### Overview
Some Executors, currently a subset of the local Executors, run in a single threaded fashion and have certain limitations and requirements, many of which are hardcoded. To add a new single threaded Executor would require changes to core Airflow code.
Note: This coupling often shows up with SQLite compatibility checks since it does not support multiple connections.
### Examples
- **2a**) SQLite check done in configuration.py: https://github.com/apache/airflow/blob/26f94c5370587f73ebd935cecf208c6a36bdf9b6/airflow/configuration.py#L412-L419
- **2b**) When running in standalone mode SQLite compatibility is checked: https://github.com/apache/airflow/blob/26f94c5370587f73ebd935cecf208c6a36bdf9b6/airflow/cli/commands/standalone_command.py#L160-L165
- **2c**) Sensors in `poke` mode can block execution of DAGs when running with single process Executors, currently hardcoded to DebugExecutor (although should also include SequentialExecutor): https://github.com/apache/airflow/blob/27e2101f6ee5567b2843cbccf1dca0b0e7c96186/airflow/sensors/base.py#L243
### Proposal
A static method or attribute on the Executor class which can be checked by core code.

There is a precedent already set with the `supports_ad_hoc_ti_run` attribute, see:
https://github.com/apache/airflow/blob/fb741fd87254e235f99d7d67e558dafad601f253/airflow/executors/kubernetes_executor.py#L435 https://github.com/apache/airflow/blob/26f94c5370587f73ebd935cecf208c6a36bdf9b6/airflow/www/views.py#L1735-L1737
"""Function defined by the sensors while deriving this class should override."""
        raise AirflowException("Override me.")
    def execute(self, context: Context) -> Any:
        started_at: datetime.datetime | float
        if self.reschedule:
            
            
            first_try_number = context["ti"].max_tries - self.retries + 1
            task_reschedules = TaskReschedule.find_for_task_instance(
                context["ti"], try_number=first_try_number
            )
            if not task_reschedules:
                start_date = timezone.utcnow()
            else:
                start_date = task_reschedules[0].start_date
            started_at = start_date
            def run_duration() -> float:
                
                
                return (timezone.utcnow() - start_date).total_seconds()
        else:
            started_at = start_monotonic = time.monotonic()
            def run_duration() -> float: