Taragolis commented on code in PR #29045:
URL: https://github.com/apache/airflow/pull/29045#discussion_r1081498187
##########
airflow/providers/amazon/aws/transfers/sql_to_s3.py:
##########
@@ -134,11 +127,23 @@ def __init__(
raise AirflowException(f"The argument file_format doesn't support
{file_format} value.")
@staticmethod
- def _fix_dtypes(df: pd.DataFrame, file_format: FILE_FORMAT) -> None:
Review Comment:
You don't need to remove this annotation.
Just add import in existed `if TYPE_CHECKING` block, everything inside it
this only evaluates on static check (mypy, etc.) and IDEs (PyCharm, VSCode,
etc.) but not in runtime.
```python
if TYPE_CHECKING:
from airflow.utils.context import Context
```
##########
airflow/providers/amazon/aws/transfers/sql_to_s3.py:
##########
@@ -134,11 +127,23 @@ def __init__(
raise AirflowException(f"The argument file_format doesn't support
{file_format} value.")
@staticmethod
- def _fix_dtypes(df: pd.DataFrame, file_format: FILE_FORMAT) -> None:
+ def _fix_dtypes(df, file_format: FILE_FORMAT) -> None:
"""
Mutate DataFrame to set dtypes for float columns containing NaN values.
Set dtype of object to str to allow for downstream transformations.
"""
+ try:
+ import numpy as np
+ from pandas import DataFrame, Float64Dtype, Int64Dtype
+ except ImportError as e:
+ from airflow.exceptions import
AirflowOptionalProviderFeatureException
+
+ raise AirflowOptionalProviderFeatureException(e)
+
+ # DataFrame type checking should be postponed because of imports order
+ if not isinstance(df, DataFrame):
+ raise TypeError('The given dataframe is not a valid pandas
DataFrame')
Review Comment:
This block could be removed as soon as we return annotations to the method.
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: commits-unsubscr...@airflow.apache.org
For queries about this service, please contact Infrastructure at:
us...@infra.apache.org
