* `tax: float = 10.5` has a default of `10.5`.
* `tags: List[str] = []` has a default of an empty list: `[]`.

but you might want to omit them from the result if they were not actually stored.

For example, if you have models with many optional attributes in a NoSQL database, but you don't want to send very long JSON responses full of default values.

### Use the `response_model_exclude_unset` parameter

It's relatively tightly coupled with relational databases (like MySQL or PostgreSQL), so, having a NoSQL database (like Couchbase, MongoDB, Cassandra, etc) as the main store engine is not very easy.

    And be compatible with all of them at the same time.

Create a utility function to hash a password coming from the user.

And another utility to verify if a received password matches the hash stored.

And another one to authenticate and return a user.

=== "Python 3.10+"

    ```Python hl_lines="7  48  55-56  59-60  69-75"
    {!> ../../../docs_src/security/tutorial004_an_py310.py!}
    ```

    end

    rect rgba(0, 255, 255, .1)
        code ->> function: say_hi(name="Rick")
        function ->> code: return stored result
    end

    rect rgba(0, 255, 255, .1)
        code ->> function: say_hi(name="Camila")
        function ->> code: return stored result
    end
```

💼 👆 🔗 `get_settings()`, 🔢 🚫 ✊ 🙆 ❌, ⚫️ 🕧 📨 🎏 💲.

Using `UploadFile` has several advantages over `bytes`:

* You don't have to use `File()` in the default value of the parameter.
* It uses a "spooled" file:
    * A file stored in memory up to a maximum size limit, and after passing this limit it will be stored in disk.
* This means that it will work well for large files like images, videos, large binaries, etc. without consuming all the memory.
* You can get metadata from the uploaded file.

    * Les cookies, etc.

Plus toutes les fonctionnalités de sécurités venant de Starlette (incluant les **cookies de sessions**).

Le tout conçu en composant réutilisable facilement intégrable à vos systèmes, data stores, base de données relationnelle ou NoSQL, etc.

### Injection de dépendances

```Python
commons: Annotated[dict, Depends(common_parameters)]
```

But because we are using `Annotated`, we can store that `Annotated` value in a variable and use it in multiple places:

=== "Python 3.10+"

    ```Python hl_lines="12  16  21"
    {!> ../../../docs_src/dependencies/tutorial001_02_an_py310.py!}
    ```

The fast food store has 8 processors (cashiers/cooks). While the concurrent burgers store might have had only 2 (one cashier and one cook).

But still, the final experience is not the best. 😞

---

This would be the parallel equivalent story for burgers. 🍔

For a more "real life" example of this, imagine a bank.

```Python hl_lines="18-20"
{!../../../docs_src/sql_databases_peewee/sql_app/main.py!}
```

Whenever you pass exactly the same content (exactly the same password) you get exactly the same gibberish.

But you cannot convert from the gibberish back to the password.

##### Why use password hashing

If your database is stolen, the thief won't have your users' plaintext passwords, only the hashes.

So, the thief won't be able to try to use those same passwords in another system (as many users use the same password everywhere, this would be dangerous).