start adding tests of pyarrow normalizer

tests/libs/pyarrow/test_pyarrow_normalizer.py

@@ -1,4 +1,58 @@
+from typing import List, Any
+
 import pyarrow as pa
 
+from dlt.common.libs.pyarrow import normalize_py_arrow_schema
+from dlt.common.normalizers import explicit_normalizers, import_normalizers
+from dlt.common.schema.utils import new_column, TColumnSchema
+from dlt.common.destination import DestinationCapabilitiesContext
+
+
+def _normalize(table: pa.Table, columns: List[TColumnSchema]) -> pa.Table:
+    _, naming, _ = import_normalizers(explicit_normalizers())
+    caps = DestinationCapabilitiesContext()
+    columns_schema = {c["name"]: c for c in columns}
+    return normalize_py_arrow_schema(table, columns_schema, naming, caps)
+
+
+def _row_at_index(table: pa.Table, index: int) -> List[Any]:
+    return [table.column(column_name)[0].as_py() for column_name in table.column_names]
+
+
+def test_quick_return_if_nothing_to_do() -> None:
+    table = pa.Table.from_pylist(
+        [
+            {"a": 1, "b": 2},
+        ]
+    )
+    columns = [new_column("a", "bigint"), new_column("b", "bigint")]
+    result = _normalize(table, columns)
+    # same object returned
+    assert result == table
+
+
+def test_pyarrow_reorder_columns() -> None:
+    table = pa.Table.from_pylist(
+        [
+            {"col_new": "hello", "col1": 1, "col2": "a"},
+        ]
+    )
+    columns = [new_column("col2", "text"), new_column("col1", "bigint")]
+    result = _normalize(table, columns)
+    # new columns appear at the end
+    assert result.column_names == ["col2", "col1", "col_new"]
+    assert _row_at_index(result, 0) == ["a", 1, "hello"]
+
 
-from dlt.common.libs.pyarrow import py_arrow_to_table_schema_columns, get_py_arrow_datatype
+def test_pyarrow_add_empty_types() -> None:
+    table = pa.Table.from_pylist(
+        [
+            {"col1": 1},
+        ]
+    )
+    columns = [new_column("col1", "bigint"), new_column("col2", "text")]
+    result = _normalize(table, columns)
+    # new columns appear at the end
+    assert result.column_names == ["col1", "col2"]
+    assert _row_at_index(result, 0) == [1, None]
+    assert result.schema.field(1).type == "string"