add validation for ignore_attributes and default_target_attribute at …

openml/datasets/functions.py

@@ -333,6 +333,29 @@ def _load_features_from_file(features_file: str) -> Dict:
         return xml_dict["oml:data_features"]
 
 
+def _expand_parameter(parameter: Union[str, List[str]]) -> List[str]:
+    expanded_parameter = []
+    if isinstance(parameter, str):
+        expanded_parameter = [x.strip() for x in parameter.split(",")]
+    elif isinstance(parameter, list):
+        expanded_parameter = parameter
+    return expanded_parameter
+
+
+def _validated_data_attributes(
+    attributes: List[str], data_attributes: List[str], parameter_name: str
+) -> None:
+    for attribute_ in attributes:
+        is_attribute_a_data_attribute = any([attr[0] == attribute_ for attr in data_attributes])
+        if not is_attribute_a_data_attribute:
+            raise ValueError(
+                "all attribute of '{}' should be one of the data attribute. "
+                " Got '{}' while candidates are {}.".format(
+                    parameter_name, attribute_, [attr[0] for attr in data_attributes]
+                )
+            )
+
+
 def check_datasets_active(
     dataset_ids: List[int],
     raise_error_if_not_exist: bool = True,
@@ -646,6 +669,7 @@ def create_dataset(
     ignore_attribute : str | list
         Attributes that should be excluded in modelling,
         such as identifiers and indexes.
+        Can have multiple values, comma separated.
     citation : str
         Reference(s) that should be cited when building on this data.
     version_label : str, optional
@@ -697,6 +721,11 @@ def create_dataset(
                     attributes_[attr_idx] = (attr_name, attributes[attr_name])
     else:
         attributes_ = attributes
+    ignore_attributes = _expand_parameter(ignore_attribute)
+    _validated_data_attributes(ignore_attributes, attributes_, "ignore_attribute")
+
+    default_target_attributes = _expand_parameter(default_target_attribute)
+    _validated_data_attributes(default_target_attributes, attributes_, "default_target_attribute")
 
     if row_id_attribute is not None:
         is_row_id_an_attribute = any([attr[0] == row_id_attribute for attr in attributes_])

tests/test_datasets/test_dataset_functions.py

@@ -901,7 +901,6 @@ def test_create_dataset_pandas(self):
         collection_date = "01-01-2018"
         language = "English"
         licence = "MIT"
-        default_target_attribute = "play"
         citation = "None"
         original_data_url = "http://openml.github.io/openml-python"
         paper_url = "http://openml.github.io/openml-python"
@@ -913,7 +912,7 @@ def test_create_dataset_pandas(self):
             collection_date=collection_date,
             language=language,
             licence=licence,
-            default_target_attribute=default_target_attribute,
+            default_target_attribute="play",
             row_id_attribute=None,
             ignore_attribute=None,
             citation=citation,
@@ -948,7 +947,7 @@ def test_create_dataset_pandas(self):
             collection_date=collection_date,
             language=language,
             licence=licence,
-            default_target_attribute=default_target_attribute,
+            default_target_attribute="y",
             row_id_attribute=None,
             ignore_attribute=None,
             citation=citation,
@@ -984,7 +983,7 @@ def test_create_dataset_pandas(self):
             collection_date=collection_date,
             language=language,
             licence=licence,
-            default_target_attribute=default_target_attribute,
+            default_target_attribute="rnd_str",
             row_id_attribute=None,
             ignore_attribute=None,
             citation=citation,
@@ -1420,3 +1419,118 @@ def test_data_fork(self):
         self.assertRaisesRegex(
             OpenMLServerException, "Unknown dataset", fork_dataset, data_id=999999,
         )
+
+
+@pytest.mark.parametrize(
+    "default_target_attribute,row_id_attribute,ignore_attribute",
+    [
+        ("wrong", None, None),
+        (None, "wrong", None),
+        (None, None, "wrong"),
+        ("wrong,sunny", None, None),
+        (None, None, "wrong,sunny"),
+        (["wrong", "sunny"], None, None),
+        (None, None, ["wrong", "sunny"]),
+    ],
+)
+def test_invalid_attribute_validations(
+    default_target_attribute, row_id_attribute, ignore_attribute
+):
+    data = [
+        ["a", "sunny", 85.0, 85.0, "FALSE", "no"],
+        ["b", "sunny", 80.0, 90.0, "TRUE", "no"],
+        ["c", "overcast", 83.0, 86.0, "FALSE", "yes"],
+        ["d", "rainy", 70.0, 96.0, "FALSE", "yes"],
+        ["e", "rainy", 68.0, 80.0, "FALSE", "yes"],
+    ]
+    column_names = ["rnd_str", "outlook", "temperature", "humidity", "windy", "play"]
+    df = pd.DataFrame(data, columns=column_names)
+    # enforce the type of each column
+    df["outlook"] = df["outlook"].astype("category")
+    df["windy"] = df["windy"].astype("bool")
+    df["play"] = df["play"].astype("category")
+    # meta-information
+    name = "pandas_testing_dataset"
+    description = "Synthetic dataset created from a Pandas DataFrame"
+    creator = "OpenML tester"
+    collection_date = "01-01-2018"
+    language = "English"
+    licence = "MIT"
+    citation = "None"
+    original_data_url = "http://openml.github.io/openml-python"
+    paper_url = "http://openml.github.io/openml-python"
+    with pytest.raises(ValueError, match="should be one of the data attribute"):
+        _ = openml.datasets.functions.create_dataset(
+            name=name,
+            description=description,
+            creator=creator,
+            contributor=None,
+            collection_date=collection_date,
+            language=language,
+            licence=licence,
+            default_target_attribute=default_target_attribute,
+            row_id_attribute=row_id_attribute,
+            ignore_attribute=ignore_attribute,
+            citation=citation,
+            attributes="auto",
+            data=df,
+            version_label="test",
+            original_data_url=original_data_url,
+            paper_url=paper_url,
+        )
+
+
+@pytest.mark.parametrize(
+    "default_target_attribute,row_id_attribute,ignore_attribute",
+    [
+        ("outlook", None, None),
+        (None, "outlook", None),
+        (None, None, "outlook"),
+        ("outlook,windy", None, None),
+        (None, None, "outlook,windy"),
+        (["outlook", "windy"], None, None),
+        (None, None, ["outlook", "windy"]),
+    ],
+)
+def test_valid_attribute_validations(default_target_attribute, row_id_attribute, ignore_attribute):
+    data = [
+        ["a", "sunny", 85.0, 85.0, "FALSE", "no"],
+        ["b", "sunny", 80.0, 90.0, "TRUE", "no"],
+        ["c", "overcast", 83.0, 86.0, "FALSE", "yes"],
+        ["d", "rainy", 70.0, 96.0, "FALSE", "yes"],
+        ["e", "rainy", 68.0, 80.0, "FALSE", "yes"],
+    ]
+    column_names = ["rnd_str", "outlook", "temperature", "humidity", "windy", "play"]
+    df = pd.DataFrame(data, columns=column_names)
+    # enforce the type of each column
+    df["outlook"] = df["outlook"].astype("category")
+    df["windy"] = df["windy"].astype("bool")
+    df["play"] = df["play"].astype("category")
+    # meta-information
+    name = "pandas_testing_dataset"
+    description = "Synthetic dataset created from a Pandas DataFrame"
+    creator = "OpenML tester"
+    collection_date = "01-01-2018"
+    language = "English"
+    licence = "MIT"
+    citation = "None"
+    original_data_url = "http://openml.github.io/openml-python"
+    paper_url = "http://openml.github.io/openml-python"
+    _ = openml.datasets.functions.create_dataset(
+        name=name,
+        description=description,
+        creator=creator,
+        contributor=None,
+        collection_date=collection_date,
+        language=language,
+        licence=licence,
+        default_target_attribute=default_target_attribute,
+        row_id_attribute=row_id_attribute,
+        ignore_attribute=ignore_attribute,
+        citation=citation,
+        attributes="auto",
+        data=df,
+        version_label="test",
+        original_data_url=original_data_url,
+        paper_url=paper_url,
+    )