If one of your dependencies is declared multiple times for the same *path operation*, for example, multiple dependencies have a common sub-dependency, **FastAPI** will know to call that sub-dependency only once per request.

        }
    ]
}
```

## 밑줄 변환 비활성화하기 { #disable-convert-underscores }

일반적인 헤더 매개변수와 마찬가지로, 매개변수 이름에 밑줄 문자가 있으면 **자동으로 하이픈으로 변환**됩니다.

예를 들어, 코드에 `save_data` 헤더 매개변수가 있으면, 기대되는 HTTP 헤더는 `save-data`이고, 문서에서도 그렇게 표시됩니다.

어떤 이유로든 이 자동 변환을 비활성화해야 한다면, 헤더 매개변수용 Pydantic 모델에서도 비활성화할 수 있습니다.

{* ../../docs_src/header_param_models/tutorial003_an_py310.py hl[19] *}

/// warning | 경고

.settings/**

# Files generated by JetBrains IDEs, e.g. IntelliJ IDEA
.idea/
*.iml

# Vscode files
.vscode

# This is where the result of the go build goes
/output*/
/_output*/
/_output

# Emacs save files
*~
\#*\#
.\#*

# Vim-related files
[._]*.s[a-w][a-z]
[._]s[a-w][a-z]
*.un~
Session.vim
.netrwhist

# cscope-related files
cscope.*

# Go test binaries
*.test

            "input": "plumbus",
        }
    ]
}
```

## 禁用下划线转换 { #disable-convert-underscores }

与常规的 header 参数相同，当参数名中包含下划线时，会**自动转换为连字符**。

例如，如果你的代码中有一个名为 `save_data` 的 header 参数，那么预期的 HTTP 头将是 `save-data`，并且在文档中也会以这种形式显示。

如果由于某些原因你需要禁用这种自动转换，你也可以在用于 header 参数的 Pydantic 模型中进行设置。

{* ../../docs_src/header_param_models/tutorial003_an_py310.py hl[19] *}

/// warning | 警告

                                        }
                                    }
                                },
                            },
                        },
                        "summary": "Save Item No Body",
                        "operationId": "save_item_no_body_items__post",
                        "requestBody": {
                            "content": {
                                "application/json": {

            "input": "plumbus",
        }
    ]
}
```

## 停用底線轉換 { #disable-convert-underscores }

與一般標頭參數相同，當參數名稱包含底線字元時，會自動轉換為連字號。

例如，若在程式碼中有標頭參數 `save_data`，實際期望的 HTTP 標頭為 `save-data`，在文件中也會如此顯示。

如果因某些原因需要停用這個自動轉換，你也可以在標頭參數的 Pydantic 模型上設定。

{* ../../docs_src/header_param_models/tutorial003_an_py310.py hl[19] *}

/// warning | 警告

In this type of scenario, you probably would want to have **a single (Uvicorn) process per container**, as you would already be handling replication at the cluster level.

So, in this case, you **would not** want to have a multiple workers in the container, for example with the `--workers` command line option. You would want to have just a **single Uvicorn process** per container (but probably multiple containers).

                    // Simulate class not found
                    throw new ClassNotFoundException(name);
                }
                return super.loadClass(name);
            }
        };

        // Save original ClassLoader
        ClassLoader originalClassLoader = Thread.currentThread().getContextClassLoader();

        try {
            // Set custom ClassLoader

    * This is comparable to using the model's `.model_dump()` method again, but it makes sure (and converts) the values to data types that can be converted to JSON, for example, `datetime` to `str`.
* Save the data to your DB.
* Return the updated model.

{* ../../docs_src/body_updates/tutorial002_py310.py hl[28:35] *}

/// tip

You can actually use this same technique with an HTTP `PUT` operation.

This can save everyone a lot of time and frustration.

For any non-trivial change, we need to be able to answer these questions:

* Why is this change done? What's the use case?
* For user-facing features, what will the API look like?
* What test cases should it have? What could go wrong?
* How will it roughly be implemented? We'll happily provide code pointers to save you time.