operation_security_dict: dict[str, list[str]] = {}
    for security_dependency in flat_dependant._security_dependencies:
        security_definition = jsonable_encoder(
            security_dependency._security_scheme.model,
            by_alias=True,
            exclude_none=True,
        )
        security_name = security_dependency._security_scheme.scheme_name
        security_definitions[security_name] = security_definition

				t.Fatalf("errors happened when query: %v", err)
			} else {
				CheckUser(t, newUser, user)
			}
		}
	}
}

func TestCreateFromMap(t *testing.T) {
	if err := DB.Model(&User{}).Create(map[string]interface{}{"Name": "create_from_map", "Age": 18}).Error; err != nil {
		t.Fatalf("failed to create data from map, got error: %v", err)
	}

	var result User

```

...這個回應會回傳：

```json
{
  "message": "Hello World"
}
```

當然，你大概能找到比格式化 JSON 更好的方式來利用這個能力。😉

### `orjson` 或回應模型 { #orjson-or-response-model }

如果你追求效能，使用[回應模型](../tutorial/response-model.md) 大概會比使用 `orjson` 回應更好。

有了回應模型，FastAPI 會使用 Pydantic 直接將資料序列化為 JSON，而不需要像其他情況那樣先經過 `jsonable_encoder` 之類的中介步驟。

而且在底層，Pydantic 用來序列化為 JSON 的 Rust 機制和 `orjson` 相同，因此用回應模型已經能獲得最佳效能。

	tx.Logger = currentLogger
	return
}

// Pluck queries a single column from a model, returning in the slice dest. E.g.:
//
//	var ages []int64
//	db.Model(&users).Pluck("age", &ages)
func (db *DB) Pluck(column string, dest interface{}) (tx *DB) {
	tx = db.getInstance()
	if tx.Statement.Model != nil {
		if tx.Statement.Parse(tx.Statement.Model) == nil {
			if f := tx.Statement.Schema.LookUpField(column); f != nil {

    /**
     * Set a given project property. Properties set through this method are only valid
     * for the current build session and do not modify the underlying project model.
     *
     * @param project the project to modify
     * @param key they property's key
     * @param value the value or {@code null} to unset the property
     */

    @Config(defaultValue = "HARD")
    public static final String MAVEN_MODEL_PROCESSOR_REFERENCE_TYPE = "maven.model.processor.referenceType";

    /**
     * User property key prefix for configuring per-object-type reference types.
     * Format: maven.model.processor.referenceType.{ClassName} = {ReferenceType}
     * Example: maven.model.processor.referenceType.Dependency = SOFT
     *
     * @since 4.1.0
     */

/// check | Inspired **FastAPI** to

Define extra validations for data types using the "default" value of model attributes. This improves editor support, and it was not available in Pydantic before.

`hashed_password`. To fix this, the declared `response_model` is cloned, if it is a Pydantic model class (or contains Pydantic model classes in it, e.g. in a `List[Item]`), the Pydantic model class(es) will be a different one (the "cloned" one). So, an object that is a subclass won't simply pass the validation and returned as-is, because it is no longer a sub-class of the cloned `response_model`. Instead, a new Pydantic model object will be created with the contents of the returned object. So, it will be a...

```console
$ pip install "fastapi[all]"
---> 100%
```

</div>

### Create the `Settings` object { #create-the-settings-object }

Import `BaseSettings` from Pydantic and create a sub-class, very much like with a Pydantic model.

The same way as with Pydantic models, you declare class attributes with type annotations, and possibly default values.

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