Hi Song, I agree that this is not ideal, but it is difficult to do otherwise without parsing/executing the Python code.
Note that an import from airflow should be enough, or DAG in a comment. I think we are open to other solutions, if anyone on the list has better ideas. Best, Arthur On Thu, May 10, 2018 at 12:59 AM Song Liu <song...@outlook.com> wrote: > Hi, > > I just create a custom Dag class naming such as "MyPipeline" by extending > the "DAG" class, but Airflow is failed to identify this is a DAG file. > > After digging into the Airflow implementation around the dag_processing.py > file: > > ``` > # Heuristic that guesses whether a Python file contains an # Airflow DAG > definition. might_contain_dag = True if safe_mode and not > zipfile.is_zipfile(file_path): with open(file_path, 'rb') as f: content = > f.read() might_contain_dag = all( [s in content for s in (b'DAG', > b'airflow')]) > ``` > > So if the keyword "DAG" and "airflow" contained, it is a DAG file. > > I don't know is there any other be more scientific way for this ? > > Thanks, > Song >
