[ci] prevent train.binary.bin and lgb_train_data.bin files being …

…left behind after testing (#6606)

Co-authored-by: Nikita Titov <[email protected]>

tests/c_api_test/test_.py

@@ -160,7 +160,7 @@ def free_dataset(handle):
     LIB.LGBM_DatasetFree(handle)
 
 
-def test_dataset():
+def test_dataset(tmp_path):
     binary_example_dir = Path(__file__).absolute().parents[2] / "examples" / "binary_classification"
     train = load_from_file(binary_example_dir / "binary.train", None)
     test = load_from_mat(binary_example_dir / "binary.test", train)
@@ -169,9 +169,10 @@ def test_dataset():
     free_dataset(test)
     test = load_from_csc(binary_example_dir / "binary.test", train)
     free_dataset(test)
-    save_to_binary(train, "train.binary.bin")
+    train_binary = str(tmp_path / "train.binary.bin")
+    save_to_binary(train, train_binary)
     free_dataset(train)
-    train = load_from_file("train.binary.bin", None)
+    train = load_from_file(train_binary, None)
     free_dataset(train)
 
 

tests/python_package_test/test_engine.py

@@ -2021,7 +2021,7 @@ def train_and_get_predictions(features, labels):
     np.testing.assert_allclose(origin_pred, sliced_pred)
 
 
-def test_init_with_subset(rng):
+def test_init_with_subset(tmp_path, rng):
     data = rng.uniform(size=(50, 2))
     y = [1] * 25 + [0] * 25
     lgb_train = lgb.Dataset(data, y, free_raw_data=False)
@@ -2035,16 +2035,17 @@ def test_init_with_subset(rng):
     assert lgb_train.get_data().shape[0] == 50
     assert subset_data_1.get_data().shape[0] == 30
     assert subset_data_2.get_data().shape[0] == 20
-    lgb_train.save_binary("lgb_train_data.bin")
-    lgb_train_from_file = lgb.Dataset("lgb_train_data.bin", free_raw_data=False)
+    lgb_train_data = str(tmp_path / "lgb_train_data.bin")
+    lgb_train.save_binary(lgb_train_data)
+    lgb_train_from_file = lgb.Dataset(lgb_train_data, free_raw_data=False)
     subset_data_3 = lgb_train_from_file.subset(subset_index_1)
     subset_data_4 = lgb_train_from_file.subset(subset_index_2)
     init_gbm_2 = lgb.train(params=params, train_set=subset_data_3, num_boost_round=10, keep_training_booster=True)
     with np.testing.assert_raises_regex(lgb.basic.LightGBMError, "Unknown format of training data"):
         lgb.train(params=params, train_set=subset_data_4, num_boost_round=10, init_model=init_gbm_2)
-    assert lgb_train_from_file.get_data() == "lgb_train_data.bin"
-    assert subset_data_3.get_data() == "lgb_train_data.bin"
-    assert subset_data_4.get_data() == "lgb_train_data.bin"
+    assert lgb_train_from_file.get_data() == lgb_train_data
+    assert subset_data_3.get_data() == lgb_train_data
+    assert subset_data_4.get_data() == lgb_train_data
 
 
 def test_training_on_constructed_subset_without_params(rng):