Replace tmpdir with tmp_path (mlflow#8603)

* Replace tmpdir with tmp_path

Signed-off-by: harupy <hkawamura0130@gmail.com>

* Replace more tmpdirs

Signed-off-by: harupy <hkawamura0130@gmail.com>

* Fix tracking_uri_mock

Signed-off-by: harupy <hkawamura0130@gmail.com>

* Replace tmpdir with tmp_path

Signed-off-by: harupy <hkawamura0130@gmail.com>

---------

Signed-off-by: harupy <hkawamura0130@gmail.com>

tests/autologging/test_autologging_behaviors_integration.py

@@ -238,10 +238,10 @@ def mlflow_autolog():
 
 
 @pytest.mark.usefixtures(test_mode_off.__name__)
-def test_autolog_respects_silent_mode(tmpdir):
+def test_autolog_respects_silent_mode(tmp_path):
     # Use file-based experiment storage for this test. Otherwise, concurrent experiment creation in
     # multithreaded contexts may fail for other storage backends (e.g. SQLAlchemy)
-    mlflow.set_tracking_uri(str(tmpdir))
+    mlflow.set_tracking_uri(str(tmp_path))
     mlflow.set_experiment("test_experiment")
 
     og_showwarning = warnings.showwarning

tests/catboost/test_catboost_model_export.py

@@ -78,13 +78,13 @@ def reg_model():
 
 
 @pytest.fixture
-def model_path(tmpdir):
-    return tmpdir.join("model").strpath
+def model_path(tmp_path):
+    return os.path.join(tmp_path, "model")
 
 
 @pytest.fixture
-def custom_env(tmpdir):
-    conda_env_path = os.path.join(tmpdir.strpath, "conda_env.yml")
+def custom_env(tmp_path):
+    conda_env_path = os.path.join(tmp_path, "conda_env.yml")
     _mlflow_conda_env(conda_env_path, additional_pip_deps=["catboost", "pytest"])
     return conda_env_path
 
@@ -211,11 +211,11 @@ def test_model_load_from_remote_uri_succeeds(reg_model, model_path, mock_s3_buck
     )
 
 
-def test_log_model(cb_model, tmpdir):
+def test_log_model(cb_model, tmp_path):
     model, inference_dataframe = cb_model
     with mlflow.start_run():
         artifact_path = "model"
-        conda_env = os.path.join(tmpdir.strpath, "conda_env.yaml")
+        conda_env = os.path.join(tmp_path, "conda_env.yaml")
         _mlflow_conda_env(conda_env, additional_pip_deps=["catboost"])
 
         model_info = mlflow.catboost.log_model(model, artifact_path, conda_env=conda_env)
@@ -236,11 +236,11 @@ def test_log_model(cb_model, tmpdir):
         assert os.path.exists(os.path.join(local_path, env_path))
 
 
-def test_log_model_calls_register_model(cb_model, tmpdir):
+def test_log_model_calls_register_model(cb_model, tmp_path):
     artifact_path = "model"
     registered_model_name = "registered_model"
     with mlflow.start_run() as run, mock.patch("mlflow.register_model") as register_model_mock:
-        conda_env_path = os.path.join(tmpdir.strpath, "conda_env.yaml")
+        conda_env_path = os.path.join(tmp_path, "conda_env.yaml")
         _mlflow_conda_env(conda_env_path, additional_pip_deps=["catboost"])
         mlflow.catboost.log_model(
             cb_model.model,
@@ -254,10 +254,10 @@ def test_log_model_calls_register_model(cb_model, tmpdir):
         )
 
 
-def test_log_model_no_registered_model_name(cb_model, tmpdir):
+def test_log_model_no_registered_model_name(cb_model, tmp_path):
     with mlflow.start_run(), mock.patch("mlflow.register_model") as register_model_mock:
         artifact_path = "model"
-        conda_env_path = os.path.join(tmpdir.strpath, "conda_env.yaml")
+        conda_env_path = os.path.join(tmp_path, "conda_env.yaml")
         _mlflow_conda_env(conda_env_path, additional_pip_deps=["catboost"])
         mlflow.catboost.log_model(cb_model.model, artifact_path, conda_env=conda_env_path)
         register_model_mock.assert_not_called()

tests/conftest.py

@@ -29,13 +29,13 @@ def set_mock(obj, attr, mock):
 
 
 @pytest.fixture(autouse=True)
-def tracking_uri_mock(tmpdir, request):
+def tracking_uri_mock(tmp_path, request):
     try:
         if "notrackingurimock" not in request.keywords:
-            tracking_uri = path_to_local_sqlite_uri(os.path.join(tmpdir.strpath, "mlruns.sqlite"))
+            tracking_uri = path_to_local_sqlite_uri(os.path.join(tmp_path, "mlruns.sqlite"))
             mlflow.set_tracking_uri(tracking_uri)
             os.environ["MLFLOW_TRACKING_URI"] = tracking_uri
-        yield tmpdir
+        yield str(tmp_path)
     finally:
         mlflow.set_tracking_uri(None)
         if "notrackingurimock" not in request.keywords:

tests/evaluate/test_evaluation.py

@@ -1133,7 +1133,7 @@ def test_evaluate_env_manager_params(multiclass_logistic_regressor_model_uri, ir
 
 
 @pytest.mark.parametrize("env_manager", ["virtualenv", "conda"])
-def test_evaluate_restores_env(tmpdir, env_manager, iris_dataset):
+def test_evaluate_restores_env(tmp_path, env_manager, iris_dataset):
     class EnvRestoringTestModel(mlflow.pyfunc.PythonModel):
         def __init__(self):
             pass
@@ -1154,7 +1154,7 @@ def evaluate(self, *, model, model_type, dataset, run_id, evaluator_config, **kw
             y = model.predict(pd.DataFrame(dataset.features_data))
             return EvaluationResult(metrics={"test": y[0]}, artifacts={})
 
-    model_path = os.path.join(str(tmpdir), "model")
+    model_path = os.path.join(tmp_path, "model")
 
     mlflow.pyfunc.save_model(
         path=model_path,

tests/fastai/test_fastai_model_export.py

@@ -50,13 +50,13 @@ def fastai_model():
 
 
 @pytest.fixture
-def model_path(tmpdir):
-    return os.path.join(str(tmpdir), "model")
+def model_path(tmp_path):
+    return os.path.join(tmp_path, "model")
 
 
 @pytest.fixture
-def fastai_custom_env(tmpdir):
-    conda_env = os.path.join(str(tmpdir), "conda_env.yml")
+def fastai_custom_env(tmp_path):
+    conda_env = os.path.join(tmp_path, "conda_env.yml")
     _mlflow_conda_env(conda_env, additional_pip_deps=["fastai", "pytest"])
     return conda_env
 

tests/gluon/test_gluon_model_export.py

@@ -46,13 +46,13 @@
 
 
 @pytest.fixture
-def model_path(tmpdir):
-    return os.path.join(tmpdir.strpath, "model")
+def model_path(tmp_path):
+    return os.path.join(tmp_path, "model")
 
 
 @pytest.fixture
-def gluon_custom_env(tmpdir):
-    conda_env = os.path.join(str(tmpdir), "conda_env.yml")
+def gluon_custom_env(tmp_path):
+    conda_env = os.path.join(tmp_path, "conda_env.yml")
     _mlflow_conda_env(conda_env, additional_pip_deps=["mxnet", "pytest"])
     return conda_env
 

tests/h2o/test_h2o_model_export.py

@@ -54,13 +54,13 @@ def h2o_iris_model():
 
 
 @pytest.fixture
-def model_path(tmpdir):
-    return os.path.join(str(tmpdir), "model")
+def model_path(tmp_path):
+    return os.path.join(tmp_path, "model")
 
 
 @pytest.fixture
-def h2o_custom_env(tmpdir):
-    conda_env = os.path.join(str(tmpdir), "conda_env.yml")
+def h2o_custom_env(tmp_path):
+    conda_env = os.path.join(tmp_path, "conda_env.yml")
     _mlflow_conda_env(conda_env, additional_pip_deps=["h2o", "pytest"])
     return conda_env
 

tests/lightgbm/test_lightgbm_model_export.py

@@ -67,13 +67,13 @@ def lgb_sklearn_model():
 
 
 @pytest.fixture
-def model_path(tmpdir):
-    return os.path.join(str(tmpdir), "model")
+def model_path(tmp_path):
+    return os.path.join(tmp_path, "model")
 
 
 @pytest.fixture
-def lgb_custom_env(tmpdir):
-    conda_env = os.path.join(str(tmpdir), "conda_env.yml")
+def lgb_custom_env(tmp_path):
+    conda_env = os.path.join(tmp_path, "conda_env.yml")
     _mlflow_conda_env(conda_env, additional_pip_deps=["lightgbm", "pytest"])
     return conda_env
 

tests/models/test_model.py

@@ -394,8 +394,8 @@ def test_model_uuid():
     assert m4.model_uuid is None
 
 
-def test_validate_schema(sklearn_knn_model, iris_data, tmpdir):
-    sk_model_path = os.path.join(str(tmpdir), "sk_model")
+def test_validate_schema(sklearn_knn_model, iris_data, tmp_path):
+    sk_model_path = os.path.join(tmp_path, "sk_model")
     X, y = iris_data
     signature = infer_signature(X, y)
     mlflow.sklearn.save_model(

tests/models/test_signature.py

@@ -164,8 +164,8 @@ def test_set_signature_to_logged_model():
     assert model_info.signature == signature
 
 
-def test_set_signature_to_saved_model(tmpdir):
-    model_path = str(tmpdir)
+def test_set_signature_to_saved_model(tmp_path):
+    model_path = str(tmp_path)
     mlflow.sklearn.save_model(
         RandomForestRegressor(),
         model_path,

tests/onnx/test_onnx_model_export.py

@@ -99,8 +99,8 @@ def model(dataset):
 
 
 @pytest.fixture
-def onnx_model(model, sample_input, tmpdir):
-    model_path = os.path.join(str(tmpdir), "torch_onnx")
+def onnx_model(model, sample_input, tmp_path):
+    model_path = os.path.join(tmp_path, "torch_onnx")
     dynamic_axes = {"input": {0: "batch"}}
     torch.onnx.export(
         model, sample_input, model_path, dynamic_axes=dynamic_axes, input_names=["input"]
@@ -154,8 +154,8 @@ def multi_tensor_model_prediction(multi_tensor_model, data):
 
 
 @pytest.fixture
-def multi_tensor_onnx_model(multi_tensor_model, sample_input, tmpdir):
-    model_path = os.path.join(str(tmpdir), "multi_tensor_onnx")
+def multi_tensor_onnx_model(multi_tensor_model, sample_input, tmp_path):
+    model_path = os.path.join(tmp_path, "multi_tensor_onnx")
     _sample_input = torch.split(sample_input, 2, 1)
     torch.onnx.export(
         multi_tensor_model,
@@ -226,13 +226,13 @@ def predicted_multiple_inputs(data_multiple_inputs):
 
 
 @pytest.fixture
-def model_path(tmpdir):
-    return os.path.join(tmpdir.strpath, "model")
+def model_path(tmp_path):
+    return os.path.join(tmp_path, "model")
 
 
 @pytest.fixture
-def onnx_custom_env(tmpdir):
-    conda_env = os.path.join(str(tmpdir), "conda_env.yml")
+def onnx_custom_env(tmp_path):
+    conda_env = os.path.join(tmp_path, "conda_env.yml")
     _mlflow_conda_env(conda_env, additional_pip_deps=["onnx", "pytest", "torch"])
     return conda_env
 

tests/paddle/test_paddle_model_export.py

@@ -94,13 +94,13 @@ def forward(self, inputs):  # pylint: disable=arguments-differ
 
 
 @pytest.fixture
-def model_path(tmpdir):
-    return os.path.join(str(tmpdir), "model")
+def model_path(tmp_path):
+    return os.path.join(tmp_path, "model")
 
 
 @pytest.fixture
-def pd_custom_env(tmpdir):
-    conda_env = os.path.join(str(tmpdir), "conda_env.yml")
+def pd_custom_env(tmp_path):
+    conda_env = os.path.join(tmp_path, "conda_env.yml")
     _mlflow_conda_env(conda_env, additional_pip_deps=["paddle", "pytest"])
     return conda_env
 
@@ -141,11 +141,11 @@ def test_model_load_from_remote_uri_succeeds(pd_model, model_path, mock_s3_bucke
     )
 
 
-def test_model_log(pd_model, model_path, tmpdir):
+def test_model_log(pd_model, model_path, tmp_path):
     model = pd_model.model
     try:
         artifact_path = "model"
-        conda_env = os.path.join(tmpdir, "conda_env.yaml")
+        conda_env = os.path.join(tmp_path, "conda_env.yaml")
         _mlflow_conda_env(conda_env, additional_pip_deps=["paddle"])
 
         model_info = mlflow.paddle.log_model(
@@ -346,12 +346,12 @@ def test_model_built_in_high_level_api_load_from_remote_uri_succeeds(
     )
 
 
-def test_model_built_in_high_level_api_log(pd_model_built_in_high_level_api, model_path, tmpdir):
+def test_model_built_in_high_level_api_log(pd_model_built_in_high_level_api, model_path, tmp_path):
     model = pd_model_built_in_high_level_api.model
     test_dataset = pd_model_built_in_high_level_api.inference_dataframe
     try:
         artifact_path = "model"
-        conda_env = os.path.join(tmpdir, "conda_env.yaml")
+        conda_env = os.path.join(tmp_path, "conda_env.yaml")
         _mlflow_conda_env(conda_env, additional_pip_deps=["paddle"])
 
         mlflow.paddle.log_model(pd_model=model, artifact_path=artifact_path, conda_env=conda_env)
@@ -378,8 +378,8 @@ def test_model_built_in_high_level_api_log(pd_model_built_in_high_level_api, mod
 
 
 @pytest.fixture
-def model_retrain_path(tmpdir):
-    return os.path.join(str(tmpdir), "model_retrain")
+def model_retrain_path(tmp_path):
+    return os.path.join(tmp_path, "model_retrain")
 
 
 @pytest.mark.allow_infer_pip_requirements_fallback
@@ -432,14 +432,14 @@ def test_model_retrain_built_in_high_level_api(
 
 
 def test_log_model_built_in_high_level_api(
-    pd_model_built_in_high_level_api, model_path, tmpdir, get_dataset_built_in_high_level_api
+    pd_model_built_in_high_level_api, model_path, tmp_path, get_dataset_built_in_high_level_api
 ):
     model = pd_model_built_in_high_level_api.model
     test_dataset = get_dataset_built_in_high_level_api[1]
 
     try:
         artifact_path = "model"
-        conda_env = os.path.join(tmpdir, "conda_env.yaml")
+        conda_env = os.path.join(tmp_path, "conda_env.yaml")
         _mlflow_conda_env(conda_env, additional_pip_deps=["paddle"])
 
         mlflow.paddle.log_model(

tests/projects/test_docker_projects.py

@@ -32,7 +32,7 @@ def _build_uri(base_uri, subdirectory):
 
 @pytest.mark.parametrize("use_start_run", map(str, [0, 1]))
 def test_docker_project_execution(
-    use_start_run, tmpdir, docker_example_base_image
+    use_start_run, docker_example_base_image
 ):  # pylint: disable=unused-argument
     expected_params = {"use_start_run": use_start_run}
     submitted_run = mlflow.projects.run(
@@ -76,7 +76,7 @@ def test_docker_project_execution(
 
 
 def test_docker_project_execution_async_docker_args(
-    tmpdir, docker_example_base_image
+    docker_example_base_image,
 ):  # pylint: disable=unused-argument
     submitted_run = mlflow.projects.run(
         TEST_DOCKER_PROJECT_DIR,
@@ -106,15 +106,19 @@ def test_docker_project_execution_async_docker_args(
 )
 @mock.patch("databricks_cli.configure.provider.ProfileConfigProvider")
 def test_docker_project_tracking_uri_propagation(
-    ProfileConfigProvider, tmpdir, tracking_uri, expected_command_segment, docker_example_base_image
+    ProfileConfigProvider,
+    tmp_path,
+    tracking_uri,
+    expected_command_segment,
+    docker_example_base_image,
 ):  # pylint: disable=unused-argument
     mock_provider = mock.MagicMock()
     mock_provider.get_config.return_value = DatabricksConfig.from_password(
         "host", "user", "pass", insecure=True
     )
     ProfileConfigProvider.return_value = mock_provider
     # Create and mock local tracking directory
-    local_tracking_dir = os.path.join(tmpdir.strpath, "mlruns")
+    local_tracking_dir = os.path.join(tmp_path, "mlruns")
     if tracking_uri is None:
         tracking_uri = local_tracking_dir
     old_uri = mlflow.get_tracking_uri()

tests/projects/test_projects.py

@@ -217,7 +217,7 @@ def test_run(use_start_run):
     assert tags[MLFLOW_PROJECT_ENTRY_POINT] == "test_tracking"
 
 
-def test_run_with_parent(tmpdir):  # pylint: disable=unused-argument
+def test_run_with_parent():
     """Verify that if we are in a nested run, mlflow.projects.run() will have a parent_run_id."""
     with mlflow.start_run():
         parent_run_id = mlflow.active_run().info.run_id