pass

    class MyModel(BaseModel):
        dt_field: safe_datetime

    instance = MyModel(dt_field=safe_datetime.now())

    encoded_instance = jsonable_encoder(
        instance, custom_encoder={safe_datetime: lambda o: o.isoformat()}
    )
    assert encoded_instance["dt_field"] == instance.dt_field.isoformat()


def test_custom_enum_encoders():
    def custom_enum_encoder(v: Enum):

then it is a "callable".

## Classes as dependencies

You might notice that to create an instance of a Python class, you use that same syntax.

For example:

```Python
class Cat:
    def __init__(self, name: str):
        self.name = name


fluffy = Cat(name="Mr Fluffy")
```

In this case, `fluffy` is an instance of the class `Cat`.

And to create `fluffy`, you are "calling" `Cat`.

    the key value sent in the query parameter automatically and provides it as the
    dependency result. But it doesn't define how to send that API key to the client.

    ## Usage

    Create an instance object and use that object as the dependency in `Depends()`.

    The dependency result will be a string containing the key value.

    ## Example

    ```python
    from fastapi import Depends, FastAPI

# `Response` class

You can declare a parameter in a *path operation function* or dependency to be of type `Response` and then you can set data for the response like headers or cookies.

You can also use it directly to create an instance of it and return it from your *path operations*.

You can import it directly from `fastapi`:

```python
from fastapi import Response
```

### Create a `SessionLocal` class

Each instance of the `SessionLocal` class will be a database session. The class itself is not a database session yet.

But once we create an instance of the `SessionLocal` class, this instance will be the actual database session.

We name it `SessionLocal` to distinguish it from the `Session` we are importing from SQLAlchemy.

### Bước 2: Tạo một `FastAPI` "instance"

```Python hl_lines="3"
{!../../../docs_src/first_steps/tutorial001.py!}
```

Biến `app` này là một "instance" của class `FastAPI`.

Đây sẽ là điểm cốt lõi để tạo ra tất cả API của bạn.

`app` này chính là điều được nhắc tới bởi `uvicorn` trong câu lệnh:

    {!> ../../../docs_src/settings/tutorial001_pv1.py!}
    ```

!!! tip
    If you want something quick to copy and paste, don't use this example, use the last one below.

Then, when you create an instance of that `Settings` class (in this case, in the `settings` object), Pydantic will read the environment variables in a case-insensitive way, so, an upper-case variable `APP_NAME` will still be read for the attribute `app_name`.

│   ├── main.py
└── static
    ├── redoc.standalone.js
    ├── swagger-ui-bundle.js
    └── swagger-ui.css
```

### Serve the static files

* Import `StaticFiles`.
* "Mount" a `StaticFiles()` instance in a specific path.

```Python hl_lines="7  11"
{!../../../docs_src/custom_docs_ui/tutorial002.py!}
```

### Test the static files

!!! note "Technical Details"
    When you import `Query`, `Path` and others from `fastapi`, they are actually functions.

    That when called, return instances of classes of the same name.

    So, you import `Query`, which is a function. And when you call it, it returns an instance of a class also named `Query`.

    These functions are there (instead of just using the classes directly) so that your editor doesn't mark errors about their types.

Tú declaras la "forma" de los datos mediante clases con atributos.

Cada atributo tiene un tipo.

Luego creas un instance de esa clase con algunos valores y Pydantic validará los valores, los convertirá al tipo apropiado (si ese es el caso) y te dará un objeto con todos los datos.

Y obtienes todo el soporte del editor con el objeto resultante.