import org.apache.maven.api.plugin.descriptor.lifecycle.LifecycleConfiguration;
import org.apache.maven.artifact.Artifact;
import org.apache.maven.artifact.ArtifactUtils;
import org.apache.maven.model.Plugin;
import org.apache.maven.plugin.lifecycle.io.LifecycleStaxReader;
import org.codehaus.plexus.classworlds.realm.ClassRealm;
import org.codehaus.plexus.component.repository.ComponentDescriptor;

 */
package org.apache.maven.plugin;

import java.io.File;
import java.nio.file.Path;
import java.util.Properties;

import org.apache.maven.execution.MavenSession;
import org.apache.maven.impl.model.reflection.ReflectionValueExtractor;
import org.apache.maven.plugin.descriptor.MojoDescriptor;
import org.apache.maven.plugin.descriptor.PluginDescriptor;
import org.apache.maven.project.MavenProject;

/// tip | Совет

Класс `Config` используется только для конфигурации Pydantic. Подробнее см. <a href="https://docs.pydantic.dev/1.10/usage/model_config/" class="external-link" target="_blank">Pydantic Model Config</a>.

///

////

/// info | Информация

///

/// tip | İpucu

Merak ediyorsanız söyleyeyim, "AlexNet", "ResNet" ve "LeNet" isimleri Makine Öğrenmesi <abbr title="Teknik olarak, Derin Öğrenme model mimarileri">modellerini</abbr> temsil eder.

///

### Bir *Yol Parametresi* Tanımlayalım

Sonrasında, yarattığımız enum sınıfını (`ModelName`) kullanarak tip belirteci aracılığıyla bir *yol parametresi* oluşturalım:

def get_app_client(separate_input_output_schemas: bool = True) -> TestClient:
    app = FastAPI(separate_input_output_schemas=separate_input_output_schemas)

    @app.post("/items/", responses={402: {"model": Item}})
    def create_item(item: Item) -> Item:
        return item

    @app.post("/items-list/")
    def create_item_list(item: list[Item]):
        return item

    @app.get("/items/")

from collections.abc import Sequence
from dataclasses import dataclass
from enum import Enum
from typing import Annotated, Any, Callable, Optional, Union

from fastapi.exceptions import FastAPIDeprecationWarning
from fastapi.openapi.models import Example
from pydantic import AliasChoices, AliasPath
from pydantic.fields import FieldInfo
from typing_extensions import Literal, deprecated

from ._compat import (
    Undefined,
)

### Memory per Process { #memory-per-process }

Now, when the program loads things in memory, for example, a machine learning model in a variable, or the contents of a large file in a variable, all that **consumes a bit of the memory (RAM)** of the server.

    full_name = user_dict["full_name"],
    disabled = user_dict["disabled"],
    hashed_password = user_dict["hashed_password"],
)
```

/// info | 说明

`user_dict` 的说明，详见[**更多模型**一章](../extra-models.md#user_indict){.internal-link target=_blank}。

///

## 返回 Token

`token` 端点的响应必须是 JSON 对象。

响应返回的内容应该包含 `token_type`。本例中用的是**Bearer**Token，因此， Token 类型应为**`bearer`**。

/// tip

Pydantic 是 FastAPI 中所有数据验证和序列化的核心，当你在没有设默认值的情况下使用 `Optional` 或 `Union[Something, None]` 时，它具有特殊行为，你可以在 Pydantic 文档中阅读有关<a href="https://docs.pydantic.dev/latest/concepts/models/#required-optional-fields" class="external-link" target="_blank">必需可选字段</a>的更多信息。

///

## 查询参数列表 / 多个值

当你使用 `Query` 显式地定义查询参数时，你还可以声明它去接收一组值，或换句话来说，接收多个值。

例如，要声明一个可在 URL 中出现多次的查询参数 `q`，你可以这样写：

 * KIND, either express or implied.  See the License for the
 * specific language governing permissions and limitations
 * under the License.
 */
package org.apache.maven.model.interpolation.reflection;

import java.lang.reflect.Method;
import java.util.ArrayList;
import java.util.Hashtable;
import java.util.Iterator;
import java.util.LinkedList;
import java.util.List;