Addressed minor comments

Author: soumya-ghosh

pyiceberg/io/pyarrow.py

@@ -2144,7 +2144,7 @@ def _dataframe_to_data_files(
 
 
 @dataclass(frozen=True)
-class TablePartition:
+class _TablePartition:
     partition_key: PartitionKey
     arrow_table_partition: pa.Table
 
@@ -2154,7 +2154,7 @@ def _get_table_partitions(
     partition_spec: PartitionSpec,
     schema: Schema,
     slice_instructions: list[dict[str, Any]],
-) -> list[TablePartition]:
+) -> list[_TablePartition]:
     sorted_slice_instructions = sorted(slice_instructions, key=lambda x: x["offset"])
 
     partition_fields = partition_spec.fields
@@ -2175,11 +2175,11 @@ def _get_table_partitions(
             for partition_field in partition_fields
         ]
         partition_key = PartitionKey(raw_partition_field_values=fieldvalues, partition_spec=partition_spec, schema=schema)
-        table_partitions.append(TablePartition(partition_key=partition_key, arrow_table_partition=partition_slice))
+        table_partitions.append(_TablePartition(partition_key=partition_key, arrow_table_partition=partition_slice))
     return table_partitions
 
 
-def _determine_partitions(spec: PartitionSpec, schema: Schema, arrow_table: pa.Table) -> List[TablePartition]:
+def _determine_partitions(spec: PartitionSpec, schema: Schema, arrow_table: pa.Table) -> List[_TablePartition]:
     """Based on the iceberg table partition spec, slice the arrow table into partitions with their keys.
 
     Example:
@@ -2235,6 +2235,6 @@ def _determine_partitions(spec: PartitionSpec, schema: Schema, arrow_table: pa.T
         last = reversed_indices[ptr]
         ptr = ptr + group_size
 
-    table_partitions: List[TablePartition] = _get_table_partitions(arrow_table, spec, schema, slice_instructions)
+    table_partitions: List[_TablePartition] = _get_table_partitions(arrow_table, spec, schema, slice_instructions)
 
     return table_partitions

tests/io/test_pyarrow.py

@@ -1723,8 +1723,6 @@ def test_bin_pack_arrow_table(arrow_table_with_null: pa.Table) -> None:
 
 
 def test_partition_for_demo() -> None:
-    import pyarrow as pa
-
     test_pa_schema = pa.schema([("year", pa.int64()), ("n_legs", pa.int64()), ("animal", pa.string())])
     test_schema = Schema(
         NestedField(field_id=1, name="year", field_type=StringType(), required=False),
@@ -1757,8 +1755,6 @@ def test_partition_for_demo() -> None:
 
 
 def test_identity_partition_on_multi_columns() -> None:
-    import pyarrow as pa
-
     test_pa_schema = pa.schema([("born_year", pa.int64()), ("n_legs", pa.int64()), ("animal", pa.string())])
     test_schema = Schema(
         NestedField(field_id=1, name="born_year", field_type=StringType(), required=False),