SimpleProblemCollector result = validate("missing-plugin-dependency-version.xml");

        assertViolations(result, 0, 1, 0);

        assertTrue(result.getErrors().get(0).contains("test:a"));
    }

    @Test
    void testBadPluginDependencyVersion() throws Exception {
        SimpleProblemCollector result = validate("bad-plugin-dependency-version.xml");

flow/core/runtime_fallback/test/saved_model,tensorflow/core/runtime_fallback/test/testdata,tensorflow/core/tfrt/stubs,tensorflow/core/tfrt/tfrt_session,tensorflow/core/tfrt/mlrt,tensorflow/core/tfrt/mlrt/attribute,tensorflow/core/tfrt/mlrt/kernel,tensorflow/core/tfrt/mlrt/bytecode,tensorflow/core/tfrt/mlrt/interpreter,tensorflow/compiler/mlir/tfrt/translate/mlrt,tensorflow/compiler/mlir/tfrt/translate/mlrt/testdata,tensorflow/core/tfrt/gpu,tensorflow/core/tfrt/run_handler_thread_pool,tensorflow/...

	}

	count := 0
	for rows.Next() {
		var name string
		var age int64
		rows.Scan(&name, &age)
		count++
	}

	if count != 2 {
		t.Errorf("Should found two records")
	}
}

func TestRaw(t *testing.T) {
	user1 := User{Name: "ExecRawSqlUser1", Age: 1}
	user2 := User{Name: "ExecRawSqlUser2", Age: 10}
	user3 := User{Name: "ExecRawSqlUser3", Age: 20}
	DB.Save(&user1).Save(&user2).Save(&user3)

        .isEqualTo(3);
  }

  @GwtIncompatible
  public void testMax_noArgs() {
    assertThrows(IllegalArgumentException.class, () -> max());
  }

  public void testMax() {
    assertThat(max(LEAST)).isEqualTo(LEAST);
    assertThat(max(GREATEST)).isEqualTo(GREATEST);
    assertThat(max((short) 8, (short) 6, (short) 7, (short) 5, (short) 3, (short) 0, (short) 9))

E após procurar por muito tempo por um framework similar e testar muitas alternativas diferentes, APIStar foi a melhor opção disponível.

* <a href="https://hub.docker.com/_/redis" class="external-link" target="_blank">Redis</a>, etc.

Usando imagens de contêiner pré-prontas é muito fácil **combinar** e usar diferentes ferramentas. Por exemplo, para testar um novo banco de dados. Em muitos casos, você pode usar as **imagens oficiais**, precisando somente de variáveis de ambiente para configurá-las.

}

TEST(CAPI, SavedModel) {
  // Load the saved model.
  const string saved_model_dir = tensorflow::GetDataDependencyFilepath(
      tensorflow::io::JoinPath("tensorflow", "cc", "saved_model", "testdata",
                               "half_plus_two", "00000123"));
  TF_SessionOptions* opt = TF_NewSessionOptions();
  TF_Buffer* run_options = TF_NewBufferFromString("", 0);
  TF_Buffer* metagraph = TF_NewBuffer();

	// Create a testbucket
	err = objLayer.MakeBucket(ctx, "testbucket", MakeBucketOptions{})
	if err != nil {
		t.Fatal(err)
	}

	// Unzip sample object data to the existing disks
	err = unzipArchive("testdata/xl-meta-inline-notinline.zip", path)
	if err != nil {
		t.Fatal(err)
	}

	// Try to read the object and check its md5sum

	// create xlStorage test setup
	xlStorage, _, err := newXLStorageTestSetup(t)
	if err != nil {
		t.Fatalf("Unable to cfgreate xlStorage test setup, %s", err)
	}

	xlMeta, _ := os.ReadFile("testdata/xl.meta")
	fi, _ := getFileInfo(xlMeta, "exists", "as-file", "", fileInfoOpts{Data: false})

	// Create files for the test cases.
	if err = xlStorage.MakeVol(t.Context(), "exists"); err != nil {

		}
		rec = httptest.NewRecorder()
		apiRouter.ServeHTTP(rec, reqC)
		checkRespErr(rec, http.StatusOK)
	}
}

// unzip a file into a specific target dir - used to unzip sample data in cmd/testdata/
func unzipArchive(zipFilePath, targetDir string) error {
	zipReader, err := zip.OpenReader(zipFilePath)
	if err != nil {
		return err
	}
	for _, file := range zipReader.File {