GitHub user starkmarkus added a comment to the discussion: Airflow cli response
times
I think the traceback shows something slightly different: it does not
necessarily mean that airflow --help is already talking to the database. It
looks like Airflow initializes its settings during import and tries to parse
the configured sql_alchemy_conn in order to derive the async SQLAlchemy URI.
The important part seems to be this:
SQL_ALCHEMY_CONN_ASYNC =
_get_async_conn_uri_from_sync(sync_uri=SQL_ALCHEMY_CONN)
...
scheme, rest = sync_uri.split(":", maxsplit=1)
ValueError: not enough values to unpack
So I would first check whether AIRFLOW__DATABASE__SQL_ALCHEMY_CONN or the
corresponding airflow.cfg value is set to something invalid in that test
environment. For example, an empty value, placeholder, secret name, or
otherwise malformed value without a : would explain this error.
A quick check could be:
airflow config get-value database sql_alchemy_conn
env | grep AIRFLOW__DATABASE__SQL_ALCHEMY_CONN
or, if the CLI crashes too early:
python - <<'PY'
import os
print(repr(os.environ.get("AIRFLOW__DATABASE__SQL_ALCHEMY_CONN")))
PY
For a simple local/test setup, you could also try setting it explicitly to a
valid SQLite URL just to compare startup behavior:
export AIRFLOW__DATABASE__SQL_ALCHEMY_CONN='sqlite:////tmp/airflow.db'
time airflow --help
So my current guess would be:
1. airflow --help does import and initialize quite a bit of Airflow, so it is
not expected to be instant.
2. But this specific traceback is probably caused by an invalid database URI
configuration, not by an actual failed database connection.
3. The slow startup may still be related to the environment, filesystem,
installed packages, or import overhead, but I would fix/verify the DB URI first
before drawing conclusions from this run.
GitHub link:
https://github.com/apache/airflow/discussions/68707#discussioncomment-17367989
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