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fix: data_api uuid typehint #2961

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merged 7 commits into from
Sep 30, 2024
Merged

fix: data_api uuid typehint #2961

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12c97f9
fix data_api uuid typehint
jethroguce Sep 14, 2024
e2cb532
Merge branch 'main' into main
jaidisido Sep 16, 2024
798a52d
Merge branch 'main' into main
jaidisido Sep 30, 2024
4b0686e
tests: add uuid case to unit test
jaidisido Sep 30, 2024
6e2a5dd
fix: sort deps correctly
jaidisido Sep 30, 2024
eb1f2ed
Merge branch 'main' into main
jaidisido Sep 30, 2024
9766691
Merge branch 'main' into main
jaidisido Sep 30, 2024
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3 changes: 3 additions & 0 deletions awswrangler/data_api/rds.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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.")


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6 changes: 4 additions & 2 deletions tests/unit/test_data_api.py
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Original file line number Diff line number Diff line change
@@ -1,5 +1,6 @@
from __future__ import annotations

import uuid
from typing import Any, Iterator

import boto3
Expand Down Expand Up @@ -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,
Expand All @@ -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)
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