[breaking] Remove support for single string feature info. (#9401)

- Input must be a sequence of strings.
- Improve validation error message.

python-package/xgboost/core.py

@@ -297,6 +297,23 @@ def _check_distributed_params(kwargs: Dict[str, Any]) -> None:
         )
 
 
+def _validate_feature_info(
+    feature_info: Sequence[str], n_features: int, name: str
+) -> List[str]:
+    if isinstance(feature_info, str) or not isinstance(feature_info, Sequence):
+        raise TypeError(
+            f"Expecting a sequence of strings for {name}, got: {type(feature_info)}"
+        )
+    feature_info = list(feature_info)
+    if len(feature_info) != n_features and n_features != 0:
+        msg = (
+            f"{name} must have the same length as the number of data columns, ",
+            f"expected {n_features}, got {len(feature_info)}",
+        )
+        raise ValueError(msg)
+    return feature_info
+
+
 def build_info() -> dict:
     """Build information of XGBoost.  The returned value format is not stable. Also,
     please note that build time dependency is not the same as runtime dependency. For
@@ -1217,11 +1234,10 @@ class DMatrix:  # pylint: disable=too-many-instance-attributes,too-many-public-m
 
     @property
     def feature_names(self) -> Optional[FeatureNames]:
-        """Get feature names (column labels).
+        """Labels for features (column labels).
+
+        Setting it to ``None`` resets existing feature names.
 
-        Returns
-        -------
-        feature_names : list or None
         """
         length = c_bst_ulong()
         sarr = ctypes.POINTER(ctypes.c_char_p)()
@@ -1240,67 +1256,61 @@ class DMatrix:  # pylint: disable=too-many-instance-attributes,too-many-public-m
 
     @feature_names.setter
     def feature_names(self, feature_names: Optional[FeatureNames]) -> None:
-        """Set feature names (column labels).
-
-        Parameters
-        ----------
-        feature_names : list or None
-            Labels for features. None will reset existing feature names
-        """
-        if feature_names is not None:
-            # validate feature name
-            try:
-                if not isinstance(feature_names, str):
-                    feature_names = list(feature_names)
-                else:
-                    feature_names = [feature_names]
-            except TypeError:
-                feature_names = [cast(str, feature_names)]
-
-            if len(feature_names) != len(set(feature_names)):
-                raise ValueError("feature_names must be unique")
-            if len(feature_names) != self.num_col() and self.num_col() != 0:
-                msg = (
-                    "feature_names must have the same length as data, ",
-                    f"expected {self.num_col()}, got {len(feature_names)}",
-                )
-                raise ValueError(msg)
-            # prohibit to use symbols may affect to parse. e.g. []<
-            if not all(
-                isinstance(f, str) and not any(x in f for x in ["[", "]", "<"])
-                for f in feature_names
-            ):
-                raise ValueError(
-                    "feature_names must be string, and may not contain [, ] or <"
-                )
-            feature_names_bytes = [bytes(f, encoding="utf-8") for f in feature_names]
-            c_feature_names = (ctypes.c_char_p * len(feature_names_bytes))(
-                *feature_names_bytes
-            )
-            _check_call(
-                _LIB.XGDMatrixSetStrFeatureInfo(
-                    self.handle,
-                    c_str("feature_name"),
-                    c_feature_names,
-                    c_bst_ulong(len(feature_names)),
-                )
-            )
-        else:
-            # reset feature_types also
+        if feature_names is None:
             _check_call(
                 _LIB.XGDMatrixSetStrFeatureInfo(
                     self.handle, c_str("feature_name"), None, c_bst_ulong(0)
                 )
             )
-            self.feature_types = None
+            return
+
+        # validate feature name
+        feature_names = _validate_feature_info(
+            feature_names, self.num_col(), "feature names"
+        )
+        if len(feature_names) != len(set(feature_names)):
+            values, counts = np.unique(
+                feature_names,
+                return_index=False,
+                return_inverse=False,
+                return_counts=True,
+            )
+            duplicates = [name for name, cnt in zip(values, counts) if cnt > 1]
+            raise ValueError(
+                f"feature_names must be unique. Duplicates found: {duplicates}"
+            )
+
+        # prohibit the use symbols that may affect parsing. e.g. []<
+        if not all(
+            isinstance(f, str) and not any(x in f for x in ["[", "]", "<"])
+            for f in feature_names
+        ):
+            raise ValueError(
+                "feature_names must be string, and may not contain [, ] or <"
+            )
+
+        feature_names_bytes = [bytes(f, encoding="utf-8") for f in feature_names]
+        c_feature_names = (ctypes.c_char_p * len(feature_names_bytes))(
+            *feature_names_bytes
+        )
+        _check_call(
+            _LIB.XGDMatrixSetStrFeatureInfo(
+                self.handle,
+                c_str("feature_name"),
+                c_feature_names,
+                c_bst_ulong(len(feature_names)),
+            )
+        )
 
     @property
     def feature_types(self) -> Optional[FeatureTypes]:
-        """Get feature types (column types).
+        """Type of features (column types).
+
+        This is for displaying the results and categorical data support. See
+        :py:class:`DMatrix` for details.
+
+        Setting it to ``None`` resets existing feature types.
 
-        Returns
-        -------
-        feature_types : list or None
         """
         length = c_bst_ulong()
         sarr = ctypes.POINTER(ctypes.c_char_p)()
@@ -1318,57 +1328,32 @@ class DMatrix:  # pylint: disable=too-many-instance-attributes,too-many-public-m
         return res
 
     @feature_types.setter
-    def feature_types(self, feature_types: Optional[Union[List[str], str]]) -> None:
-        """Set feature types (column types).
-
-        This is for displaying the results and categorical data support. See
-        :py:class:`DMatrix` for details.
-
-        Parameters
-        ----------
-        feature_types :
-            Labels for features. None will reset existing feature names
-
-        """
-        # For compatibility reason this function wraps single str input into a list.  But
-        # we should not promote such usage since other than visualization, the field is
-        # also used for specifying categorical data type.
-        if feature_types is not None:
-            if not isinstance(feature_types, (list, str)):
-                raise TypeError("feature_types must be string or list of strings")
-            if isinstance(feature_types, str):
-                # single string will be applied to all columns
-                feature_types = [feature_types] * self.num_col()
-            try:
-                if not isinstance(feature_types, str):
-                    feature_types = list(feature_types)
-                else:
-                    feature_types = [feature_types]
-            except TypeError:
-                feature_types = [cast(str, feature_types)]
-            feature_types_bytes = [bytes(f, encoding="utf-8") for f in feature_types]
-            c_feature_types = (ctypes.c_char_p * len(feature_types_bytes))(
-                *feature_types_bytes
-            )
-            _check_call(
-                _LIB.XGDMatrixSetStrFeatureInfo(
-                    self.handle,
-                    c_str("feature_type"),
-                    c_feature_types,
-                    c_bst_ulong(len(feature_types)),
-                )
-            )
-
-            if len(feature_types) != self.num_col() and self.num_col() != 0:
-                msg = "feature_types must have the same length as data"
-                raise ValueError(msg)
-        else:
-            # Reset.
+    def feature_types(self, feature_types: Optional[FeatureTypes]) -> None:
+        if feature_types is None:
+            # Reset
             _check_call(
                 _LIB.XGDMatrixSetStrFeatureInfo(
                     self.handle, c_str("feature_type"), None, c_bst_ulong(0)
                 )
             )
+            return
+
+        feature_types = _validate_feature_info(
+            feature_types, self.num_col(), "feature types"
+        )
+
+        feature_types_bytes = [bytes(f, encoding="utf-8") for f in feature_types]
+        c_feature_types = (ctypes.c_char_p * len(feature_types_bytes))(
+            *feature_types_bytes
+        )
+        _check_call(
+            _LIB.XGDMatrixSetStrFeatureInfo(
+                self.handle,
+                c_str("feature_type"),
+                c_feature_types,
+                c_bst_ulong(len(feature_types)),
+            )
+        )
 
 
 class _ProxyDMatrix(DMatrix):

tests/python/test_dmatrix.py

@@ -219,8 +219,8 @@ class TestDMatrix:
         assert dm.slice([0, 1]).num_col() == dm.num_col()
         assert dm.slice([0, 1]).feature_names == dm.feature_names
 
-        dm.feature_types = 'q'
-        assert dm.feature_types == list('qqqqq')
+        with pytest.raises(ValueError, match=r"Duplicates found: \['bar'\]"):
+            dm.feature_names = ["bar"] * (data.shape[1] - 2) + ["a", "b"]
 
         dm.feature_types = list('qiqiq')
         assert dm.feature_types == list('qiqiq')
@@ -230,6 +230,7 @@ class TestDMatrix:
 
         # reset
         dm.feature_names = None
+        dm.feature_types = None
         assert dm.feature_names is None
         assert dm.feature_types is None