Add rows processor to GenericTransfer

[dabla]

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This PR extends the GenericTransfer operator with a rows_processor parameter, similar to SQLInsertRowsOperator.
The rows_processor allows users to post-process rows returned by the source hook before they are inserted into the destination hook.

This enables lightweight transformations (filtering, normalization, enrichment, etc.) without introducing an intermediate task, while keeping database-specific type handling encapsulated in the hook itself.

def rows_processor(rows, **context):
    # Example: normalize string values before insertion
    return [
        tuple(value.strip() if isinstance(value, str) else value for value in row)
        for row in rows
    ]

GenericTransfer(
    task_id="transfer_data",
    source_conn_id="source_db",
    destination_conn_id="target_db",
    sql="SELECT id, name FROM source_table",
    destination_table="target_table",
    rows_processor=rows_processor,
)

In addition, this PR makes SQLExecuteQueryTrigger non-blocking when running on Airflow 3.2 or higher.

Previously, the trigger had to remain blocking due to a bug in the CommsDecoder that could raise a “Response read out of order” error when handling asynchronous trigger events. With this issue fixed in Airflow 3.2, the trigger can now safely run in a non-blocking mode, improving triggerer scalability and resource usage.

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[Nataneljpwd]

Looks great, I have left a few comments and questions, mainly nitpicks

[Nataneljpwd]

Looks great!
Only 1 question regarding the python interface file

[dabla]

Looks great! Only 1 question regarding the python interface file

Thx for to review @Nataneljpwd, really appreciated, well done! I think I've fixed all issues, awaiting CI/CD now.

[Nataneljpwd]

Looks great, 1 minor nitpick for type hinting, other than that, looks great

[Nataneljpwd]

Looks great! just need to make the CI pass

[dabla]

@Nataneljpwd thx for the review and helping fixing the mypy issues!

[Nataneljpwd]

Everything looks amazing, nice work!