KEY:
site  label the server and its location

ARGS:
name     (string)    name for the site e.g. "cal-rack0"
region   (string)    name of the location of the server e.g. "us-west-1"
comment  (sentence)  optionally add a comment to this setting
```

or environment variables

```
KEY:
site  label the server and its location

ARGS:
MINIO_SITE_NAME     (string)    name for the site e.g. "cal-rack0"

abstract class AdHocPerformanceScenario(os: Os, arch: Arch = Arch.AMD64) : BuildType({
    val id = "Util_Performance_AdHocPerformanceScenario${os.asName()}${arch.asName()}"
    name = "AdHoc Performance Scenario - ${os.asName()} ${arch.asName()}"
    id(id)

    applyPerformanceTestSettings(os = os, arch = arch, timeout = 420)
    artifactRules = individualPerformanceTestArtifactRules

    params {

    testClasses: List<String>,
) : OsAwareBaseGradleBuildType(os = os, stage = stage, init = {

    id("${model.projectId}_${docsTestType.docsTestName}_${os.asName()}_$index")
    name = "${docsTestType.docsTestDesc} - ${testJava.version.name.toCapitalized()} ${os.asName()} ($index)"

    applyTestDefaults(
        model,
        this,
        "docs:docsTest${if (testSplitType == EXCLUDE) " docs:checkSamples" else ""}",

import jetbrains.buildServer.configs.kotlin.ParameterDisplay

class RerunFlakyTest(os: Os, arch: Arch = Arch.AMD64) : BuildType({
    val id = "Util_RerunFlakyTest${os.asName()}${arch.asName()}"
    name = "Rerun Flaky Test - ${os.asName()} ${arch.asName()}"
    description = "Allows you to rerun a selected flaky test 10 times"
    id(id)
    val testJvmVendorParameter = "testJavaVendor"
    val testJvmVersionParameter = "testJavaVersion"

     */
    private static final long serialVersionUID = 1L;

    /**
     * {@link NullArgumentException}を作成します。
     *
     * @param argName
     *            {@code null} である引数の名前
     */
    public NullArgumentException(final String argName) {
        super(argName, "ECL0008", asArray(argName));
    }

All container images are available as manifest lists and support the described
architectures. It is also possible to pull a specific architecture directly by
adding the "-$ARCH" suffix  to the container image name.

name | architectures
---- | -------------

        "hide": true,
        "iconColor": "rgba(0, 211, 255, 1)",
        "name": "Annotations & Alerts",
        "target": {
          "limit": 100,
          "matchAny": false,
          "tags": [],
          "type": "dashboard"
        },
        "type": "dashboard"
      }
    ]
  },
  "__inputs": [
    {
      "name": "DS_PROMETHEUS",
      "label": "Prometheus",
      "description": "", 

	omitColumns := []string{}
	selectColumns, _ := association.DB.Statement.SelectAndOmitColumns(true, false)
	for name, ok := range selectColumns {
		columnName := ""
		if strings.HasPrefix(name, association.Relationship.Name) {
			if columnName = strings.TrimPrefix(name, association.Relationship.Name); columnName == ".*" {
				columnName = name
			}

						t.Run(name, func(t *testing.T) {
							dbName := DB.NamingStrategy.ColumnName("", name)

							switch name {
							case "Name":
								if _, ok := allMap[idx][dbName].(string); !ok {
									t.Errorf("invalid data type for %v, got %#v", dbName, allMap[idx][dbName])
								}
							case "Age":
								if _, ok := allMap[idx][dbName].(uint); !ok {

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.

///