### 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
key, (command, _, queue, ti) = sorted_queue.pop(0)
            
            
            
            #
            
            
            
            
            
            
            if key in self.running:
                attempt = self.attempts[key]
                if attempt.can_try_again():
                    
                    self.log.info("queued but still running; attempt=%s task=%s", attempt.total_tries, key)
                    continue
                
                self.log.error(
                    "could not queue task %s (still running after %d attempts)", key, attempt.total_tries
                )
                del self.attempts[key]
                del self.queued_tasks[key]
            else:
                if key in self.attempts:
                    del self.attempts[key]
                task_tuples.append((key, command, queue, ti.executor_config))
        if task_tuples:
            self._process_tasks(task_tuples)
    def _process_tasks(self, task_tuples: list[TaskTuple]) -> None: