After you have tests, then you can upgrade the **FastAPI** version to a more recent one, and make sure that all your code is working correctly by running your tests.

If everything is working, or after you make the necessary changes, and all your tests are passing, then you can pin your `fastapi` to that new recent version.

## About Starlette

You shouldn't pin the version of `starlette`.

As Python advances, **newer versions** come with improved support for these type annotations and in many cases you won't even need to import and use the `typing` module to declare the type annotations.

If you can choose a more recent version of Python for your project, you will be able to take advantage of that extra simplicity.

In all the docs there are examples compatible with each version of Python (when there's a difference).

* Fix incorrect `Request` class import. PR [#493](https://github.com/tiangolo/fastapi/pull/493) by [@kamalgill](https://github.com/kamalgill).

## 0.38.0

* Add recent articles to [External Links](https://fastapi.tiangolo.com/external-links/) and recent opinions. PR [#490](https://github.com/tiangolo/fastapi/pull/490).

    ```

=== "Python 3.8+"

    ```Python hl_lines="14"
    {!> ../../../docs_src/body_nested_models/tutorial002.py!}
    ```

## Set types

But then we think about it, and realize that tags shouldn't repeat, they would probably be unique strings.

And Python has a special data type for sets of unique items, the `set`.

Then we can declare `tags` as a set of strings:

=== "Python 3.10+"

    ```Python hl_lines="12"

```

And in the file `sql_app/main.py` file, uncomment the body of the `async` dependency `reset_db_state()`:

```Python
async def reset_db_state():
    database.db._state._state.set(db_state_default.copy())
    database.db._state.reset()
```

Terminate your running app and start it again.

Repeat the same process with the 10 tabs. This time all of them will wait and you will get all the results without errors.

```

A **context manager** in Python is something that you can use in a `with` statement, for example, `open()` can be used as a context manager:

```Python
with open("file.txt") as file:
    file.read()
```

In recent versions of Python, there's also an **async context manager**. You would use it with `async with`:

```Python
async with lifespan(app):
    await do_stuff()
```