graph TB

current_user(["current_user"])
active_user(["active_user"])
admin_user(["admin_user"])
paying_user(["paying_user"])

public["/items/public/"]
private["/items/private/"]
activate_user["/users/{user_id}/activate"]
pro_items["/items/pro/"]

current_user --> active_user
active_user --> admin_user
active_user --> paying_user

current_user --> public
active_user --> private
admin_user --> activate_user

import org.apache.maven.api.model.Profile;
import org.apache.maven.api.services.ModelProblemCollector;

/**
 * Calculates the active profiles among a given collection of profiles.
 *
 */
public interface ProfileSelector {

    /**
     * Determines the profiles which are active in the specified activation context. Active profiles will eventually be
     * injected into the model.
     *

Você pode declarar informação extra em `Field`, `Query`, `Body`, etc. E isso será incluído no JSON Schema gerado.

Você irá aprender mais sobre adicionar informações extras posteriormente nessa documentação, quando estiver aprendendo a declarar exemplos.

## Recapitulando

Você pode usar `Field` do Pydantic para declarar validações extras e metadados para atributos do modelo.

RESOURCE NAME     TYPE           STATUS     VALID CERT     SERIAL NUMBER                        NOT AFTER                NOT BEFORE
default           Cert Chain     ACTIVE     false          6fbee254c22900615cb1f74e3d2f1713     2023-05-16T01:32:52Z     2023-05-15T01:30:52Z

graph TB

current_user(["current_user"])
active_user(["active_user"])
admin_user(["admin_user"])
paying_user(["paying_user"])

public["/items/public/"]
private["/items/private/"]
activate_user["/users/{user_id}/activate"]
pro_items["/items/pro/"]

current_user --> active_user
active_user --> admin_user
active_user --> paying_user

current_user --> public
active_user --> private
admin_user --> activate_user

@app.get("/users/me/", response_model=User)
async def read_users_me(current_user: User = Depends(get_current_active_user)):
    return current_user


@app.get("/users/me/items/")
async def read_own_items(current_user: User = Depends(get_current_active_user)):

@app.get("/users/me/", response_model=User)
async def read_users_me(
    current_user: Annotated[User, Depends(get_current_active_user)],
):
    return current_user


@app.get("/users/me/items/")
async def read_own_items(
    current_user: Annotated[User, Depends(get_current_active_user)],
):

MinIO is a high performance distributed object storage server, designed for large-scale private cloud infrastructure. MinIO is designed in a cloud-native manner to scale sustainably in multi-tenant environments. Orchestration platforms like Kubernetes provide perfect cloud-native environment to deploy and scale MinIO.

## MinIO Deployment on Kubernetes

There are multiple options to deploy MinIO on Kubernetes:

    private Features() {}

    /**
     * Check if the build/consumer POM feature is active.
     */
    public static boolean buildConsumer(@Nullable Properties userProperties) {
        return doGet(userProperties, BUILDCONSUMER, true);
    }

    /**
     * Check if the build/consumer POM feature is active.
     */
    public static boolean buildConsumer(@Nullable Map<String, String> userProperties) {

			AssertObjEqual(t, newUser, user, "ID", "CreatedAt", "UpdatedAt", "DeletedAt", "Name", "Age", "Birthday",
				"CompanyID", "ManagerID", "Active")
		}
	}

	AssertObjEqual(t, user, expect, "ID", "CreatedAt", "UpdatedAt", "DeletedAt", "Name", "Age", "Birthday", "CompanyID",
		"ManagerID", "Active")

	t.Run("Account", func(t *testing.T) {