///

In HTTP, you send a numeric status code of 3 digits as part of the response.

These status codes have a name associated to recognize them, but the important part is the number.

In short:

* `100 - 199` are for "Information". You rarely use them directly.  Responses with these status codes cannot have a body.
* **`200 - 299`** are for "Successful" responses. These are the ones you would use the most.

* `title`: the title of your API.
* `oauth2_redirect_url`: you can use `app.swagger_ui_oauth2_redirect_url` here to use the default.
* `swagger_js_url`: the URL where the HTML for your Swagger UI docs can get the **JavaScript** file. This is the custom CDN URL.

For example, if an attacker were to upload a malicious video file, they could
potentially exploit a vulnerability in the TensorFlow code that handles videos,
which could allow them to execute arbitrary code on the system running
TensorFlow.

It is important to keep TensorFlow up to date with the latest security patches
and follow the sandboxing guideline above to protect against these types of
vulnerabilities.

{* ../../docs_src/query_param_models/tutorial001_an_py310.py hl[9:13,17] *}

**FastAPI** will **extract** the data for **each field** from the **query parameters** in the request and give you the Pydantic model you defined.

## Check the Docs { #check-the-docs }

You can see the query parameters in the docs UI at `/docs`:

<div class="screenshot">
<img src="/img/tutorial/query-param-models/image01.png">
</div>

At some point you would have started the definition of the function, you had the parameters ready...

But then you have to call "that method that converts the first letter to upper case".

Was it `upper`? Was it `uppercase`? `first_uppercase`? `capitalize`?

Then, you try with the old programmer's friend, editor autocompletion.

You type the first parameter of the function, `first_name`, then a dot (`.`) and then hit `Ctrl+Space` to trigger the completion.

If the top level value of the JSON body you expect is a JSON `array` (a Python `list`), you can declare the type in the parameter of the function, the same as in Pydantic models:

```Python
images: List[Image]
```

or in Python 3.9 and above:

```Python
images: list[Image]
```

as in:

{* ../../docs_src/body_nested_models/tutorial008_py39.py hl[13] *}

Declare the **cookie** parameters that you need in a **Pydantic model**, and then declare the parameter as `Cookie`:

{* ../../docs_src/cookie_param_models/tutorial001_an_py310.py hl[9:12,16] *}

**FastAPI** will **extract** the data for **each field** from the **cookies** received in the request and give you the Pydantic model you defined.

## Check the Docs { #check-the-docs }

If something seems interesting and useful to your project, go ahead and check it, but otherwise, you might probably just skip them.

/// tip

/// note

Keep in mind that you have to return the `JSONResponse` directly.

///

/// info

The `model` key is not part of OpenAPI.

**FastAPI** will take the Pydantic model from there, generate the JSON Schema, and put it in the correct place.

The correct place is:

* In the key `content`, that has as value another JSON object (`dict`) that contains:

When you try to open the URL for the first time (or click the "Execute" button in the docs) the browser will ask you for your username and password:

<img src="/img/tutorial/security/image12.png">

## Check the username { #check-the-username }

Here's a more complete example.

Use a dependency to check if the username and password are correct.