In some cases, you might still have to use Pydantic's version of `dataclasses`. For example, if you have errors with the automatically generated API documentation.

In that case, you can simply swap the standard `dataclasses` with `pydantic.dataclasses`, which is a drop-in replacement:

{* ../../docs_src/dataclasses/tutorial003.py hl[1,5,8:11,14:17,23:25,28] *}

1. We still import `field` from standard `dataclasses`.

          .put("MD5", Hashing.md5())
          .put("SHA", Hashing.sha1()) // Not the official name, but still works
          .put("SHA1", Hashing.sha1()) // Not the official name, but still works
          .put("sHa-1", Hashing.sha1()) // Not the official name, but still works
          .put("SHA-1", Hashing.sha1())
          .put("SHA-256", Hashing.sha256())
          .put("SHA-384", Hashing.sha384())

**FastAPI** is already being used in production in many applications and systems. And the test coverage is kept at 100%. But its development is still moving quickly.

New features are added frequently, bugs are fixed regularly, and the code is still continuously improving.

Hiding your documentation user interfaces in production *shouldn't* be the way to protect your API.

That doesn't add any extra security to your API, the *path operations* will still be available where they are.

If there's a security flaw in your code, it will still exist.

/// warning

The current page still doesn't have a translation for this language.

But you can help translating it: [Contributing](https://fastapi.tiangolo.com/contributing/){.internal-link target=_blank}.

          .put("MD5", Hashing.md5())
          .put("SHA", Hashing.sha1()) // Not the official name, but still works
          .put("SHA1", Hashing.sha1()) // Not the official name, but still works
          .put("sHa-1", Hashing.sha1()) // Not the official name, but still works
          .put("SHA-1", Hashing.sha1())
          .put("SHA-256", Hashing.sha256())
          .put("SHA-384", Hashing.sha384())

## Use case

For example, imagine that you want to return an HTTP status code of "OK" `200` by default.

But if the data didn't exist, you want to create it, and return an HTTP status code of "CREATED" `201`.

But you still want to be able to filter and convert the data you return with a `response_model`.

For those cases, you can use a `Response` parameter.

## Use a `Response` parameter

    assertEquals(
        "next() should still return first element after peeking", "A", peekingIterator.next());

    assertEquals("Should be able to peek() at middle element", "B", peekingIterator.peek());
    assertEquals(
        "Should be able to peek() middle element multiple times", "B", peekingIterator.peek());
    assertEquals(
        "next() should still return middle element after peeking", "B", peekingIterator.next());

Like `item.model_dump(exclude_unset=True)`.

/// info

In Pydantic v1 the method was called `.dict()`, it was deprecated (but still supported) in Pydantic v2, and renamed to `.model_dump()`.

The examples here use `.dict()` for compatibility with Pydantic v1, but you should use `.model_dump()` instead if you can use Pydantic v2.

///

    assertEquals(
        "next() should still return first element after peeking", "A", peekingIterator.next());

    assertEquals("Should be able to peek() at middle element", "B", peekingIterator.peek());
    assertEquals(
        "Should be able to peek() middle element multiple times", "B", peekingIterator.peek());
    assertEquals(
        "next() should still return middle element after peeking", "B", peekingIterator.next());