"$ref": "#/components/schemas/Body_login_login__post"
                                }
                            }
                        },
                        "required": True,
                    },
                }
            }
        },
        "components": {
            "schemas": {
                "Body_login_login__post": {

    **FastAPI** 对此没有任何限制，可以**随意**互换使用这两种操作。

    但本指南也会分别介绍这两种操作各自的用途。

### 使用 Pydantic 的 `exclude_unset` 参数

更新部分数据时，可以在 Pydantic 模型的 `.dict()` 中使用 `exclude_unset` 参数。

比如，`item.dict(exclude_unset=True)`。

这段代码生成的 `dict` 只包含创建 `item` 模型时显式设置的数据，而不包括默认值。

然后再用它生成一个只含已设置（在请求中所发送）数据，且省略了默认值的 `dict`：

```Python hl_lines="34"
{!../../../docs_src/body_updates/tutorial002.py!}
```

### 使用 Pydantic 的 `update` 参数

                                }
                            }
                        },
                        "required": True,
                    },
                }
            },
            "/users/me/": {
                "get": {
                    "responses": {
                        "200": {

                            "application/json": {
                                "schema": {"$ref": "#/components/schemas/Item"}
                            }
                        },
                        "required": True,
                    },
                }
            }
        },
        "components": {
            "schemas": {
                "Item": {
                    "title": "Item",

                            "application/json": {
                                "schema": {"$ref": "#/components/schemas/Item"}
                            }
                        },
                        "required": True,
                    },
                }
            }
        },
        "components": {
            "schemas": {
                "Item": {
                    "title": "Item",

Some of them also ✨ [**sponsor FastAPI**](../help-fastapi.md#sponsor-the-author){.internal-link target=_blank} ✨, this ensures the continued and healthy **development** of FastAPI and its **ecosystem**.

And it shows their true commitment to FastAPI and its **community** (you), as they not only want to provide you a **good service** but also want to make sure you have a **good and healthy framework**, FastAPI. 🙇

                    "parameters": [
                        {
                            "required": True,
                            "schema": {
                                "title": "Query",
                                "uniqueItems": True,
                                "type": "array",
                                "items": {"type": "integer"},
                            },

    "pydantic-extra-types >=2.0.0",
]

[tool.mypy]
strict = true

[[tool.mypy.overrides]]
module = "fastapi.concurrency"
warn_unused_ignores = false
ignore_missing_imports = true

[[tool.mypy.overrides]]
module = "fastapi.tests.*"
ignore_missing_imports = true
check_untyped_defs = true

[[tool.mypy.overrides]]
module = "docs_src.*"
disallow_incomplete_defs = false

### 使用 Pydantic 的`orm_mode`

现在，在用于查询的 Pydantic*模型*`Item`中`User`，添加一个内部`Config`类。

此类[`Config`](https://docs.pydantic.dev/latest/api/config/)用于为 Pydantic 提供配置。

在`Config`类中，设置属性`orm_mode = True`。

=== "Python 3.10+"

    ```Python hl_lines="13  17-18  29  34-35"
    {!> ../../../docs_src/sql_databases/sql_app_py310/schemas.py!}
    ```

=== "Python 3.9+"

    subprocess.run(["git", "config", "user.name", "github-actions"], check=True)
    subprocess.run(
        ["git", "config", "user.email", "******@****.***"], check=True
    )
    branch_name = "fastapi-people"
    logging.info(f"Creating a new branch {branch_name}")
    subprocess.run(["git", "checkout", "-b", branch_name], check=True)
    logging.info("Adding updated file")
    subprocess.run(