The Custom Pokemon Service is a service that creates a customized pokemon based in PokeAPI data with extras attributtes saved in database. This extras attributtes are: nickname, powerLevel and favorite. The pokemon result after this combination is a enriched pokemons wit following structure:
id
name
height
weight
types
nickname
favorite
powerLevelThis service is a Node.js application that provides a GraphQL interface for managing Pokémon information.
Main Features:
- Pokémon List:
- Fetches official data from PokeAPI.
- Returns paginated lists of Pokémon, which can include additional attributes saved in MongoDB.
- Registering and Updating Additional Attributes:
- Allows you to add or update additional information about a Pokémon in MongoDB.
- Respects business rules, such as a maximum of 3 favorite Pokémon and
powerLevelvalues between 1 and 100.
- Node.js (minimum v16)
- GraphQL (Apollo Server or Yoga)
- MongoDB (Mongoose or native driver)
- Jest for testing
- Integration with PokeAPI to retrieve official Pokémon data
To build the solution of this challenge the following architecture was thought:
Below is the diagram representing the organization of custom-pokemon-service following the principles of Clean Architecture:
Execution Flow:
- Client sends queries or mutations to the API.
- The API communicates with the Custom Pokemon Service.
- If the operation is to retrieve data from the PokeApi, access PokeApi and return data.
- If the operation is to save/change/search, access PokemonDB (in MongoDB).
- Always returns an enriched Pokemon to the client.
type Pokemon {
id: ID!
name: String!
height: Int
weight: Int
types: [String!]!
# Atributos extras (MongoDB)
nickname: String
favorite: Boolean
powerLevel: Int
}To build the service's Docker image, run:
docker-compose buildAfter building, start the service with:
docker-compose upThis will start the GraphQL API along with MongoDB (configured in docker-compose.yml).
query {
pokemons(page:4, limit:10) {
id
name
powerLevel
favorite
}
}Send via curl:
curl -X POST http://localhost:4000/ \
-H "Content-Type: application/json" \
-d '{"query":"query { pokemons(page:4, limit:10) { id name powerLevel favorite } }"}'
expect output:
{
"data": {
"pokemons": [
{
"id": "1",
"name": "bulbasaur",
"powerLevel": null,
"favorite": false
},
{
"id": "2",
"name": "ivysaur",
"powerLevel": null,
"favorite": false
},
{...},
{
"id": "12",
"name": "butterfree",
"powerLevel": null,
"favorite": false
},
{
"id": "13",
"name": "weedle",
"powerLevel": null,
"favorite": false
},
{
"id": "14",
"name": "kakuna",
"powerLevel": null,
"favorite": false
},
{
"id": "15",
"name": "beedrill",
"powerLevel": null,
"favorite": false
},
{
"id": "16",
"name": "pidgey",
"powerLevel": null,
"favorite": false
},
{
"id": "17",
"name": "pidgeotto",
"powerLevel": null,
"favorite": false
},
{
"id": "18",
"name": "pidgeot",
"powerLevel": null,
"favorite": false
},
{
"id": "19",
"name": "rattata",
"powerLevel": null,
"favorite": false
},
{
"id": "20",
"name": "raticate",
"powerLevel": null,
"favorite": false
}
]
}
}
mutation{
createPokemonAttributes(input:{
pokemonName: "cascoon"
nickname: "cascaozinho"
favorite: false
powerLevel: 1
}){
id
name
nickname
favorite
powerLevel
}
}Send via curl:
curl -s -X POST http://localhost:4000/ \
-H "Content-Type: application/json" \
-d '{"query":"mutation { createPokemonAttributes(input: { pokemonName: \"cascoon\", nickname: \"cascaozinho\", favorite: false, powerLevel: 1 }) { id name nickname favorite powerLevel } }"}'
expected output
{
"data": {
"createPokemonAttributes": {
"id": "268",
"name": "cascoon",
"nickname": "cascaozao",
"favorite": false,
"powerLevel": 1
}
}
}
Execute the following command to run tests:
docker-compose run --rm app npm testrun : creates a temporary container to run the command.
--rm: automatically removes the container after execution.
app: name of the service defined in docker-compose.yml.
npm test: command that runs the project's tests.
- Fixed failed unit tests
- Increased test coverage
- Added an API gateway so clients don't connect directly to the API
- Added custom logging to have greater control over behavior within the app
- Added caching for frequently performed queries
- Added a resilience strategy (retry, circuit break, timeout) for the PokeApi and MongoDB APIs
- Improved the implementation of layered architectures (clean architecture) by creating more DTOS and factories to avoid maximum coupling