</a>
                                <c:forEach var="item" varStatus="s" items="${pathItems}">
                                    / <span><a
                                        href="${contextPath}/admin/storage/list/${f:u(item.id)}/">${f:h(item.name)}</a></span>
                                </c:forEach>

                            "description": "Successful Response",
                            "content": {"application/json": {"schema": {}}},
                        }
                    },
                    "summary": "Read Item",
                    "operationId": "read_item_items__get",
                }
            }
        },

{* ../../docs_src/query_params_str_validations/tutorial008.py hl[13] *}

## 别名参数

假设你想要查询参数为 `item-query`。

像下面这样：

```
http://127.0.0.1:8000/items/?item-query=foobaritems
```

但是 `item-query` 不是一个有效的 Python 变量名称。

最接近的有效名称是 `item_query`。

但是你仍然要求它在 URL 中必须是 `item-query`...

这时你可以用 `alias` 参数声明一个别名，该别名将用于在 URL 中查找查询参数值：

                        <ol class="breadcrumb float-sm-right">
                            <li class="breadcrumb-item active"><la:link href="/admin/badword">
                                <la:message key="labels.bad_word_link_list"/>
                            </la:link></li>
                            <li class="breadcrumb-item active"><la:message
                                    key="labels.bad_word_link_upload"/></li>

///

`response_model` receives the same type you would declare for a Pydantic model field, so, it can be a Pydantic model, but it can also be, e.g. a `list` of Pydantic models, like `List[Item]`.

FastAPI will use this `response_model` to do all the data documentation, validation, etc. and also to **convert and filter the output data** to its type declaration.

/// tip

///

`response_model` recebe o mesmo tipo que você declararia para um campo de modelo Pydantic, então, pode ser um modelo Pydantic, mas também pode ser, por exemplo, uma `list` de modelos Pydantic, como `List[Item]`.

O FastAPI usará este `response_model` para fazer toda a documentação de dados, validação, etc. e também para **converter e filtrar os dados de saída** para sua declaração de tipo.

/// tip | Dica

                            <li class="breadcrumb-item"><la:link href="/admin/searchlog">
                                <la:message key="labels.searchlog_configuration_link_top"/>
                            </la:link></li>
                            <c:if test="${crudMode == 4}">
                                <li class="breadcrumb-item active"><la:message

     * chains a collection of {@link WorkspaceReader}s
     * @param workspaceReaderCollection the collection of readers, might be empty but never <code>null</code>
     * @return if the collection contains only one item returns the single item, otherwise creates a new
     *         {@link MavenChainedWorkspaceReader} chaining all readers in the order of the given collection.
     */

3. Die Datenklasse `Author` enthält eine Liste von `Item`-Datenklassen.

4. Die Datenklasse `Author` wird im `response_model`-Parameter verwendet.

5. Sie können andere Standard-Typannotationen mit Datenklassen als Requestbody verwenden.

    In diesem Fall handelt es sich um eine Liste von `Item`-Datenklassen.

2. `pydantic.dataclasses` is a drop-in replacement for `dataclasses`.

3. The `Author` dataclass includes a list of `Item` dataclasses.

4. The `Author` dataclass is used as the `response_model` parameter.

5. You can use other standard type annotations with dataclasses as the request body.

    In this case, it's a list of `Item` dataclasses.

6. Here we are returning a dictionary that contains `items` which is a list of dataclasses.