[python-package] convert string concatenation to f-strings in test_engine.py (fixes #4136)

tests/python_package_test/test_engine.py

@@ -819,11 +819,11 @@ def test_feature_name():
  X_train, y_train = load_boston(return_X_y=True)
  params = {'verbose': -1}
  lgb_train = lgb.Dataset(X_train, y_train)
- feature_names = ['f_' + str(i) for i in range(X_train.shape[-1])]
+ feature_names = [f'f_{i}' for i in range(X_train.shape[-1])]
  gbm = lgb.train(params, lgb_train, num_boost_round=5, feature_name=feature_names)
  assert feature_names == gbm.feature_name()
  # test feature_names with whitespaces
- feature_names_with_space = ['f ' + str(i) for i in range(X_train.shape[-1])]
+ feature_names_with_space = [f'f {i}' for i in range(X_train.shape[-1])]
  gbm = lgb.train(params, lgb_train, num_boost_round=5, feature_name=feature_names_with_space)
  assert feature_names == gbm.feature_name()
 
@@ -2021,12 +2021,12 @@ def test_model_size():
  multiplier = 100
  total_trees = multiplier + 2
  try:
- new_model_str = (model_str[:model_str.find('tree_sizes')]
-  + '\n\n'
-  + model_str[model_str.find('Tree=0'):model_str.find('end of trees')]
-  + (one_tree * multiplier).format(*range(2, total_trees))
-  + model_str[model_str.find('end of trees'):]
-  + ' ' * (2**31 - one_tree_size * total_trees))
+ before_tree_sizes = model_str[:model_str.find('tree_sizes')]
+ trees = model_str[model_str.find('Tree=0'):model_str.find('end of trees')]
+ more_trees = (one_tree * multiplier).format(*range(2, total_trees))
+ after_trees = model_str[model_str.find('end of trees'):]
+ num_end_spaces = 2**31 - one_tree_size * total_trees
+ new_model_str = f"{before_tree_sizes}\n\n{trees}{more_trees}{after_trees}{'':{num_end_spaces}}"
  assert len(new_model_str) > 2**31
  bst.model_from_string(new_model_str, verbose=False)
  assert bst.num_trees() == total_trees
@@ -2398,10 +2398,13 @@ def test_dataset_update_params():
  for key, value in unchangeable_params.items():
  new_params = default_params.copy()
  new_params[key] = value
+ if key != "forcedbins_filename":
+ param_name = key
+ else:
+ param_name = "forced bins"
  err_msg = ("Reducing `min_data_in_leaf` with `feature_pre_filter=true` may cause *"
  if key == "min_data_in_leaf"
- else "Cannot change {} *".format(key if key != "forcedbins_filename"
- else "forced bins"))
+ else f"Cannot change {param_name} *")
  with np.testing.assert_raises_regex(lgb.basic.LightGBMError, err_msg):
  lgb.train(new_params, lgb_data, num_boost_round=3)
 
@@ -2460,7 +2463,7 @@ def test_trees_to_dataframe():
  pytest.importorskip("pandas")
 
  def _imptcs_to_numpy(X, impcts_dict):
- cols = ['Column_' + str(i) for i in range(X.shape[1])]
+ cols = [f'Column_{i}' for i in range(X.shape[1])]
  return [impcts_dict.get(col, 0.) for col in cols]
 
  X, y = load_breast_cancer(return_X_y=True)