It won't do any data conversion with Pydantic models, it won't convert the contents to any type, etc.

This gives you a lot of **flexibility**. You can return any data type, override any data declaration or validation, etc.

It also gives you a lot of **responsibility**. You have to make sure that the data you return is correct, in the correct format, that it can be serialized, etc.

/// tip

If you have strict type checks in your editor, mypy, etc, you can declare the function return type as `Any`.

That way you tell the editor that you are intentionally returning anything. But FastAPI will still do the data documentation, validation, filtering, etc. with the `response_model`.

///

    * If you are comparing Uvicorn, compare it against Daphne, Hypercorn, uWSGI, etc. Application servers.
* **Starlette**:
    * Will have the next best performance, after Uvicorn. In fact, Starlette uses Uvicorn to run. So, it probably can only get "slower" than Uvicorn by having to execute more code.
    * But it provides you the tools to build simple web applications, with routing based on paths, etc.

* `upgrade`: Upgrades

The same way you use `Body`, `Query`, etc. with your *path operation function* parameters, use `Depends` with a new parameter:

{* ../../docs_src/dependencies/tutorial001_an_py310.py hl[13,18] *}

Although you use `Depends` in the parameters of your function the same way you use `Body`, `Query`, etc, `Depends` works a bit differently.

You only give `Depends` a single parameter.

This is in contrast to the **development** stages, where you are constantly changing the code, breaking it and fixing it, stopping and restarting the development server, etc.

## Deployment Strategies { #deployment-strategies }

* API keys in:
    * Headers.
    * Query parameters.
    * Cookies, etc.

Plus all the security features from Starlette (including **session cookies**).

All built as reusable tools and components that are easy to integrate with your systems, data stores, relational and NoSQL databases, etc.

### Dependency Injection { #dependency-injection }

}
```

Again, doing just that declaration, with **FastAPI** you get:

* Editor support (completion, etc.), even for nested models
* Data conversion
* Data validation
* Automatic documentation

## Special types and validation { #special-types-and-validation }

Apart from normal singular types like `str`, `int`, `float`, etc. you can use more complex singular types that inherit from `str`.

Here are some possible ideas:

* An "Init Container" in Kubernetes that runs before your app container
* A bash script that runs the previous steps and then starts your application
    * You would still need a way to start/restart *that* bash script, detect errors, etc.

/// tip

Some of the tasks they can perform include:

* Adding labels to PRs.
* Editing PR titles.
* Adding commits on top of PRs to tweak them.
* Mark answers in GitHub Discussions questions, etc.
* Merge some specific types of PRs.

You can see the current team members in [FastAPI People - Team](./fastapi-people.md#team).