Let's see how that works and how to change it if you need to do that.

## Pydantic Models for Input and Output

Let's say you have a Pydantic model with default values, like this one:

{* ../../docs_src/separate_openapi_schemas/tutorial001_py310.py ln[1:7] hl[7] *}

### Model for Input

            <id>modello-site-doc</id>
            <goals>
              <goal>xdoc</goal>
            </goals>
            <phase>pre-site</phase>
            <configuration>
              <version>1.0.0</version>
              <models>
                <model>src/main/mdo/extension.mdo</model>
              </models>
            </configuration>
          </execution>

    page.get_by_role("button", name="GET /items/ Read Items").click()
    page.get_by_role("button", name="Try it out").click()
    # Manually add the screenshot
    page.screenshot(path="docs/en/docs/img/tutorial/header-param-models/image01.png")

    # ---------------------
    context.close()
    browser.close()


process = subprocess.Popen(
    ["fastapi", "run", "docs_src/header_param_models/tutorial001.py"]
)
try:

    page.get_by_role("button", name="POST /login/ Login").click()
    page.get_by_role("button", name="Try it out").click()
    # Manually add the screenshot
    page.screenshot(path="docs/en/docs/img/tutorial/request-form-models/image01.png")

    # ---------------------
    context.close()
    browser.close()


process = subprocess.Popen(
    ["fastapi", "run", "docs_src/request_form_models/tutorial001.py"]
)
try:

    def _model_rebuild(model: Type[BaseModel]) -> None:
        model.model_rebuild()

    def _model_dump(
        model: BaseModel, mode: Literal["json", "python"] = "json", **kwargs: Any
    ) -> Any:
        return model.model_dump(mode=mode, **kwargs)

    def _get_model_config(model: BaseModel) -> Any:
        return model.model_config

    def get_schema_from_model_field(

)

// TestMain initializes the testing framework
func TestMain(m *testing.M) {
	startLockServers()

	// Initialize locker clients for dsync.
	var clnts []NetLocker
	for i := 0; i < len(nodes); i++ {
		clnts = append(clnts, newClient(nodes[i].URL))
	}

	ds = &Dsync{
		GetLockers: func() ([]NetLocker, string) { return clnts, uuid.New().String() },
		Timeouts: Timeouts{
			Acquire:         testDrwMutexAcquireTimeout,

```Python hl_lines="1  10-13  21-24"
{!../../docs_src/sql_databases/sql_app/models.py!}
```

### 创建关系

现在创建关系。

为此，我们使用SQLAlchemy  ORM提供的`relationship`。

这将或多或少会成为一种“神奇”属性，其中表示该表与其他相关的表中的值。

```Python hl_lines="2  15  26"
{!../../docs_src/sql_databases/sql_app/models.py!}
```

当访问 user 中的属性`items`时，如 中`my_user.items`，它将有一个`Item`SQLAlchemy 模型列表（来自`items`表），这些模型具有指向`users`表中此记录的外键。

## Import `Field`

First, you have to import it:

{* ../../docs_src/body_fields/tutorial001_an_py310.py hl[4] *}


/// warning

Notice that `Field` is imported directly from `pydantic`, not from `fastapi` as are all the rest (`Query`, `Path`, `Body`, etc).

///

## Declare model attributes

@app.get("/items/")
async def read_items(filter_query: Annotated[FilterParams, Query()]):
    return filter_query
```

Read the new docs: [Query Parameter Models](https://fastapi.tiangolo.com/tutorial/query-param-models/).

#### `Header` Parameter Models

Use Pydantic models for `Header` parameters:

```python
from typing import Annotated

from fastapi import FastAPI, Header
from pydantic import BaseModel

 */
package org.apache.maven.model.composition;

import java.util.List;

import org.apache.maven.api.model.DependencyManagement;
import org.apache.maven.api.model.Model;
import org.apache.maven.model.building.ModelBuildingRequest;
import org.apache.maven.model.building.ModelProblemCollector;

/**
 * Handles the import of dependency management from other models into the target model.
 *