# Buggy code
def slots_stats(
    *,
    lock_rows: bool = False,
    session: Session = None,
) -> Dict[str, PoolStats]:
    """
    Get Pool stats (Number of Running, Queued, Open & Total tasks)

    If ``lock_rows`` is True, and the database engine in use supports the ``NOWAIT`` syntax, then a
    non-blocking lock will be attempted -- if the lock is not available then SQLAlchemy will throw an
    OperationalError.

    :param lock_rows: Should we attempt to obtain a row-level lock on all the Pool rows returns
    :param session: SQLAlchemy ORM Session
    """
    from airflow.models.taskinstance import TaskInstance  # Avoid circular import

    pools: Dict[str, PoolStats] = {}

    query = session.query(Pool.pool, Pool.slots)

    if lock_rows:
        query = with_row_locks(query, **nowait(session))

    pool_rows: Iterable[Tuple[str, int]] = query.all()
    for pool_name, total_slots in pool_rows:
        pools[pool_name] = PoolStats(total=total_slots, running=0, queued=0, open=0)

    state_count_by_pool = (
        session.query(TaskInstance.pool, TaskInstance.state, func.count())
        .filter(TaskInstance.state.in_(list(EXECUTION_STATES)))
        .group_by(TaskInstance.pool, TaskInstance.state)
    ).all()

    # calculate queued and running metrics
    count: int
    for pool_name, state, count in state_count_by_pool:
        stats_dict: Optional[PoolStats] = pools.get(pool_name)
        if not stats_dict:
            continue
        # TypedDict key must be a string literal, so we use if-statements to set value
        if state == "running":
            stats_dict["running"] = count
        elif state == "queued":
            stats_dict["queued"] = count
        else:
            raise AirflowException(
                f"Unexpected state. Expected values: {EXECUTION_STATES}."
            )

    # calculate open metric
    for pool_name, stats_dict in pools.items():
        if stats_dict["total"] == -1:
            # -1 means infinite
            stats_dict["open"] = -1
        else:
            stats_dict["open"] = (
                stats_dict["total"] - stats_dict["running"] - stats_dict["queued"]
            )

    return pools


# Traceback (_mysql_exceptions.OperationalError)
[2020-10-26 09:03:54,608] {{settings.py:49}} INFO - Configured default timezone Timezone('UTC')
[2020-10-26 09:04:05,467] {{scheduler_job.py:1327}} ERROR - Exception when executing SchedulerJob._run_scheduler_loop
Traceback (most recent call last):
File "/home/airflow/.local/lib/python3.8/site-packages/sqlalchemy/engine/base.py", line 1277, in _execute_context
self.dialect.do_execute(
File "/home/airflow/.local/lib/python3.8/site-packages/sqlalchemy/engine/default.py", line 593, in do_execute
cursor.execute(statement, parameters)
File "/home/airflow/.local/lib/python3.8/site-packages/MySQLdb/cursors.py", line 255, in execute
self.errorhandler(self, exc, value)
File "/home/airflow/.local/lib/python3.8/site-packages/MySQLdb/connections.py", line 50, in defaulterrorhandler
raise errorvalue
File "/home/airflow/.local/lib/python3.8/site-packages/MySQLdb/cursors.py", line 252, in execute
res = self._query(query)
File "/home/airflow/.local/lib/python3.8/site-packages/MySQLdb/cursors.py", line 379, in _query
self._do_get_result(db)
File "/home/airflow/.local/lib/python3.8/site-packages/MySQLdb/cursors.py", line 182, in _do_get_result
self._result = result = self._get_result()
File "/home/airflow/.local/lib/python3.8/site-packages/MySQLdb/cursors.py", line 411, in _get_result
return self._get_db().store_result()
_mysql_exceptions.OperationalError: (1213, 'Deadlock found when trying to get lock; try restarting transaction')

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
File "/home/airflow/.local/lib/python3.8/site-packages/airflow/jobs/scheduler_job.py", line 1308, in _execute
self._run_scheduler_loop()
File "/home/airflow/.local/lib/python3.8/site-packages/airflow/jobs/scheduler_job.py", line 1379, in _run_scheduler_loop
num_queued_tis = self._do_scheduling(session)
File "/home/airflow/.local/lib/python3.8/site-packages/airflow/jobs/scheduler_job.py", line 1451, in _do_scheduling
self._create_dag_runs(query.all(), session)
File "/home/airflow/.local/lib/python3.8/site-packages/sqlalchemy/orm/query.py", line 3341, in all
return list(self)
File "/home/airflow/.local/lib/python3.8/site-packages/sqlalchemy/orm/query.py", line 3503, in __iter__
return self._execute_and_instances(context)
File "/home/airflow/.local/lib/python3.8/site-packages/sqlalchemy/orm/query.py", line 3528, in _execute_and_instances
result = conn.execute(querycontext.statement, self._params)
File "/home/airflow/.local/lib/python3.8/site-packages/sqlalchemy/engine/base.py", line 1014, in execute
return meth(self, multiparams, params)
File "/home/airflow/.local/lib/python3.8/site-packages/sqlalchemy/sql/elements.py", line 298, in _execute_on_connection
return connection._execute_clauseelement(self, multiparams, params)
File "/home/airflow/.local/lib/python3.8/site-packages/sqlalchemy/engine/base.py", line 1127, in _execute_clauseelement
ret = self._execute_context(
File "/home/airflow/.local/lib/python3.8/site-packages/sqlalchemy/engine/base.py", line 1317, in _execute_context
self._handle_dbapi_exception(
File "/home/airflow/.local/lib/python3.8/site-packages/sqlalchemy/engine/base.py", line 1511, in _handle_dbapi_exception
util.raise_(
File "/home/airflow/.local/lib/python3.8/site-packages/sqlalchemy/util/compat.py", line 178, in raise_
raise exception
File "/home/airflow/.local/lib/python3.8/site-packages/sqlalchemy/engine/base.py", line 1277, in _execute_context
self.dialect.do_execute(
File "/home/airflow/.local/lib/python3.8/site-packages/sqlalchemy/engine/default.py", line 593, in do_execute
cursor.execute(statement, parameters)
File "/home/airflow/.local/lib/python3.8/site-packages/MySQLdb/cursors.py", line 255, in execute
self.errorhandler(self, exc, value)
File "/home/airflow/.local/lib/python3.8/site-packages/MySQLdb/connections.py", line 50, in defaulterrorhandler
raise errorvalue
File "/home/airflow/.local/lib/python3.8/site-packages/MySQLdb/cursors.py", line 252, in execute
res = self._query(query)
File "/home/airflow/.local/lib/python3.8/site-packages/MySQLdb/cursors.py", line 379, in _query
self._do_get_result(db)
File "/home/airflow/.local/lib/python3.8/site-packages/MySQLdb/cursors.py", line 182, in _do_get_result
self._result = result = self._get_result()
File "/home/airflow/.local/lib/python3.8/site-packages/MySQLdb/cursors.py", line 411, in _get_result
return self._get_db().store_result()
sqlalchemy.exc.OperationalError: (_mysql_exceptions.OperationalError) (1213, 'Deadlock found when trying to get lock; try restarting transaction')
[SQL: SELECT dag.dag_id AS dag_dag_id, dag.root_dag_id AS dag_root_dag_id, dag.is_paused AS dag_is_paused, dag.is_subdag AS dag_is_subdag, dag.is_active AS dag_is_active, dag.last_scheduler_run AS dag_last_scheduler_run, dag.last_pickled AS dag_last_pickled, dag.last_expired AS dag_last_expired, dag.scheduler_lock AS dag_scheduler_lock, dag.pickle_id AS dag_pickle_id, dag.fileloc AS dag_fileloc, dag.owners AS dag_owners, dag.description AS dag_description, dag.default_view AS dag_default_view, dag.schedule_interval AS dag_schedule_interval, dag.concurrency AS dag_concurrency, dag.has_task_concurrency_limits AS dag_has_task_concurrency_limits, dag.next_dagrun AS dag_next_dagrun, dag.next_dagrun_create_after AS dag_next_dagrun_create_after
FROM dag
WHERE dag.is_paused IS false AND dag.is_active IS true AND dag.next_dagrun_create_after <= now() ORDER BY dag.next_dagrun_create_after
LIMIT %s FOR UPDATE]
[parameters: (10,)]
(Background on this error at: http://sqlalche.me/e/13/e3q8)
[2020-10-26 09:04:06,512] {{process_utils.py:102}} INFO - Sending Signals.SIGTERM to GPID 7437
[2020-10-26 09:04:07,029] {{process_utils.py:68}} INFO - Process psutil.Process(pid=7762, status='terminated', started='09:04:05') (7762) terminated with exit code None
[2020-10-26 09:04:07,122] {{process_utils.py:219}} INFO - Waiting up to 5 seconds for processes to exit...
[2020-10-26 09:04:07,126] {{process_utils.py:68}} INFO - Process psutil.Process(pid=7774, status='terminated', started='09:04:05') (7774) terminated with exit code None
[2020-10-26 09:04:07,128] {{process_utils.py:68}} INFO - Process psutil.Process(pid=7437, status='terminated', exitcode=0, started='09:03:54') (7437) terminated with exit code 0
[2020-10-26 09:04:07,128] {{process_utils.py:68}} INFO - Process psutil.Process(pid=7775, status='terminated', started='09:04:05') (7775) terminated with exit code None
[2020-10-26 09:04:07,129] {{process_utils.py:68}} INFO - Process psutil.Process(pid=7773, status='terminated', started='09:04:05') (7773) terminated with exit code None
[2020-10-26 09:04:07,129] {{process_utils.py:68}} INFO - Process psutil.Process(pid=7782, status='terminated', started='09:04:05') (7782) terminated with exit code None

# Fixed code
def slots_stats(
    *,
    lock_rows: bool = False,
    session: Session = None,
) -> Dict[str, PoolStats]:
    """
    Get Pool stats (Number of Running, Queued, Open & Total tasks)

    If ``lock_rows`` is True, and the database engine in use supports the ``NOWAIT`` syntax, then a
    non-blocking lock will be attempted -- if the lock is not available then SQLAlchemy will throw an
    OperationalError.

    :param lock_rows: Should we attempt to obtain a row-level lock on all the Pool rows returns
    :param session: SQLAlchemy ORM Session
    """
    from airflow.models.taskinstance import TaskInstance  # Avoid circular import

    pools: Dict[str, PoolStats] = {}

    query = session.query(Pool.pool, Pool.slots)

    if lock_rows:
        query = with_row_locks(query, session=session, **nowait(session))

    pool_rows: Iterable[Tuple[str, int]] = query.all()
    for pool_name, total_slots in pool_rows:
        pools[pool_name] = PoolStats(total=total_slots, running=0, queued=0, open=0)

    state_count_by_pool = (
        session.query(TaskInstance.pool, TaskInstance.state, func.count())
        .filter(TaskInstance.state.in_(list(EXECUTION_STATES)))
        .group_by(TaskInstance.pool, TaskInstance.state)
    ).all()

    # calculate queued and running metrics
    count: int
    for pool_name, state, count in state_count_by_pool:
        stats_dict: Optional[PoolStats] = pools.get(pool_name)
        if not stats_dict:
            continue
        # TypedDict key must be a string literal, so we use if-statements to set value
        if state == "running":
            stats_dict["running"] = count
        elif state == "queued":
            stats_dict["queued"] = count
        else:
            raise AirflowException(
                f"Unexpected state. Expected values: {EXECUTION_STATES}."
            )

    # calculate open metric
    for pool_name, stats_dict in pools.items():
        if stats_dict["total"] == -1:
            # -1 means infinite
            stats_dict["open"] = -1
        else:
            stats_dict["open"] = (
                stats_dict["total"] - stats_dict["running"] - stats_dict["queued"]
            )

    return pools