feat: add FunctionalTableTransformer

src/safeds/data/tabular/transformation/__init__.py

@@ -6,6 +6,7 @@
 
 if TYPE_CHECKING:
     from ._discretizer import Discretizer
+    from ._functional_table_transformer import FunctionalTableTransformer
     from ._invertible_table_transformer import InvertibleTableTransformer
     from ._k_nearest_neighbors_imputer import KNearestNeighborsImputer
     from ._label_encoder import LabelEncoder
@@ -16,10 +17,12 @@
     from ._standard_scaler import StandardScaler
     from ._table_transformer import TableTransformer
 
+
 apipkg.initpkg(
     __name__,
     {
         "Discretizer": "._discretizer:Discretizer",
+        "FunctionalTableTransformer": "._functional_table_transformer:FunctionalTableTransformer",
         "InvertibleTableTransformer": "._invertible_table_transformer:InvertibleTableTransformer",
         "LabelEncoder": "._label_encoder:LabelEncoder",
         "OneHotEncoder": "._one_hot_encoder:OneHotEncoder",
@@ -34,6 +37,7 @@
 
 __all__ = [
     "Discretizer",
+    "FunctionalTableTransformer",
     "InvertibleTableTransformer",
     "LabelEncoder",
     "OneHotEncoder",

src/safeds/data/tabular/transformation/_functional_table_transformer.py

@@ -0,0 +1,119 @@
+from __future__ import annotations
+
+from typing import TYPE_CHECKING
+
+from safeds._utils import _structural_hash
+
+if TYPE_CHECKING:
+    from collections.abc import Callable
+
+    from safeds.data.tabular.containers import Table
+
+from ._table_transformer import TableTransformer
+
+
+class FunctionalTableTransformer(TableTransformer):
+    """
+    Learn a transformation for a set of columns in a `Table` and transform another `Table` with the same columns.
+
+    Parameters
+    ----------
+    funct:
+        The Callable that receives a table and returns a table that is to be wrapped.
+    """
+
+    # ------------------------------------------------------------------------------------------------------------------
+    # Dunder methods
+    # ------------------------------------------------------------------------------------------------------------------
+
+    def __init__(self,
+                 funct: Callable[[Table], Table],
+                 ) -> None:
+        super().__init__(None)
+        self._func = funct
+
+
+
+    def __hash__(self) -> int:
+        return _structural_hash(
+            super().__hash__(),
+            self._func,
+        )
+
+    # ------------------------------------------------------------------------------------------------------------------
+    # Properties
+    # ------------------------------------------------------------------------------------------------------------------
+
+    @property
+    def is_fitted(self) -> bool:
+        """FunctionalTableTransformer is always considered to be fitted."""
+        return True
+
+    # ------------------------------------------------------------------------------------------------------------------
+    # Learning and transformation
+    # ------------------------------------------------------------------------------------------------------------------
+
+    def fit(self, table: Table) -> FunctionalTableTransformer:   # noqa: ARG002
+        """
+        **Note:** For FunctionalTableTransformer this is a no-OP.
+
+        Parameters
+        ----------
+        table:
+            Required only to be consistent with other transformers.
+
+        Returns
+        -------
+        fitted_transformer:
+            Returns self, because this transformer is always fitted.
+
+        """
+        return self
+
+    def transform(self, table: Table) -> Table:
+        """
+        Apply the callable to a table.
+
+        **Note:** The given table is not modified.
+
+        Parameters
+        ----------
+        table:
+            The table on which on which the callable is executed.
+
+        Returns
+        -------
+        transformed_table:
+            The transformed table.
+
+        Raises
+        ------
+        Exception:
+            Raised when the wrapped callable encounters an error.
+
+        """
+        try:
+            return self._func(table)
+        except Exception as e:
+            #TODO Evaluate if switch to non-generic exception is useful, as _func can be any callable
+            raise Exception("The underlying function encountered an error") from e  # noqa: TRY002
+
+    def fit_and_transform(self, table: Table) -> tuple[FunctionalTableTransformer, Table]:
+        """
+        **Note:** For the FunctionalTableTransformer this is the same as transform().
+
+        Parameters
+        ----------
+        table:
+            The table on which the callable is to be executed.
+
+        Returns
+        -------
+        fitted_transformer:
+            Return self because the transformer is always fitted.
+        transformed_table:
+            The transformed table.
+        """
+        fitted_transformer = self
+        transformed_table = self.transform(table)
+        return fitted_transformer, transformed_table

tests/safeds/data/tabular/transformation/test_functional_table_transformer.py

@@ -0,0 +1,104 @@
+import pytest
+from safeds.data.tabular.containers import Table
+from safeds.data.tabular.transformation import FunctionalTableTransformer
+
+
+def valid_callable(table: Table) -> Table:
+    return table.remove_columns(["col1"])
+
+class TestInit:
+    def test_should_not_raise_type_error(self) -> None:
+            FunctionalTableTransformer(valid_callable)
+
+class TestFit:
+    def test_should_return_self(self) -> None:
+        table = Table(
+            {
+                "col1": [1, 2, 3],
+                "col2": [1, 2, 3],
+            },
+        )
+        transformer = FunctionalTableTransformer(valid_callable)
+        assert transformer.fit(table) is transformer
+
+class TestIsFitted:
+    def test_should_always_be_fitted(self) -> None:
+        transformer = FunctionalTableTransformer(valid_callable)
+        assert transformer.is_fitted
+
+class TestTransform:
+    def test_should_raise_generic_error_when_error_in_method(self) -> None:
+        table = Table(
+            {
+                "col2": [1, 2, 3],
+
+            },
+        )
+        transformer = FunctionalTableTransformer(valid_callable)
+        with pytest.raises(Exception, match=r"The underlying function encountered an error"):
+            transformer.transform(table)
+
+    def test_should_not_modify_original_table(self) -> None:
+        table = Table(
+            {
+                "col1": [1, 2, 3],
+                "col2": [1, 2, 3],
+
+            },
+        )
+        transformer = FunctionalTableTransformer(valid_callable)
+        transformer.transform(table)
+        assert table == Table(
+            {
+                "col1": [1, 2, 3],
+                "col2": [1, 2, 3],
+
+            },
+        )
+
+    def test_should_return_modified_table(self) -> None:
+        table = Table(
+            {
+                "col1": [1, 2, 3],
+                "col2": [1, 2, 3],
+
+            },
+        )
+        transformer = FunctionalTableTransformer(valid_callable)
+        transformed_table = transformer.transform(table)
+        assert transformed_table == Table(
+            {
+                "col2": [1, 2, 3],
+
+            },
+        )
+
+class TestFitAndTransform:
+    def test_should_return_self(self) -> None:
+        table = Table(
+            {
+                "col1": [1, 2, 3],
+                "col2": [1, 2, 3],
+
+            },
+        )
+        transformer = FunctionalTableTransformer(valid_callable)
+        assert transformer.fit_and_transform(table)[0] is transformer
+
+    def test_should_not_modify_original_table(self) -> None:
+        table = Table(
+            {
+                "col1": [1, 2, 3],
+                "col2": [1, 2, 3],
+
+            },
+        )
+        transformer = FunctionalTableTransformer(valid_callable)
+        transformer.fit_and_transform(table)
+        assert table == Table(
+            {
+                "col1": [1, 2, 3],
+                "col2": [1, 2, 3],
+
+            },
+        )