Arrow: Remove check for supported Arrow transforms

pyiceberg/table/__init__.py

@@ -431,7 +431,9 @@ def update_schema(self, allow_incompatible_changes: bool = False, case_sensitive
             name_mapping=self.table_metadata.name_mapping(),
         )
 
-    def update_snapshot(self, snapshot_properties: Dict[str, str] = EMPTY_DICT, branch: Optional[str] = None) -> UpdateSnapshot:
+    def update_snapshot(
+        self, snapshot_properties: Dict[str, str] = EMPTY_DICT, branch: Optional[str] = MAIN_BRANCH
+    ) -> UpdateSnapshot:
         """Create a new UpdateSnapshot to produce a new snapshot for the table.
 
         Returns:
@@ -470,12 +472,6 @@ def append(self, df: pa.Table, snapshot_properties: Dict[str, str] = EMPTY_DICT,
         if not isinstance(df, pa.Table):
             raise ValueError(f"Expected PyArrow table, got: {df}")
 
-        if unsupported_partitions := [
-            field for field in self.table_metadata.spec().fields if not field.transform.supports_pyarrow_transform
-        ]:
-            raise ValueError(
-                f"Not all partition types are supported for writes. Following partitions cannot be written using pyarrow: {unsupported_partitions}."
-            )
         downcast_ns_timestamp_to_us = Config().get_bool(DOWNCAST_NS_TIMESTAMP_TO_US_ON_WRITE) or False
         _check_pyarrow_schema_compatible(
             self.table_metadata.schema(),
@@ -592,12 +588,6 @@ def overwrite(
         if not isinstance(df, pa.Table):
             raise ValueError(f"Expected PyArrow table, got: {df}")
 
-        if unsupported_partitions := [
-            field for field in self.table_metadata.spec().fields if not field.transform.supports_pyarrow_transform
-        ]:
-            raise ValueError(
-                f"Not all partition types are supported for writes. Following partitions cannot be written using pyarrow: {unsupported_partitions}."
-            )
         downcast_ns_timestamp_to_us = Config().get_bool(DOWNCAST_NS_TIMESTAMP_TO_US_ON_WRITE) or False
         _check_pyarrow_schema_compatible(
             self.table_metadata.schema(),

pyiceberg/transforms.py

@@ -212,10 +212,6 @@ def __eq__(self, other: Any) -> bool:
             return self.root == other.root
         return False
 
-    @property
-    def supports_pyarrow_transform(self) -> bool:
-        return False
-
     @abstractmethod
     def pyarrow_transform(self, source: IcebergType) -> "Callable[[pa.Array], pa.Array]": ...
 
@@ -399,10 +395,6 @@ def pyarrow_transform(self, source: IcebergType) -> "Callable[[pa.Array], pa.Arr
         pyiceberg_core_transform = _try_import("pyiceberg_core", extras_name="pyiceberg-core").transform
         return _pyiceberg_transform_wrapper(pyiceberg_core_transform.bucket, self._num_buckets)
 
-    @property
-    def supports_pyarrow_transform(self) -> bool:
-        return True
-
 
 class TimeResolution(IntEnum):
     YEAR = 6
@@ -462,10 +454,6 @@ def dedup_name(self) -> str:
     def preserves_order(self) -> bool:
         return True
 
-    @property
-    def supports_pyarrow_transform(self) -> bool:
-        return True
-
 
 class YearTransform(TimeTransform[S]):
     """Transforms a datetime value into a year value.
@@ -781,10 +769,6 @@ def __repr__(self) -> str:
     def pyarrow_transform(self, source: IcebergType) -> "Callable[[pa.Array], pa.Array]":
         return lambda v: v
 
-    @property
-    def supports_pyarrow_transform(self) -> bool:
-        return True
-
 
 class TruncateTransform(Transform[S, S]):
     """A transform for truncating a value to a specified width.
@@ -931,10 +915,6 @@ def pyarrow_transform(self, source: IcebergType) -> "Callable[[pa.Array], pa.Arr
 
         return _pyiceberg_transform_wrapper(pyiceberg_core_transform.truncate, self._width)
 
-    @property
-    def supports_pyarrow_transform(self) -> bool:
-        return True
-
 
 @singledispatch
 def _human_string(value: Any, _type: IcebergType) -> str:
@@ -1049,7 +1029,12 @@ def __repr__(self) -> str:
         return "VoidTransform()"
 
     def pyarrow_transform(self, source: IcebergType) -> "Callable[[pa.Array], pa.Array]":
-        raise NotImplementedError()
+        try:
+            import pyarrow as pa
+        except ModuleNotFoundError as e:
+            raise ModuleNotFoundError("For partition transforms, PyArrow needs to be installed") from e
+
+        return lambda arr: pa.nulls(len(arr), type=arr.type)
 
 
 def _truncate_number(

tests/test_transforms.py

@@ -1655,6 +1655,12 @@ def test_bucket_pyarrow_transforms(
     assert expected == transform.pyarrow_transform(source_type)(input_arr)
 
 
+def test_bucket_pyarrow_void_transform() -> None:
+    input_arr = pa.chunked_array([pa.array([1, 2], type=pa.int32()), pa.array([3, 4], type=pa.int32())])
+    output_arr = pa.array([None, None, None, None], type=pa.int32())
+    assert output_arr == VoidTransform().pyarrow_transform(IntegerType())(input_arr)
+
+
 @pytest.mark.parametrize(
     "source_type, input_arr, expected, width",
     [