!!! info
    To declare headers, you need to use `Header`, because otherwise the parameters would be interpreted as query parameters.

## Automatic conversion

`Header` has a little extra functionality on top of what `Path`, `Query` and `Cookie` provide.

* `le`: `l`ess than or `e`qual

!!! info
    `Query`, `Path`, and other classes you will see later are subclasses of a common `Param` class.

    All of them share the same parameters for additional validation and metadata you have seen.

!!! note "Technical Details"
    When you import `Query`, `Path` and others from `fastapi`, they are actually functions.

    That when called, return instances of classes of the same name.

That's what we'll solve, let's load the model before the requests are handled, but only right before the application starts receiving requests, not while  the code is being loaded.

## Lifespan

    Here we are focusing only on the tools and mechanics of databases.

!!! tip
    Instead of passing each of the keyword arguments to `Item` and reading each one of them from the Pydantic *model*, we are generating a `dict` with the Pydantic *model*'s data with:

    `item.dict()`

`HTTPException` is a normal Python exception with additional data relevant for APIs.

Because it's a Python exception, you don't `return` it, you `raise` it.

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

There are several ways to do it depending on your specific use case and the tools that you use.

### Always `raise` in Dependencies with `yield` and `except`

If you catch an exception in a dependency with `yield`, unless you are raising another `HTTPException` or similar, you should re-raise the original exception.

## Additional Response with `model`

You can pass to your *path operation decorators* a parameter `responses`.

It receives a `dict`, the keys are status codes for each response, like `200`, and the values are other `dict`s with the information for each of them.

Each of those response `dict`s can have a key `model`, containing a Pydantic model, just like `response_model`.

    So, you will have to make sure your data is of the correct type. E.g. it is compatible with JSON, if you are returning a `JSONResponse`.

    And also that you are not sending any data that should have been filtered by a `response_model`.

### More info

!!! note "Technical Details"

It is also built to work as a future reference.

So you can come back and see exactly what you need.

## Run the code

All the code blocks can be copied and used directly (they are actually tested Python files).

To run any of the examples, copy the code to a file `main.py`, and start `uvicorn` with:

<div class="termy">

```console
$ uvicorn main:app --reload