Enable all datasets to take a metadata parameter

CHANGELOG.md

@@ -2,6 +2,10 @@
 
 ## [Unreleased]
 
+### Added
+
+-   :sparkles: All datasets can now take a metadata parameter ([#625](https://github.com/Galileo-Galilei/kedro-mlflow/issues/625), [#633](https://github.com/Galileo-Galilei/kedro-mlflow/pull/633))
+
 ## [0.14.2] - 2025-02-16
 
 ### Fixed

kedro_mlflow/io/artifacts/mlflow_artifact_dataset.py

@@ -19,6 +19,7 @@ def __new__(
         run_id: str = None,
         artifact_path: str = None,
         credentials: Dict[str, Any] = None,
+        metadata: Dict[str, Any] | None = None,
     ):
         dataset_obj, dataset_args = parse_dataset_definition(config=dataset)
 
@@ -27,11 +28,12 @@ def __new__(
         # instead and since we can't modify the core package,
         # we create a subclass which inherits dynamically from the dataset class
         class MlflowArtifactDatasetChildren(dataset_obj):
-            def __init__(self, run_id, artifact_path):
+            def __init__(self, run_id, artifact_path, metadata):
                 super().__init__(**dataset_args)
                 self.run_id = run_id
                 self.artifact_path = artifact_path
                 self._logging_activated = True
+                self.metadata = metadata
 
             @property
             def _logging_activated(self):
@@ -147,7 +149,9 @@ def _load(self) -> Any:  # pragma: no cover
         )
 
         mlflow_dataset_instance = MlflowArtifactDatasetChildren(
-            run_id=run_id, artifact_path=artifact_path
+            run_id=run_id,
+            artifact_path=artifact_path,
+            metadata=metadata,
         )
         return mlflow_dataset_instance
 

kedro_mlflow/io/metrics/mlflow_abstract_metric_dataset.py

@@ -12,6 +12,7 @@ def __init__(
         run_id: str = None,
         load_args: Dict[str, Any] = None,
         save_args: Dict[str, Any] = None,
+        metadata: Dict[str, Any] | None = None,
     ):
         """Initialise MlflowMetricsHistoryDataset.
 
@@ -24,6 +25,7 @@ def __init__(
         self._load_args = load_args or {}
         self._save_args = save_args or {}
         self._logging_activated = True  # by default, logging is activated!
+        self.metadata = metadata
 
     @property
     def run_id(self) -> Union[str, None]:

kedro_mlflow/io/metrics/mlflow_metric_dataset.py

@@ -18,13 +18,14 @@ def __init__(
         run_id: str = None,
         load_args: Dict[str, Any] = None,
         save_args: Dict[str, Any] = None,
+        metadata: Dict[str, Any] | None = None,
     ):
         """Initialise MlflowMetricDataset.
         Args:
             run_id (str): The ID of the mlflow run where the metric should be logged
         """
 
-        super().__init__(key, run_id, load_args, save_args)
+        super().__init__(key, run_id, load_args, save_args, metadata)
 
         # We add an extra argument mode="overwrite" / "append" to enable logging update an existing metric
         # this is not an offical mlflow argument for log_metric, so we separate it from the others

kedro_mlflow/io/metrics/mlflow_metric_history_dataset.py

@@ -14,13 +14,14 @@ def __init__(
         run_id: str = None,
         load_args: Dict[str, Any] = None,
         save_args: Dict[str, Any] = None,
+        metadata: Dict[str, Any] | None = None,
     ):
         """Initialise MlflowMetricDataset.
         Args:
             run_id (str): The ID of the mlflow run where the metric should be logged
         """
 
-        super().__init__(key, run_id, load_args, save_args)
+        super().__init__(key, run_id, load_args, save_args, metadata)
 
     def _load(self):
         self._validate_run_id()

kedro_mlflow/io/metrics/mlflow_metrics_history_dataset.py

@@ -18,6 +18,7 @@ def __init__(
         self,
         run_id: str = None,
         prefix: Optional[str] = None,
+        metadata: Dict[str, Any] | None = None,
     ):
         """Initialise MlflowMetricsHistoryDataset.
 
@@ -28,6 +29,7 @@ def __init__(
         self._prefix = prefix
         self.run_id = run_id
         self._logging_activated = True  # by default, logging is activated!
+        self.metadata = metadata
 
     @property
     def run_id(self):

kedro_mlflow/io/models/mlflow_abstract_model_dataset.py

@@ -20,6 +20,7 @@ def __init__(
         load_args: Dict[str, Any] = None,
         save_args: Dict[str, Any] = None,
         version: Version = None,
+        metadata: Dict[str, Any] | None = None,
     ) -> None:
         """Initialize the Kedro MlflowAbstractModelDataSet.
 
@@ -39,6 +40,8 @@ def __init__(
             save_args (Dict[str, Any], optional): Arguments to `log_model`
                 function from specified `flavor`. Defaults to {}.
             version (Version, optional): Specific version to load.
+            metadata: Any arbitrary metadata.
+                This is ignored by Kedro, but may be consumed by users or external plugins.
 
         Raises:
             DatasetError: When passed `flavor` does not exist.
@@ -61,6 +64,7 @@ def __init__(
 
         self._load_args = load_args or {}
         self._save_args = save_args or {}
+        self.metadata = metadata
 
         try:
             self._mlflow_model_module

kedro_mlflow/io/models/mlflow_model_local_filesystem_dataset.py

@@ -21,6 +21,7 @@ def __init__(
         save_args: Dict[str, Any] = None,
         log_args: Dict[str, Any] = None,
         version: Version = None,
+        metadata: Dict[str, Any] | None = None,
     ) -> None:
         """Initialize the Kedro MlflowModelDataSet.
 
@@ -40,6 +41,9 @@ def __init__(
             save_args (Dict[str, Any], optional): Arguments to `save_model`
                 function from specified `flavor`. Defaults to None.
             version (Version, optional): Kedro version to use. Defaults to None.
+            metadata: Any arbitrary metadata.
+                This is ignored by Kedro, but may be consumed by users or external plugins.
+
         Raises:
             DatasetError: When passed `flavor` does not exist.
         """
@@ -50,6 +54,7 @@ def __init__(
             load_args=load_args,
             save_args=save_args,
             version=version,
+            metadata=metadata,
         )
 
     def _load(self) -> Any:

kedro_mlflow/io/models/mlflow_model_registry_dataset.py

@@ -19,6 +19,7 @@ def __init__(
         flavor: Optional[str] = "mlflow.pyfunc",
         pyfunc_workflow: Optional[str] = "python_model",
         load_args: Optional[Dict[str, Any]] = None,
+        metadata: Dict[str, Any] | None = None,
     ) -> None:
         """Initialize the Kedro MlflowModelRegistryDataset.
 
@@ -37,6 +38,8 @@ def __init__(
                 See https://www.mlflow.org/docs/latest/python_api/mlflow.pyfunc.html#workflows.
             load_args (Dict[str, Any], optional): Arguments to `load_model`
                 function from specified `flavor`. Defaults to None.
+            metadata: Any arbitrary metadata.
+                This is ignored by Kedro, but may be consumed by users or external plugins.
 
         Raises:
             DatasetError: When passed `flavor` does not exist.
@@ -48,6 +51,7 @@ def __init__(
             load_args=load_args,
             save_args={},
             version=None,
+            metadata=metadata,
         )
 
         if alias is None and stage_or_version is None:

kedro_mlflow/io/models/mlflow_model_tracking_dataset.py

@@ -19,6 +19,7 @@ def __init__(
         pyfunc_workflow: Optional[str] = None,
         load_args: Optional[Dict[str, Any]] = None,
         save_args: Optional[Dict[str, Any]] = None,
+        metadata: Dict[str, Any] | None = None,
     ) -> None:
         """Initialize the Kedro MlflowModelDataSet.
 
@@ -40,6 +41,8 @@ def __init__(
                 function from specified `flavor`. Defaults to None.
             save_args (Dict[str, Any], optional): Arguments to `log_model`
                 function from specified `flavor`. Defaults to None.
+            metadata: Any arbitrary metadata.
+                This is ignored by Kedro, but may be consumed by users or external plugins.
 
         Raises:
             DatasetError: When passed `flavor` does not exist.
@@ -51,6 +54,7 @@ def __init__(
             load_args=load_args,
             save_args=save_args,
             version=None,
+            metadata=metadata,
         )
 
         self._run_id = run_id

tests/io/artifacts/test_mlflow_artifact_dataset.py

@@ -376,3 +376,23 @@ def _describe(self):
     remote_path = (Path("artifact_dir") / filepath.name).as_posix()
     assert remote_path in run_artifacts
     assert df1.equals(mlflow_dataset.load())
+
+
+@pytest.mark.parametrize(
+    "metadata",
+    (
+        None,
+        {"description": "My awsome dataset"},
+        {"string": "bbb", "int": 0},
+    ),
+)
+def test_artifact_dataset_with_metadata(metadata):
+    mlflow_csv_dataset = MlflowArtifactDataset(
+        dataset=dict(type=CSVDataset, filepath="/my/file/path"),
+        metadata=metadata,
+    )
+
+    assert mlflow_csv_dataset.metadata == metadata
+
+    # Metadata should not show in _describe
+    assert "metadata" not in mlflow_csv_dataset._describe()

tests/io/metrics/test_mlflow_metric_dataset.py

@@ -193,3 +193,23 @@ def test_mlflow_metric_logging_deactivation_is_bool():
 
     with pytest.raises(ValueError, match="_logging_activated must be a boolean"):
         mlflow_metric_dataset._logging_activated = "hello"
+
+
+@pytest.mark.parametrize(
+    "metadata",
+    (
+        None,
+        {"description": "My awsome dataset"},
+        {"string": "bbb", "int": 0},
+    ),
+)
+def test_metric_dataset_with_metadata(tmp_path, metadata):
+    mlflow_metric_dataset = MlflowMetricDataset(
+        key="hello",
+        metadata=metadata,
+    )
+
+    assert mlflow_metric_dataset.metadata == metadata
+
+    # Metadata should not show in _describe
+    assert "metadata" not in mlflow_metric_dataset._describe()

tests/io/metrics/test_mlflow_metric_history_dataset.py

@@ -68,3 +68,23 @@ def test_mlflow_metric_history_dataset_logging_deactivation(mlflow_tracking_uri)
     with mlflow.start_run():
         metric_ds.save([0.1])
         assert metric_ds._exists() is False
+
+
+@pytest.mark.parametrize(
+    "metadata",
+    (
+        None,
+        {"description": "My awsome dataset"},
+        {"string": "bbb", "int": 0},
+    ),
+)
+def test_metric_history_dataset_with_metadata(tmp_path, metadata):
+    metric_ds = MlflowMetricHistoryDataset(
+        key="hello",
+        metadata=metadata,
+    )
+
+    assert metric_ds.metadata == metadata
+
+    # Metadata should not show in _describe
+    assert "metadata" not in metric_ds._describe()

tests/io/metrics/test_mlflow_metrics_dataset.py

@@ -189,3 +189,23 @@ def test_mlflow_metrics_logging_deactivation_is_bool():
 
     with pytest.raises(ValueError, match="_logging_activated must be a boolean"):
         mlflow_metrics_dataset._logging_activated = "hello"
+
+
+@pytest.mark.parametrize(
+    "metadata",
+    (
+        None,
+        {"description": "My awsome dataset"},
+        {"string": "bbb", "int": 0},
+    ),
+)
+def test_metrics_history_dataset_with_metadata(tmp_path, metadata):
+    mlflow_metrics_dataset = MlflowMetricsHistoryDataset(
+        prefix="hello",
+        metadata=metadata,
+    )
+
+    assert mlflow_metrics_dataset.metadata == metadata
+
+    # Metadata should not show in _describe
+    assert "metadata" not in mlflow_metrics_dataset._describe()

tests/io/models/test_mlflow_model_local_filesystem_dataset.py

@@ -193,3 +193,24 @@ def test_pyfunc_flavor_python_model_save_and_load(
     loaded_model.predict(pd.DataFrame(data=[1], columns=["a"])) == pd.DataFrame(
         data=[2], columns=["a"]
     )
+
+
+@pytest.mark.parametrize(
+    "metadata",
+    (
+        None,
+        {"description": "My awsome dataset"},
+        {"string": "bbb", "int": 0},
+    ),
+)
+def test_metrics_history_dataset_with_metadata(metadata):
+    mlflow_model_ds = MlflowModelLocalFileSystemDataset(
+        flavor="mlflow.sklearn",
+        filepath="/my/file/path",
+        metadata=metadata,
+    )
+
+    assert mlflow_model_ds.metadata == metadata
+
+    # Metadata should not show in _describe
+    assert "metadata" not in mlflow_model_ds._describe()

tests/io/models/test_mlflow_model_registry_dataset.py

@@ -156,3 +156,23 @@ def test_mlflow_model_registry_load_given_alias(tmp_path, monkeypatch):
     ml_ds = MlflowModelRegistryDataset(model_name="demo_model", alias="champion")
     loaded_model = ml_ds.load()
     assert loaded_model.metadata.run_id == runs[1]
+
+
+@pytest.mark.parametrize(
+    "metadata",
+    (
+        None,
+        {"description": "My awsome dataset"},
+        {"string": "bbb", "int": 0},
+    ),
+)
+def test_metrics_history_dataset_with_metadata(tmp_path, metadata):
+    mlflow_model_ds = MlflowModelRegistryDataset(
+        model_name="demo_model",
+        metadata=metadata,
+    )
+
+    assert mlflow_model_ds.metadata == metadata
+
+    # Metadata should not show in _describe
+    assert "metadata" not in mlflow_model_ds._describe()

tests/io/models/test_mlflow_model_tracking_dataset.py

@@ -364,3 +364,23 @@ def test_mlflow_model_tracking_logging_deactivation_is_bool():
 
     with pytest.raises(ValueError, match="_logging_activated must be a boolean"):
         mlflow_model_tracking_dataset._logging_activated = "hello"
+
+
+@pytest.mark.parametrize(
+    "metadata",
+    (
+        None,
+        {"description": "My awsome dataset"},
+        {"string": "bbb", "int": 0},
+    ),
+)
+def test_metrics_history_dataset_with_metadata(metadata):
+    mlflow_model_ds = MlflowModelTrackingDataset(
+        flavor="mlflow.sklearn",
+        metadata=metadata,
+    )
+
+    assert mlflow_model_ds.metadata == metadata
+
+    # Metadata should not show in _describe
+    assert "metadata" not in mlflow_model_ds._describe()