### 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
"""The method is replaced by custom trigger_task implementation."""
    def sync(self) -> None:
        task_succeeded = True
        while self.tasks_to_run:
            ti = self.tasks_to_run.pop(0)
            if self.fail_fast and not task_succeeded:
                self.log.info("Setting %s to %s", ti.key, State.UPSTREAM_FAILED)
                ti.set_state(State.UPSTREAM_FAILED)
                self.change_state(ti.key, State.UPSTREAM_FAILED)
                continue
            if self._terminated.is_set():
                self.log.info("Executor is terminated! Stopping %s to %s", ti.key, State.FAILED)
                ti.set_state(State.FAILED)
                self.change_state(ti.key, State.FAILED)
                continue
            task_succeeded = self._run_task(ti)
    def _run_task(self, ti: TaskInstance) -> bool:
        self.log.debug("Executing task: %s", ti)
        key = ti.key
        try:
            params = self.tasks_params.pop(ti.key, {})
            ti.run(job_id=ti.job_id, **params)
            self.change_state(key, State.SUCCESS)
            return True
        except Exception as e:
            ti.set_state(State.FAILED)
            self.change_state(key, State.FAILED)
            self.log.exception("Failed to execute task: %s.", str(e))
            return False
    def queue_task_instance(