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 {

Incluindo bibliotecas externas também baseadas no Pydantic, como <abbr title="Object-Relational Mapper">ORM</abbr>s e <abbr title="Object-Document Mapper">ODM</abbr>s para bancos de dados.

         */
        protected int pageNumber;
        /**
         * The total number of records found.
         */
        protected long recordCount;
        /**
         * The relation of the record count (e.g., "eq" for exact, "gte" for greater than or equal to).
         */
        protected String recordCountRelation;
        /**
         * The total number of pages in the search results.

/// tip | Dica

Você pode usar qualquer outra biblioteca de banco de dados SQL ou NoSQL que quiser (em alguns casos chamadas de <abbr title="Object Relational Mapper, um termo sofisticado para uma biblioteca onde algumas classes representam tabelas SQL e instâncias representam linhas nessas tabelas">"ORMs"</abbr>), o FastAPI não obriga você a usar nada. 😎

///

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...

Bao gồm các thư viện bên ngoài cũng dựa trên Pydantic, như <abbr title="Object-Relational Mapper">ORM</abbr>s, <abbr title="Object-Document Mapper">ODM</abbr>s cho cơ sở dữ liệu.

import java.util.Set;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.atomic.AtomicInteger;
import junit.framework.TestCase;
import org.jspecify.annotations.NullUnmarked;

/**
 * Tests relating to cache expiration: make sure entries expire at the right times, make sure
 * expired entries don't show up, etc.
 *
 * @author mike nonemacher
 */
@SuppressWarnings("deprecation") // tests of deprecated method

## 0.30.0

* Add support for Pydantic's ORM mode:
    * Updated documentation about SQL with SQLAlchemy, using Pydantic models with ORM mode, SQLAlchemy models with relations, separation of files, simplification of code and other changes. New docs: [SQL (Relational) Databases](https://fastapi.tiangolo.com/tutorial/sql-databases/).

**FastAPI**는 <a href="https://docs.pydantic.dev/" class="external-link" target="_blank"><strong>Pydantic</strong></a>을 기반으로 하며 Pydantic과 완벽하게 호환됩니다. 그래서 어느 추가적인 Pydantic 코드를 여러분이 가지고 있든 작동할 것입니다.

Pydantic을 기반으로 하는, 데이터베이스를 위한 <abbr title="Object-Relational Mapper">ORM</abbr>, <abbr title="Object-Document Mapper">ODM</abbr>을 포함한 외부 라이브러리를 포함합니다.

이는 모든 것이 자동으로 검증되기 때문에, 많은 경우에서 요청을 통해 얻은 동일한 객체를, **직접 데이터베이스로** 넘겨줄 수 있습니다.

/// tip | Подсказка

Вы можете воспользоваться любой библиотекой для работы с реляционными (SQL) или нереляционными (NoSQL) базами данных. (Их ещё называют <abbr title="ORM = Object Relational Mapper, этот термин для библиотеки, в которой классы представляют SQL-таблицы, а экземпляры классов представляют строки в этих таблицах.">**ORM**</abbr> библиотеками). FastAPI не принуждает вас к использованию чего-либо конкретного. 😎