{* ../../docs_src/query_params_str_validations/tutorial002_py310.py hl[7] *}

As in this case (without using `Annotated`) we have to replace the default value `None` in the function with `Query()`, we now need to set the default value with the parameter `Query(default=None)`, it serves the same purpose of defining that default value (at least for FastAPI).

So:

```Python
q: str | None = Query(default=None)
```

Directory for files of schema info

Files are auto-generated by DBFlute tasks.

# Response - Change Status Code { #response-change-status-code }

You probably read before that you can set a default [Response Status Code](../tutorial/response-status-code.md){.internal-link target=_blank}.

But in some cases you need to return a different status code than the default.

## Use case { #use-case }

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

# For most projects, this workflow file will not need changing; you simply need
# to commit it to your repository.
#
# You may wish to alter this file to override the set of languages analyzed,
# or to provide custom queries or build logic.
name: "CodeQL"

on:
  push:
    branches: [master]
  pull_request:
    # The branches below must be a subset of the branches above
    branches: [master]
  schedule:
    - cron: '0 11 * * 4'

jobs:

You don't necessarily need OAuth2 scopes, and you can handle authentication and authorization however you want.

But OAuth2 with scopes can be nicely integrated into your API (with OpenAPI) and your API docs.

Nevertheless, you still enforce those scopes, or any other security/authorization requirement, however you need, in your code.

In many cases, OAuth2 with scopes can be an overkill.

import java.lang.annotation.Target;
import org.jspecify.annotations.NullMarked;

/**
 * Disables Animal Sniffer's checking of compatibility with older versions of Java/Android.
 *
 * <p>Each package's copy of this annotation needs to be listed in our {@code pom.xml}.
 */
@Target({METHOD, CONSTRUCTOR, TYPE, FIELD})
@NullMarked

# JSON Compatible Encoder { #json-compatible-encoder }

There are some cases where you might need to convert a data type (like a Pydantic model) to something compatible with JSON (like a `dict`, `list`, etc).

For example, if you need to store it in a database.

For that, **FastAPI** provides a `jsonable_encoder()` function.

## Using the `jsonable_encoder` { #using-the-jsonable-encoder }

	CSRRC	X0, CYCLE, (X10)		// ERROR "needs an integer register output"
	CSRRC	$-1, TIME, X15			// ERROR "immediate out of range 0 to 31"
	CSRRCI	$32, TIME, X15			// ERROR "immediate out of range 0 to 31"
	CSRRCI	$1, TIME, (X15)			// ERROR "needs an integer register output"
	CSRRS	(X10), CYCLE, X5		// ERROR "integer register or immediate expected for 1st operand"
	CSRRS	X0, CYCLE, (X10)		// ERROR "needs an integer register output"

				return
			}
		}
		// Set this for multipart only operations, we need to differentiate during
		// decryption if the file was actually multipart or not.
		encMetadata[ReservedMetadataPrefix+"Encrypted-Multipart"] = ""
	}

	// Extract metadata that needs to be saved.
	metadata, err := extractMetadataFromReq(ctx, r)
	if err != nil {

            field_dict = asdict(self.field_info)
            annotated_args = (
                field_dict["annotation"],
                *field_dict["metadata"],
                # this FieldInfo needs to be created again so that it doesn't include
                # the old field info metadata and only the rest of the attributes
                Field(**field_dict["attributes"]),
            )