Add schema evolution to s3.to_csv

awswrangler/s3/_write.py

@@ -99,3 +99,20 @@ def _sanitize(
     dtype = {catalog.sanitize_column_name(k): v.lower() for k, v in dtype.items()}
     _utils.check_duplicated_columns(df=df)
     return df, dtype, partition_cols
+
+
+def _check_schema_changes(columns_types: Dict[str, str], table_input: Optional[Dict[str, Any]], mode: str) -> None:
+    if (table_input is not None) and (mode in ("append", "overwrite_partitions")):
+        catalog_cols: Dict[str, str] = {x["Name"]: x["Type"] for x in table_input["StorageDescriptor"]["Columns"]}
+        for c, t in columns_types.items():
+            if c not in catalog_cols:
+                raise exceptions.InvalidArgumentValue(
+                    f"Schema change detected: New column {c} with type {t}. "
+                    "Please pass schema_evolution=True to allow new columns "
+                    "behaviour."
+                )
+            if t != catalog_cols[c]:  # Data type change detected!
+                raise exceptions.InvalidArgumentValue(
+                    f"Schema change detected: Data type change on column {c} "
+                    f"(Old type: {catalog_cols[c]} / New type {t})."
+                )

awswrangler/s3/_write_parquet.py

@@ -17,30 +17,13 @@
 from awswrangler.s3._delete import delete_objects
 from awswrangler.s3._fs import open_s3_object
 from awswrangler.s3._read_parquet import _read_parquet_metadata
-from awswrangler.s3._write import _COMPRESSION_2_EXT, _apply_dtype, _sanitize, _validate_args
+from awswrangler.s3._write import _COMPRESSION_2_EXT, _apply_dtype, _check_schema_changes, _sanitize, _validate_args
 from awswrangler.s3._write_concurrent import _WriteProxy
 from awswrangler.s3._write_dataset import _to_dataset
 
 _logger: logging.Logger = logging.getLogger(__name__)
 
 
-def _check_schema_changes(columns_types: Dict[str, str], table_input: Optional[Dict[str, Any]], mode: str) -> None:
-    if (table_input is not None) and (mode in ("append", "overwrite_partitions")):
-        catalog_cols: Dict[str, str] = {x["Name"]: x["Type"] for x in table_input["StorageDescriptor"]["Columns"]}
-        for c, t in columns_types.items():
-            if c not in catalog_cols:
-                raise exceptions.InvalidArgumentValue(
-                    f"Schema change detected: New column {c} with type {t}. "
-                    "Please pass schema_evolution=True to allow new columns "
-                    "behaviour."
-                )
-            if t != catalog_cols[c]:  # Data type change detected!
-                raise exceptions.InvalidArgumentValue(
-                    f"Schema change detected: Data type change on column {c} "
-                    f"(Old type: {catalog_cols[c]} / New type {t})."
-                )
-
-
 def _get_file_path(file_counter: int, file_path: str) -> str:
     slash_index: int = file_path.rfind("/")
     dot_index: int = file_path.find(".", slash_index)

awswrangler/s3/_write_text.py

@@ -14,7 +14,7 @@
 from awswrangler._config import apply_configs
 from awswrangler.s3._delete import delete_objects
 from awswrangler.s3._fs import open_s3_object
-from awswrangler.s3._write import _COMPRESSION_2_EXT, _apply_dtype, _sanitize, _validate_args
+from awswrangler.s3._write import _COMPRESSION_2_EXT, _apply_dtype, _check_schema_changes, _sanitize, _validate_args
 from awswrangler.s3._write_dataset import _to_dataset
 
 _logger: logging.Logger = logging.getLogger(__name__)
@@ -87,6 +87,7 @@ def to_csv(  # pylint: disable=too-many-arguments,too-many-locals,too-many-state
     concurrent_partitioning: bool = False,
     mode: Optional[str] = None,
     catalog_versioning: bool = False,
+    schema_evolution: bool = False,
     database: Optional[str] = None,
     table: Optional[str] = None,
     dtype: Optional[Dict[str, str]] = None,
@@ -182,6 +183,11 @@ def to_csv(  # pylint: disable=too-many-arguments,too-many-locals,too-many-state
         https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.s3.to_parquet.html#awswrangler.s3.to_parquet
     catalog_versioning : bool
         If True and `mode="overwrite"`, creates an archived version of the table catalog before updating it.
+    schema_evolution : bool
+        If True allows schema evolution (new or missing columns), otherwise a exception will be raised.
+        (Only considered if dataset=True and mode in ("append", "overwrite_partitions"))
+        Related tutorial:
+        https://aws-data-wrangler.readthedocs.io/en/2.9.0/tutorials/014%20-%20Schema%20Evolution.html
     database : str, optional
         Glue/Athena catalog: Database name.
     table : str, optional
@@ -474,6 +480,16 @@ def to_csv(  # pylint: disable=too-many-arguments,too-many-locals,too-many-state
             pd_kwargs.pop("compression", None)
 
         df = df[columns] if columns else df
+
+        columns_types: Dict[str, str] = {}
+        partitions_types: Dict[str, str] = {}
+        if (database is not None) and (table is not None):
+            columns_types, partitions_types = _data_types.athena_types_from_pandas_partitioned(
+                df=df, index=index, partition_cols=partition_cols, dtype=dtype, index_left=True
+            )
+            if schema_evolution is False:
+                _check_schema_changes(columns_types=columns_types, table_input=catalog_table_input, mode=mode)
+
         paths, partitions_values = _to_dataset(
             func=_to_text,
             concurrent_partitioning=concurrent_partitioning,
@@ -498,9 +514,6 @@ def to_csv(  # pylint: disable=too-many-arguments,too-many-locals,too-many-state
         )
         if database and table:
             try:
-                columns_types, partitions_types = _data_types.athena_types_from_pandas_partitioned(
-                    df=df, index=index, partition_cols=partition_cols, dtype=dtype, index_left=True
-                )
                 serde_info: Dict[str, Any] = {}
                 if catalog_table_input:
                     serde_info = catalog_table_input["StorageDescriptor"]["SerdeInfo"]

tests/test_s3_text.py

@@ -331,3 +331,14 @@ def test_read_csv_versioned(path) -> None:
         df_temp = wr.s3.read_csv(path_file, version_id=version_id)
         assert df_temp.equals(df)
         assert version_id == wr.s3.describe_objects(path=path_file, version_id=version_id)[path_file]["VersionId"]
+
+
+def test_to_csv_schema_evolution(path, glue_database, glue_table) -> None:
+    path_file = f"{path}0.csv"
+    df = pd.DataFrame({"c0": [0, 1, 2], "c1": [3, 4, 5]})
+    wr.s3.to_csv(df=df, path=path_file, dataset=True, database=glue_database, table=glue_table)
+    df["test"] = 1
+    with pytest.raises(wr.exceptions.InvalidArgumentValue):
+        wr.s3.to_csv(
+            df=df, path=path_file, dataset=True, database=glue_database, table=glue_table, schema_evolution=True
+        )