMMENDER_PORT}:${MOVIE_RECOMMENDER_PORT}"

    depends_on:

      - movie-service

      - rating-service

    environment:

      MOVIE_RECOMMENDER_PORT: ${MOVIE_RECOMMENDER_PORT}

      MOVIE_PORT: ${MOVIE_PORT}

      RATING_PORT: ${RATING_PORT}

volumes:

  #  movie-recommender-postgres-data: # no db -> no volume

  movie-microservice-postgres-data:

  rating-microservice-postgres-data:

  user-microservice-postgres-data:

docker compose up --build 

```

The service will be accessible at localhost:8001/api/v1/movies

The movie microservice endpoints work in [localhost:8001/api/v1/movies](http://localhost:8001/api/v1/movies).

## Movie API endpoints

## Seeding and clearing

To seed the database with some initial data, you can make the following POST request:

To seed the database with some initial data, you can use the following command while running the app:

```bash

curl -X POST http://localhost:8001/api/v1/movies/production/seed

docker cp ./sql/seed_movie_database.sql movie-postgres:/ && \

docker exec -it movie-postgres psql -U movie_user -d movie_database -p 5431 -a -f ./seed_movie_database.sql

```

To clear the whole database, you can make the following POST request:

To clear the whole database, you can use the following script:

```bash

curl -X POST http://localhost:8001/api/v1/movies/production/clear

docker cp ./sql/clear_movie_database.sql movie-postgres:/ && \

docker exec -it movie-postgres psql -U movie_user -d movie_database -p 5431 -a -f ./clear_movie_database.sql

```

For windows use `;` instead of `&&` in the above commands.

## Validation and Error handling

## Testing 

You can use swagger with url /api/v1/movies/swagger-ui/index.html to test the endpoints.

You can use swagger with url <http://localhost:8001/api/v1/swagger-ui/index.html#/> to test the endpoints.

- (your host, port may be different depending on your env)