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The following commit(s) were added to refs/heads/main by this push:
new 1f1cbec33eb Fix remaining mypy issues in amazon provider (#58950)
1f1cbec33eb is described below
commit 1f1cbec33eb8f59ab520818caf1ad68b763c5e7e
Author: Jarek Potiuk <[email protected]>
AuthorDate: Tue Dec 2 18:32:57 2025 +0100
Fix remaining mypy issues in amazon provider (#58950)
---
.../amazon/src/airflow/providers/amazon/aws/transfers/sql_to_s3.py | 6 +++---
1 file changed, 3 insertions(+), 3 deletions(-)
diff --git
a/providers/amazon/src/airflow/providers/amazon/aws/transfers/sql_to_s3.py
b/providers/amazon/src/airflow/providers/amazon/aws/transfers/sql_to_s3.py
index 41ffc111b4d..6a073561e84 100644
--- a/providers/amazon/src/airflow/providers/amazon/aws/transfers/sql_to_s3.py
+++ b/providers/amazon/src/airflow/providers/amazon/aws/transfers/sql_to_s3.py
@@ -191,7 +191,7 @@ class SqlToS3Operator(BaseOperator):
if df[col].dtype.name == "object" and file_format ==
FILE_FORMAT.PARQUET:
# if the type wasn't identified or converted, change it to a
string so if can still be
# processed.
- df[col] = cast("pd.Series", df[col].astype(str))
+ df[col] = cast("pd.Series", df[col].astype(str)) # type:
ignore[call-overload]
if "float" in df[col].dtype.name and df[col].hasnans:
# inspect values to determine if dtype of non-null values is
int or float
@@ -201,13 +201,13 @@ class SqlToS3Operator(BaseOperator):
# The type ignore can be removed here if
https://github.com/numpy/numpy/pull/23690
# is merged and released as currently NumPy does not
consider None as valid for x/y.
df[col] = np.where(df[col].isnull(), None, df[col]) #
type: ignore[call-overload]
- df[col] = cast("pd.Series",
df[col].astype(pd.Int64Dtype()))
+ df[col] = cast("pd.Series",
df[col].astype(pd.Int64Dtype())) # type: ignore[call-overload]
elif np.isclose(notna_series, notna_series.astype(int)).all():
# set to float dtype that retains floats and supports NaNs
# The type ignore can be removed here if
https://github.com/numpy/numpy/pull/23690
# is merged and released
df[col] = np.where(df[col].isnull(), None, df[col]) #
type: ignore[call-overload]
- df[col] = cast("pd.Series",
df[col].astype(pd.Float64Dtype()))
+ df[col] = cast("pd.Series",
df[col].astype(pd.Float64Dtype())) # type: ignore[call-overload]
@staticmethod
def _strip_suffixes(
