"required": True,
        },
    },
)
async def create_item(request: Request):
    raw_body = await request.body()
    try:
        data = yaml.safe_load(raw_body)
    except yaml.YAMLError:
        raise HTTPException(status_code=422, detail="Invalid YAML")
    try:
        item = Item.model_validate(data)
    except ValidationError as e:

                    sqlalchemy_safe=sqlalchemy_safe,
                )
                encoded_value = jsonable_encoder(
                    value,
                    by_alias=by_alias,
                    exclude_unset=exclude_unset,
                    exclude_none=exclude_none,
                    custom_encoder=custom_encoder,
                    sqlalchemy_safe=sqlalchemy_safe,
                )

        run: echo "$GITHUB_CONTEXT"
      - uses: actions/checkout@v4
      # Ref: https://github.com/actions/runner/issues/2033
      - name: Fix git safe.directory in container
        run: mkdir -p /home/runner/work/_temp/_github_home && printf "[safe]\n\tdirectory = /github/workspace" > /home/runner/work/_temp/_github_home/.gitconfig
      # Allow debugging with tmate
      - name: Setup tmate session

            "required": True,
        },
    },
)
async def create_item(request: Request):
    raw_body = await request.body()
    try:
        data = yaml.safe_load(raw_body)
    except yaml.YAMLError:
        raise HTTPException(status_code=422, detail="Invalid YAML")
    try:
        item = Item.parse_obj(data)
    except ValidationError as e:

    }


@needs_pydanticv1
def test_custom_encoders():
    class safe_datetime(datetime):
        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()}
    )

* There can be **multiple processes** of the **same program** running at the same time.

If you check out the "task manager" or "system monitor" (or similar tools) in your operating system, you will be able to see many of those processes running.

But in our code we are actually using `secrets.compare_digest()`.

In short, it will take the same time to compare `stanleyjobsox` to `stanleyjobson` than it takes to compare `johndoe` to `stanleyjobson`. And the same for the password.

That way, using `secrets.compare_digest()` in your application code, it will be safe against this whole range of security attacks.

### Return the error

And these same full-stack generators were the base of the [**FastAPI** Project Generators](project-generation.md){.internal-link target=_blank}.

!!! info
    Flask-apispec was created by the same Marshmallow developers.

!!! check "Inspired **FastAPI** to"
    Generate the OpenAPI schema automatically, from the same code that defines serialization and validation.

Do you want to just have a `str`? Or just a `dict`? Or a database class model instance directly? It all works the same way.

You actually don't have users that log in to your application but robots, bots, or other systems, that have just an access token? Again, it all works the same.

You can use the same dependency overrides from [Testing Dependencies with Overrides](testing-dependencies.md){.internal-link target=_blank} to alter a database for testing.

You could want to set up a different database for testing, rollback the data after the tests, pre-fill it with some testing data, etc.

The main idea is exactly the same you saw in that previous chapter.

## Add tests for the SQL app