// Test additional acquire
        session.acquire();
        assertTrue(session.isInUse(), "Session should still be in use after additional acquire");

        // Test release (still in use because of initial transport acquire)
        session.release();
        assertTrue(session.isInUse(), "Session should still be in use after one release");

        // Test final release
        session.release();

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`.

**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.

{* ../../docs_src/query_params_str_validations/tutorial002_an_py310.py hl[9] *}

Notice that the default value is still `None`, so the parameter is still optional.

But now, having `Query(max_length=50)` inside of `Annotated`, we are telling FastAPI that we want it to have **additional validation** for this value, we want it to have maximum 50 characters. 😎

/// tip

But it is still recommended to use the ideas above, using multiple classes, instead of these parameters.

This is because the JSON Schema generated in your app's OpenAPI (and the docs) will still be the one for the complete model, even if you use `response_model_include` or `response_model_exclude` to omit some attributes.

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.

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 { #use-a-response-parameter }

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.

///

            assertTrue(successfulThreads.get() > 0, "At least some threads should complete successfully");

            // The rate limiter should still be functional after concurrent access
            assertTrue(concurrentLimiter.checkAttempt("finaluser", "192.168.3.1"),
                    "Rate limiter should still be functional after concurrent operations");

            // Verify that the rate limiter tracked some activity

            // Refresh should not break anything
            orig.refresh();
            copy.refresh();

            // Both should still return null
            assertNull(orig.getSubject(), "Original should still return null after refresh");
            assertNull(copy.getSubject(), "Clone should still return null after refresh");
        }
    }

    @Test
    @DisplayName("renew: invokes getSubject and returns self")