improved error handling when no target column is passed

folktexts/acs/acs_tasks.py

@@ -51,14 +51,7 @@ def make_task(
         description: str = None,
         folktables_obj: BasicProblem = None,
     ) -> ACSTaskMetadata:
-        # Validate columns mappings exist
-        if not all(col in acs_columns_map for col in (features + [target])):
-            missing_cols = {col for col in (features + [target]) if col not in acs_columns_map}
-            raise ValueError(
-                f"Not all columns have mappings to textual descriptions. "
-                f"Missing columns: {missing_cols}."
-            )
-
+        """Create an ACS task object from the given parameters."""
         # Resolve target column name
         target_col_name = (
             target_threshold.apply_to_column_name(target)

folktexts/dataset.py

@@ -62,7 +62,9 @@ def __init__(
                 f"Expected `TaskMetadata`.")
 
         # Validate data for this task
-        self._check_task_columns_are_in_df(task, data)
+        task.check_task_columns_are_available(
+            available_cols=data.columns.to_list()
+        )
 
         self._test_size = test_size
         self._val_size = val_size or 0
@@ -83,27 +85,16 @@ def __init__(
         if subsampling is not None:
             self.subsample(subsampling)
 
-    @staticmethod
-    def _check_task_columns_are_in_df(task: TaskMetadata, df: pd.DataFrame, raise_: bool = True) -> bool:
-        available_cols = df.columns
-        required_cols = task.features + ([task.get_target()] if task.target else [])
-
-        if raise_ and not all(col in available_cols for col in required_cols):
-            raise ValueError(
-                f"The following required task columns were not found in the dataset: "
-                f"{list(set(required_cols) - set(available_cols))};"
-            )
-
-        return all(col in available_cols for col in required_cols)
-
     @property
     def data(self) -> pd.DataFrame:
         return self._data
 
     @data.setter
-    def data(self, new_data) -> pd.DataFrame:
+    def data(self, new_data: pd.DataFrame) -> pd.DataFrame:
         # Check if task columns are in the data
-        self._check_task_columns_are_in_df(self.task, new_data)
+        self.task.check_task_columns_are_available(
+            new_data.columns.to_list()
+        )
 
         # Update data
         self._data = new_data
@@ -127,8 +118,9 @@ def task(self) -> TaskMetadata:
     @task.setter
     def task(self, new_task: TaskMetadata):
         # Check if task columns are in the data
-        self._check_task_columns_are_in_df(new_task, self.data)
-
+        new_task.check_task_columns_are_available(
+            self.data.columns.to_list()
+        )
         self._task = new_task
 
     @property

folktexts/task.py

@@ -60,6 +60,9 @@ def __post_init__(self):
         # Add this task to the class-level dictionary
         TaskMetadata._tasks[self.name] = self
 
+        # Check all required columns are provided by the `cols_to_text` map
+        self.check_task_columns_are_available(self.cols_to_text.keys())
+
         # Check target is provided
         if self.target is None:
             logging.warning(
@@ -92,6 +95,37 @@ def __hash__(self) -> int:
         hashable_params["question_hash"] = hash(self.question)
         return int(hash_dict(hashable_params), 16)
 
+    def check_task_columns_are_available(
+        self,
+        available_cols: list[str],
+        raise_: bool = True,
+    ) -> bool:
+        """Checks if all columns required by this task are available.
+
+        Parameters
+        ----------
+        available_cols : list[str]
+            The list of column names available in the dataset.
+        raise_ : bool, optional
+            Whether to raise an error if some columns are missing, by default True.
+
+        Returns
+        -------
+        all_available : bool
+            True if all required columns are present in the given list of
+            available columns, False otherwise.
+        """
+        required_cols = self.features + ([self.get_target()] if self.target else [])
+        missing_cols = set(required_cols) - set(available_cols)
+
+        if raise_ and len(missing_cols) > 0:
+            raise ValueError(
+                f"The following required task columns were not found in the dataset: "
+                f"{list(missing_cols)};"
+            )
+
+        return len(missing_cols) == 0   # Return True if all columns are present
+
     def get_target(self) -> str:
         """Resolves the name of the target column depending on `self.target_threshold`."""
         if self.target is None: