Merge branch 'main' into fix/issue-2965-bool-config

Author: jaidisido

awswrangler/data_api/rds.py

@@ -359,6 +359,9 @@ def _create_value_dict(  # noqa: PLR0911
     if isinstance(value, Decimal):
         return {"stringValue": str(value)}, "DECIMAL"
 
+    if isinstance(value, uuid.UUID):
+        return {"stringValue": str(value)}, "UUID"
+
     raise exceptions.InvalidArgumentType(f"Value {value} not supported.")
 
 

test_infra/stacks/base_stack.py

@@ -79,6 +79,7 @@ def __init__(self, scope: Construct, construct_id: str, **kwargs: str) -> None:
                 ),
             ],
             versioned=True,
+            enforce_ssl=True,
         )
         self.bucket_access_point = s3.CfnAccessPoint(
             self,

test_infra/stacks/glueray_stack.py

@@ -21,6 +21,7 @@ def __init__(
             "Script Bucket",
             block_public_access=s3.BlockPublicAccess.BLOCK_ALL,
             removal_policy=RemovalPolicy.DESTROY,
+            enforce_ssl=True,
         )
 
         self.athena_workgroup = athena.CfnWorkGroup(

tests/unit/test_data_api.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import uuid
 from typing import Any, Iterator
 
 import boto3
@@ -284,7 +285,8 @@ def test_data_api_mysql_ansi(mysql_serverless_connector: "RdsDataApi", mysql_ser
 
 def test_data_api_postgresql(postgresql_serverless_connector: "RdsDataApi", postgresql_serverless_table: str) -> None:
     database = "test"
-    frame = pd.DataFrame([[42, "test"]], columns=["id", "name"])
+    _id = uuid.uuid4()
+    frame = pd.DataFrame([[_id, "test"]], columns=["id", "name"])
 
     wr.data_api.rds.to_sql(
         df=frame,
@@ -295,7 +297,7 @@ def test_data_api_postgresql(postgresql_serverless_connector: "RdsDataApi", post
     )
 
     out_frame = wr.data_api.rds.read_sql_query(
-        f"SELECT name FROM {postgresql_serverless_table} WHERE id = 42", con=postgresql_serverless_connector
+        f"SELECT name FROM {postgresql_serverless_table} WHERE id = '{_id}'", con=postgresql_serverless_connector
     )
     expected_dataframe = pd.DataFrame([["test"]], columns=["name"])
     assert_pandas_equals(out_frame, expected_dataframe)