And as the code related to SQLAlchemy and the SQLAlchemy models lives in separate independent files, you would even be able to perform the migrations with Alembic without having to install FastAPI, Pydantic, or anything else.

The same way, you would be able to use the same SQLAlchemy models and utilities in other parts of your code that are not related to **FastAPI**.

In this example, to be able to have both `HTTPException`s in the same code, Starlette's exceptions is renamed to `StarletteHTTPException`:

```Python
from starlette.exceptions import HTTPException as StarletteHTTPException
```

### Re-use **FastAPI**'s exception handlers

When the `with` block finishes, it makes sure to close the file, even if there were exceptions.

When you create a dependency with `yield`, **FastAPI** will internally create a context manager for it, and combine it with some other related tools.

### Using context managers in dependencies with `yield`

!!! warning
    This is, more or less, an "advanced" idea.

    If you are just starting with **FastAPI** you might want to skip it for now.

          required: true
        - label: I already checked if it is not related to FastAPI but to [Pydantic](https://github.com/pydantic/pydantic).
          required: true
        - label: I already checked if it is not related to FastAPI but to [Swagger UI](https://github.com/swagger-api/swagger-ui).
          required: true
        - label: I already checked if it is not related to FastAPI but to [ReDoc](https://github.com/Redocly/redoc).

    return files


def generate_renamed_section_items(
    items: List[Union[Page, Section, Link]], *, config: MkDocsConfig
) -> List[Union[Page, Section, Link]]:
    new_items: List[Union[Page, Section, Link]] = []
    for item in items:
        if isinstance(item, Section):
            new_title = item.title
            new_children = generate_renamed_section_items(item.children, config=config)

Like `item.model_dump(exclude_unset=True)`.

!!! info
    In Pydantic v1 the method was called `.dict()`, it was deprecated (but still supported) in Pydantic v2, and renamed to `.model_dump()`.

    The examples here use `.dict()` for compatibility with Pydantic v1, but you should use `.model_dump()` instead if you can use Pydantic v2.

    !!! note
        The `--no-cache-dir` is only related to `pip`, it has nothing to do with Docker or containers.

    The `--upgrade` option tells `pip` to upgrade the packages if they are already installed.

# 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.

### Tags with Enums

If you have a big application, you might end up accumulating **several tags**, and you would want to make sure you always use the **same tag** for related *path operations*.

In these cases, it could make sense to store the tags in an `Enum`.

**FastAPI** supports that the same way as with plain strings:

```Python hl_lines="1  8-10  13  18"

* If you can't understand the question, ask for more **details**.

### Reproduce the problem

For most of the cases and most of the questions there's something related to the person's **original code**.

In many cases they will only copy a fragment of the code, but that's not enough to **reproduce the problem**.