- raw_headers
            - render
            - init_headers
            - headers
            - set_cookie
            - delete_cookie

::: fastapi.responses.ORJSONResponse
    options:
        members:
            - charset
            - status_code
            - media_type
            - body
            - background
            - raw_headers
            - render
            - init_headers

        KtDiagnosticClassRenderer.render(path.resolve("KtFirDiagnostics.kt"), diagnosticList, packageName, emptySet())
        KtDiagnosticClassImplementationRenderer.render(path.resolve("KtFirDiagnosticsImpl.kt"), diagnosticList, packageName, emptySet())
        FirDiagnosticToKtDiagnosticConverterRenderer.render(path.resolve("KtFirDataClassConverters.kt"), diagnosticList, packageName, emptySet())

				Having:  []clause.Expression{clause.Eq{"role", "admin"}},
			}, clause.GroupBy{
				Columns: []clause.Column{{Name: "gender"}},
				Having:  []clause.Expression{clause.Neq{"gender", "U"}},
			}},
			"SELECT * FROM `users` GROUP BY `role`,`gender` HAVING `role` = ? AND `gender` <> ?",
			[]interface{}{"admin", "U"},
		},
	}

	for idx, result := range results {

import org.jetbrains.kotlin.name.FqName
import org.jetbrains.kotlin.name.SpecialNames
import org.jetbrains.kotlin.name.StandardClassIds
import org.jetbrains.kotlin.renderer.DescriptorRenderer
import org.jetbrains.kotlin.renderer.render
import org.jetbrains.kotlin.resolve.calls.inference.CapturedType
import org.jetbrains.kotlin.resolve.descriptorUtil.annotationClass
import org.jetbrains.kotlin.types.*
import org.jetbrains.kotlin.types.checker.NewCapturedType

    share a link to Colab/Jupyter/any notebook. placeholder: Tell us what you
    see! value: render: shell validations: required: true

-   type: textarea id: logs attributes: label: Relevant log output description:
    Please copy and paste any relevant log output. This will be automatically

		diag.Info:    "",           // no special color for info messages
		diag.Warning: "\033[33m",   // yellow
		diag.Error:   "\033[1;31m", // bold red
	}
)

// render turns a Message instance into a string with an option of colored bash output
func render(m diag.Message, colorize bool) string {
	return fmt.Sprintf("%s%v%s [%v]%s %s",
		colorPrefix(m, colorize), m.Type.Level(), colorSuffix(colorize),

abstract class AbstractDiagnosticsDataClassRenderer : DiagnosticListRenderer() {
    override fun render(file: File, diagnosticList: DiagnosticList, packageName: String, starImportsToAdd: Set<String>) {
        val hlDiagnosticsList = HLDiagnosticConverter.convert(diagnosticList)
        file.writeToFileUsingSmartPrinterIfFileContentChanged { render(hlDiagnosticsList, packageName) }
    }

		bucket:       "bucket",
		root:         "folder/prefix",
		recursive:    false,
		status:       scanStateSuccess,
		fileNotFound: false,
		error:        "",
		started:      metaCacheTestsetTimestamp,
		ended:        metaCacheTestsetTimestamp.Add(time.Minute),
		lastUpdate:   metaCacheTestsetTimestamp.Add(time.Minute),
		lastHandout:  metaCacheTestsetTimestamp,
		dataVersion:  metacacheStreamVersion,
	},
	1: {

    const val HEADER_TABLE_SIZE = 1

    /** HTTP/2: The peer must not send a PUSH_PROMISE frame when this is 0. */
    const val ENABLE_PUSH = 2

    /** Sender's maximum number of concurrent streams. */
    const val MAX_CONCURRENT_STREAMS = 4

    /** HTTP/2: Size in bytes of the largest frame payload the sender will accept. */
    const val MAX_FRAME_SIZE = 5

* Import `Jinja2Templates`.
* Create a `templates` object that you can re-use later.
* Declare a `Request` parameter in the *path operation* that will return a template.
* Use the `templates` you created to render and return a `TemplateResponse`, pass the name of the template, the request object, and a "context" dictionary with key-value pairs to be used inside of the Jinja2 template.

```Python hl_lines="4  11  15-18"