```Python
    first_name, last_name
```

naar:

```Python
    first_name: str, last_name: str
```

Dat is alles.

Dat zijn de "type hints":

{* ../../docs_src/python_types/tutorial002.py hl[1] *}


Dit is niet hetzelfde als het declareren van standaardwaarden zoals bij:

```Python
    first_name="john", last_name="doe"
```

Het is iets anders.

        doc.put("key9", new ArrayList<Integer>(Arrays.asList(777, 888, 999)));
        assertEquals(777, DocumentUtil.getValue(doc, "key9", Integer.class));
    }

    public void test_date() {
        Map<String, Object> doc = new HashMap<>();

        Date expected4 = new Date();
        doc.put("key4", expected4);
        assertEquals(expected4, DocumentUtil.getValue(doc, "key4", Date.class));
    }

        originalPairs.add(new AvFlags(0x12345678));
        originalPairs.add(new AvTimestamp(new byte[] { 0x01, 0x02, 0x03, 0x04, 0x05, 0x06, 0x07, 0x08 }));
        originalPairs.add(new AvTargetName("TESTNAME".getBytes()));
        originalPairs.add(new AvSingleHost(new byte[] { 0x11, 0x22, 0x33, 0x44 }));
        originalPairs.add(new AvChannelBindings(new byte[] { 0x55, 0x66 }));

      hermetic_cuda_compute_capabilities,
  )


def set_cuda_local_path(environ_cp, dist_name, env_var):
  ask_path = (
      'Please specify the local {} path you want to use '
      'or leave empty to use the default version. '
  ).format(dist_name)
  local_path = get_from_env_or_user_or_default(
      environ_cp, env_var, ask_path, None
  )
  if local_path:

  using tensorflow::shape_inference::ShapeHandle;

  const int num_inputs = input_shapes->num_items;
  NodeDef node_def;
  tensorflow::ImmediateExecutionOperation* op = tensorflow::unwrap(tfe_op);
  node_def.set_name(op->Name());
  node_def.set_op(op->Name());
  for (int i = 0; i < num_inputs; ++i) {
    node_def.add_input("dummy_input");
  }
  OperationFromInterface(op)->Attrs().FillAttrValueMap(node_def.mutable_attr());

func TestQueryScanToArray(t *testing.T) {
	err := DB.Create(&User{Name: "testname1", Age: 10}).Error
	if err != nil {
		t.Fatal(err)
	}

	users := [2]*User{{Name: "1"}, {Name: "2"}}
	err = DB.Model(&User{}).Where("name = ?", "testname1").Find(&users).Error
	if err != nil {
		t.Fatal(err)
	}
	if users[0] == nil || users[0].Name != "testname1" {
		t.Error("users[0] not covered")
	}
	if users[1] != nil {

//
//	STEP 1: Call the handler with the unsigned HTTP request (anonReq), assert for the `ErrAccessDenied` error response.
func ExecObjectLayerAPIAnonTest(t *testing.T, obj ObjectLayer, testName, bucketName, objectName, instanceType string, apiRouter http.Handler,
	anonReq *http.Request, bucketPolicy *policy.BucketPolicy,
) {
	anonTestStr := "Anonymous HTTP request test"

		t.Fatalf("no view should be created, got %v", err)
	}

	query := DB.Model(&User{}).
		Select("users.id as users_id, users.name as users_name, pets.id as pets_id, pets.name as pets_name").
		Joins("inner join pets on pets.user_id = users.id")

	if err := DB.Migrator().CreateView("users_pets", gorm.ViewOption{Query: query}); err != nil {
		t.Fatalf("Failed to crate view, got %v", err)
	}

}

void TF_SetAttrFuncName(TF_OperationDescription* desc, const char* attr_name,
                        const char* value, size_t length) {
  tensorflow::NameAttrList func_name;
  func_name.set_name(string(value, value + length));
  desc->node_builder.Attr(attr_name, func_name);
}

void TF_SetAttrShape(TF_OperationDescription* desc, const char* attr_name,
                     const int64_t* dims, int num_dims) {

  if (TF_TensorDefaultAlignment() > 0) {
    EXPECT_FALSE(TF_TensorIsAligned(a));
  }
  TF_DeleteTensor(a);
}

TEST(CAPI, MessageBufferConversion) {
  NodeDef node_in, node_out;
  node_in.set_name("Test name");
  node_in.set_op("Test op");

  TF_Buffer* buffer = TF_NewBuffer();
  TF_CHECK_OK(MessageToBuffer(node_in, buffer));
  TF_CHECK_OK(BufferToMessage(buffer, &node_out));
  TF_DeleteBuffer(buffer);