code: def test_create_backtesting_folds_no_refit_no_gap_allow_incomplete_fold_False(
      capfd, return_all_indexes, expected
  ):
      """
      Test _create_backtesting_folds output when refit is 0 (False), gap=0,
      remainder and allow_incomplete_fold=False.
      """
      y = pd.Series(np.arange(100))
      y.index = pd.date_range(start="2022-01-01", periods=100, freq="D")
      window_size = 4
      initial_train_size = 65
      test_size = 10
      refit = 0
      allow_incomplete_fold = False
  
      folds = _create_backtesting_folds(
          data=y,
          window_size=window_size,
          initial_train_size=initial_train_size,
          test_size=test_size,
          externally_fitted=False,
          refit=refit,
          fixed_train_size=False,
          gap=0,
          allow_incomplete_fold=allow_incomplete_fold,
          return_all_indexes=return_all_indexes,
          verbose=True,
      )
  
      out, _ = capfd.readouterr()
      expected_out = (
          "Information of backtesting process\n"
          "----------------------------------\n"
          "Number of observations used for initial training: 65\n"
          "Number of observations used for backtesting: 35\n"
          "    Number of folds: 3\n"
          "    Number of steps per fold: 10\n"
          "    Number of steps to exclude from the end of each train set before test (gap): 0\n"
          "    Last fold has been excluded because it was incomplete.\n\n"
          "Fold: 0\n"
          "    Training:   2022-01-01 00:00:00 -- 2022-03-06 00:00:00  (n=65)\n"
          "    Validation: 2022-03-07 00:00:00 -- 2022-03-16 00:00:00  (n=10)\n"
          "Fold: 1\n"
          "    Training:   2022-01-01 00:00:00 -- 2022-03-06 00:00:00  (n=65)\n"
          "    Validation: 2022-03-17 00:00:00 -- 2022-03-26 00:00:00  (n=10)\n"
          "Fold: 2\n"
          "    Training:   2022-01-01 00:00:00 -- 2022-03-06 00:00:00  (n=65)\n"
          "    Validation: 2022-03-27 00:00:00 -- 2022-04-05 00:00:00  (n=10)\n\n"
      )
  
      assert out == expected_out
      assert folds == expected
  
imports: import pytest
  import numpy
  import pandas
  from skforecast.model_selection.model_selection import _create_backtesting_folds
label_desc: Use image node_id 2 for calling a global function with example usage: test_create_backtesting_folds_no_refit_no_gap_allow_incomplete_fold_False(capfd, return_all_indexes, expected) without return types