### Description

Ability to clear or mark task groups as success/failure and have that propagate to the tasks within that task group. Sometimes there is a need to adjust the status of tasks within a task group, which can get unwieldy depending on the number of tasks in that task group. A great quality of life upgrade, and something that seems like an intuitive feature, would be the ability to clear or change the status of all tasks at their taskgroup level through the UI.

### Use case/motivation

In the event a large number of tasks, or a whole task group in this case, need to be cleared or their status set to success/failure this would be a great improvement. For example, a manual DAG run triggered through the UI or the API that has a number of task sensors or tasks that otherwise don't matter for that DAG run - instead of setting each one as success by hand, doing so for each task group would be great.

### Related issues

_No response_

### Are you willing to submit a PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

from contextlib import redirect_stdout
from datetime import timedelta
from pathlib import Path
from tempfile import NamedTemporaryFile
from unittest import mock
from unittest.mock import patch
import jinja2
import pendulum
import pytest
import time_machine
from dateutil.relativedelta import relativedelta
from sqlalchemy import inspect
import airflow
from airflow import models, settings
from airflow.configuration import conf
from airflow.datasets import Dataset
from airflow.decorators import task as task_decorator
from airflow.exceptions import (
    AirflowException,
    DuplicateTaskIdFound,
    ParamValidationError,
    RemovedInAirflow3Warning,
)
from airflow.models import DAG, DagModel, DagRun, DagTag, TaskFail, TaskInstance as TI
from airflow.models.baseoperator import BaseOperator
from airflow.models.dag import DagOwnerAttributes, dag as dag_decorator, get_dataset_triggered_next_run_info
from airflow.models.dataset import DatasetDagRunQueue, DatasetEvent, DatasetModel, TaskOutletDatasetReference
from airflow.models.param import DagParam, Param, ParamsDict
from airflow.models.serialized_dag import SerializedDagModel
from airflow.operators.bash import BashOperator