``` hl_lines="5"
.
├── app
│   ├── __init__.py
│   ├── main.py
│   └── test_main.py
```

Como esse arquivo está no mesmo pacote, você pode usar importações relativas para importar o objeto `app` do módulo `main` (`main.py`):

{* ../../docs_src/app_testing/app_a_py39/test_main.py hl[3] *}

...e ter o código para os testes como antes.

# Bases de Datos SQL (Relacionales) { #sql-relational-databases }

**FastAPI** no requiere que uses una base de datos SQL (relacional). Pero puedes utilizar **cualquier base de datos** que desees.

Aquí veremos un ejemplo usando <a href="https://sqlmodel.tiangolo.com/" class="external-link" target="_blank">SQLModel</a>.

            }

            if (!visited.add(a.getGroupId() + ':' + a.getArtifactId() + ':' + a.getBaseVersion())) {
                RepositoryException exception =
                        new RepositoryException("Artifact relocations form a cycle: " + visited);
                invalidDescriptor(session, trace, a, exception);
                if ((getPolicy(session, a, request) & ArtifactDescriptorPolicy.IGNORE_INVALID) != 0) {
                    return null;

Inklusive externer Bibliotheken, die auf Pydantic basieren, wie <abbr title="Object-Relational Mapper – Objektrelationaler Abbilder">ORM</abbr>s, <abbr title="Object-Document Mapper – Objekt-Dokument-Abbilder">ODM</abbr>s für Datenbanken.

Bunlara Pydantic üzerine kurulu <abbr title="Object-Relational Mapper">ORM</abbr> databaseler ve , <abbr title="Object-Document Mapper">ODM</abbr> kütüphaneler de dahil olmak üzere.

versioning is designed to keep multiple versions of an object in one bucket. For example, you could store `spark.csv` (version `ede336f2`) and `spark.csv` (version `fae684da`) in a single bucket. Versioning protects you from unintended overwrites, deletions, protect objects with retention policies.

To control data retention and storage usage, use object versioning with [object lifecycle management](https://github.com/minio/minio/blob/master/docs/bucket/lifecycle/README.md).  If you have an object...

 * a traditional {@code HashMap} implementation which stores keys and count values as map entries,
 * {@code ObjectCountHashMap} minimizes object allocation and reduces memory footprint.
 *
 * <p>In the absence of element deletions, this will iterate over elements in insertion order.
 */
@GwtCompatible
@NullMarked
class ObjectCountHashMap<K extends @Nullable Object> {

  /** Creates an empty {@code ObjectCountHashMap} instance. */

Inclus des librairies externes basées, aussi, sur Pydantic, servent d'<abbr title="Object-Relational Mapper">ORM</abbr>s, <abbr title="Object-Document Mapper">ODM</abbr>s pour les bases de données.

Включая внешние библиотеки, также основанные на Pydantic, такие как <abbr title="Object-Relational Mapper">ORM</abbr>’ы, <abbr title="Object-Document Mapper">ODM</abbr>’ы для баз данных.

import com.google.common.cache.TestingRemovalListeners.CountingRemovalListener;
import java.util.List;
import java.util.Set;
import junit.framework.TestCase;
import org.jspecify.annotations.NullUnmarked;

/**
 * Tests relating to cache eviction: what does and doesn't count toward maximumSize, what happens
 * when maximumSize is reached, etc.
 *
 * @author mike nonemacher
 */
@NullUnmarked
public class CacheEvictionTest extends TestCase {