}
		})
	}
}

func TestEqual(t *testing.T) {
	vals := []interface{}{
		true, []byte("bytes"), float64(1.2), int64(-42), uint64(63), time.Duration(300),
		time.Now().UTC(), types.NullValue, NewListValue(), NewMapValue(),
		NewObjectValue(NewObjectType("TestObject", map[string]*DeclField{})),
	}
	for i, v := range vals {
		dv := testValue(t, int64(i), v)
		if dv.Equal(dv.ExprValue()) != types.True {

	"challenge":       contentTypeUnsafe,
	"charset":         contentTypeUnsafe,
	"class":           contentTypePlain,
	"classid":         contentTypeURL,
	"codebase":        contentTypeURL,
	"cols":            contentTypePlain,
	"colspan":         contentTypePlain,
	"content":         contentTypeUnsafe,
	"contenteditable": contentTypePlain,
	"contextmenu":     contentTypePlain,
	"controls":        contentTypePlain,

You can also write them in Scala or Groovy but that is not recommended.

Here is a breakdown of all options for implementing Gradle plugins:

[cols="~,~,~,~,~"]
|===
|*#* |*Using:* |*Type:* |*The Plugin is:* |*Recommended?*

|1
|Kotlin DSL
|Script plugin

	VMLS_GT_F32:       "VMLS.GT.F32",
	VMLS_LE_F32:       "VMLS.LE.F32",
	VMLS_F32:          "VMLS.F32",
	VMLS_ZZ_F32:       "VMLS.ZZ.F32",
	VMLS_EQ_F64:       "VMLS.EQ.F64",
	VMLS_NE_F64:       "VMLS.NE.F64",
	VMLS_CS_F64:       "VMLS.CS.F64",
	VMLS_CC_F64:       "VMLS.CC.F64",
	VMLS_MI_F64:       "VMLS.MI.F64",
	VMLS_PL_F64:       "VMLS.PL.F64",
	VMLS_VS_F64:       "VMLS.VS.F64",

  int size = end - start;

  SmallVector<int64_t, 4> vals;
  vals.resize(size);
  std::iota(vals.begin(), vals.end(), start);

  TensorType ty =
      tensorflow::GetTypeFromTFTensorShape({size}, builder->getIntegerType(64));
  return DenseIntElementsAttr::get(ty, vals);
}

// Return an Attr representation of the value.

	vars := measure(l, "variable")
	vals := measure(r, "value")
	rhs0 := rhs[0]

	if len(rhs) == 1 {
		if call, _ := ast.Unparen(rhs0).(*ast.CallExpr); call != nil {
			check.errorf(rhs0, WrongAssignCount, "assignment mismatch: %s but %s returns %s", vars, call.Fun, vals)
			return
		}
	}
	check.errorf(rhs0, WrongAssignCount, "assignment mismatch: %s but %s", vars, vals)
}

	for _, s := range p.Sample {
		for key, vals := range s.Label {
			for _, val := range vals {
				valueMap, ok := tagMap[key]
				if !ok {
					valueMap = make(map[string]int64)
					tagMap[key] = valueMap
				}
				valueMap[val] += o.SampleValue(s.Value)
			}
		}
		for key, vals := range s.NumLabel {
			unit := o.NumLabelUnits[key]
			for _, nval := range vals {
				val := formatTag(nval, unit)

Generates the source files for all ANTLR grammars for the given source set.

The ANTLR plugin adds the following dependencies to tasks added by the Java plugin.

.ANTLR plugin - additional task dependencies
[cols="a,a", options="header"]
|===
| Task name
| Depends on
| `compileJava`
| `generateGrammarSource`

| `compileTestJava`
| `generateTestGrammarSource`

| `compile__SourceSet__Java`

     */
    private
    fun File.injectAgentOptions(separator: String) {
        if (agentJarNames.isEmpty()) {
            return
        }
        var replacementsCount = 0
        // readLines eats EOLs, so we need to use postfix to make sure the last line ends with EOL too.
        writeBytes(readLines().joinToString(separator = separator, postfix = separator) { line ->
            when {

Mais en prêtant attention aux tests de performance et aux comparaisons, il faut tenir compte de ce qu'il suit.

## Tests de performance et rapidité

Lorsque vous vérifiez les tests de performance, il est commun de voir plusieurs outils de différents types comparés comme équivalents.

En particulier, on voit Uvicorn, Starlette et FastAPI comparés (parmi de nombreux autres outils).