//     fgha[c]|[b]de -> fgha[b]|[c]de. Because these two blocks are the same size, we are done.
    // The Dolphin algorithm is attractive because it does the fewest array reads and writes: each
    // array slot is read and written exactly once. However, it can have very poor memory locality:
    // benchmarking shows it can take 7 times longer than the other two in some cases. The other two

You can use this template to get started, as it includes a lot of the initial set up, security, database and some API endpoints already done for you.

    assertThrows(IndexOutOfBoundsException.class, () -> sink.putBytes(new byte[8], 0, -1));
  }

  /**
   * This test creates a long random sequence of inputs, then a lot of differently configured sinks
   * process it; all should produce the same answer, the only difference should be the number of
   * process()/processRemaining() invocations, due to alignment.
   */

With **FastAPI**, using OpenAPI, you can define the names of these webhooks, the types of HTTP operations that your app can send (e.g. `POST`, `PUT`, etc.) and the request **bodies** that your app would send.

This can make it a lot easier for your users to **implement their APIs** to receive your **webhook** requests, they might even be able to autogenerate some of their own API code.

/// info

///

And when you return a `Response`, **FastAPI** will pass it directly.

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.

## Using the `jsonable_encoder` in a `Response` { #using-the-jsonable-encoder-in-a-response }

In Python 3.10, as an alternative to using the generics `Union` and `Optional`, you can use the <abbr title='also called "bitwise or operator", but that meaning is not relevant here'>vertical bar (`|`)</abbr> to declare unions of types, that's a lot better and simpler.

////

//// tab | Python 3.9+

You can use the same builtin types as generics (with square brackets and types inside):

* `list`
* `tuple`
* `set`
* `dict`

The same models are shared among requests, so, it's not one model per request, or one per user or something similar.

Let's imagine that loading the model can **take quite some time**, because it has to read a lot of **data from disk**. So you don't want to do it for every request.

## Accessing the request body in an exception handler { #accessing-the-request-body-in-an-exception-handler }

/// tip

To solve this same problem, it's probably a lot easier to use the `body` in a custom handler for `RequestValidationError` ([Handling Errors](../tutorial/handling-errors.md#use-the-requestvalidationerror-body){.internal-link target=_blank}).

{* ../../docs_src/dependencies/tutorial001_an_py310.py hl[9] *}

But then we get a `dict` in the parameter `commons` of the *path operation function*.

And we know that editors can't provide a lot of support (like completion) for `dict`s, because they can't know their keys and value types.

We can do better...

## What makes a dependency { #what-makes-a-dependency }

As code duplication increments the chances of bugs, security issues, code desynchronization issues (when you update in one place but not in the others), etc.

And these models are all sharing a lot of the data and duplicating attribute names and types.

We could do better.