# Extra Models

Continuing with the previous example, it will be common to have more than one related model.

This is especially the case for user models, because:

* The **input model** needs to be able to have a password.
* The **output model** should not have a password.
* The **database model** would probably need to have a hashed password.

!!! danger
    Never store user's plaintext passwords. Always store a "secure hash" that you can then verify.

]

[tool.coverage.run]
parallel = true
source = [
    "docs_src",
    "tests",
    "fastapi"
]
context = '${CONTEXT}'
omit = [
    "docs_src/response_model/tutorial003_04.py",
    "docs_src/response_model/tutorial003_04_py310.py",
]

[tool.ruff.lint]
select = [
    "E",  # pycodestyle errors
    "W",  # pycodestyle warnings
    "F",  # pyflakes
    "I",  # isort

    access_token = create_access_token(
        data={"sub": user.username}, expires_delta=access_token_expires
    )
    return Token(access_token=access_token, token_type="bearer")


@app.get("/users/me/", response_model=User)
async def read_users_me(
    current_user: Annotated[User, Depends(get_current_active_user)],
):
    return current_user


@app.get("/users/me/items/")
async def read_own_items(

`RequestValidationError`はPydanticの<a href="https://docs.pydantic.dev/latest/concepts/models/#error-handling" class="external-link" target="_blank">`ValidationError`</a>のサブクラスです。

**FastAPI** は`response_model`でPydanticモデルを使用していて、データにエラーがあった場合、ログにエラーが表示されるようにこれを使用しています。

しかし、クライアントやユーザーはそれを見ることはありません。その代わりに、クライアントはHTTPステータスコード`500`の「Internal Server Error」を受け取ります。

```Python hl_lines="17"
{!../../../docs_src/path_params/tutorial005.py!}
```

#### *Enum-Wert* erhalten

Den tatsächlichen Wert (in diesem Fall ein `str`) erhalten Sie via `model_name.value`, oder generell, `ihr_enum_member.value`:

```Python hl_lines="20"
{!../../../docs_src/path_params/tutorial005.py!}
```

!!! tip "Tipp"

        data={"sub": user.username, "scopes": form_data.scopes},
        expires_delta=access_token_expires,
    )
    return Token(access_token=access_token, token_type="bearer")


@app.get("/users/me/", response_model=User)
async def read_users_me(
    current_user: Annotated[User, Depends(get_current_active_user)],
):
    return current_user


@app.get("/users/me/items/")
async def read_own_items(

            response_model_include=response_model_include,
            response_model_exclude=response_model_exclude,
            response_model_by_alias=response_model_by_alias,
            response_model_exclude_unset=response_model_exclude_unset,
            response_model_exclude_defaults=response_model_exclude_defaults,
            response_model_exclude_none=response_model_exclude_none,

!!! info
    ✔️ 🤯 👈 🎻 💪 🚫 🌐 Pydantic 🏷 💪.

    , 👆 5️⃣📆 💪 ⚙️ Pydantic 🏷.

    ✋️ 🚥 👆 ✔️ 📚 🎻 🤥 🤭, 👉 👌 🎱 ⚙️ 👫 🏋️ 🕸 🛠️ ⚙️ FastAPI. 👶

## 🎻 `response_model`

👆 💪 ⚙️ `dataclasses` `response_model` 🔢:

```Python hl_lines="1  7-13  19"
{!../../../docs_src/dataclasses/tutorial002.py!}
```

🎻 🔜 🔁 🗜 Pydantic 🎻.

👉 🌌, 🚮 🔗 🔜 🎦 🆙 🛠️ 🩺 👩‍💻 🔢:

### Memory per Process

Now, when the program loads things in memory, for example, a machine learning model in a variable, or the contents of a large file in a variable, all that **consumes a bit of the memory (RAM)** of the server.

def test_encode_model_with_alias_raises():
    with pytest.raises(ValidationError):
        ModelWithAlias(foo="Bar")


def test_encode_model_with_alias():
    model = ModelWithAlias(Foo="Bar")
    assert jsonable_encoder(model) == {"Foo": "Bar"}


def test_encode_model_with_default():
    model = ModelWithDefault(foo="foo", bar="bar")