Another way for reusing DAGs not stated in docs

### What do you see as an issue?

[In official docs](https://airflow.apache.org/docs/apache-airflow/stable/howto/dynamic-dag-generation.html) there have been stated several ways for dynamic DAGs generation. I found out another way which looks very convenient, so I'd like to get your opinion of it.

### Solving the problem

```
# reusable_dag.py

import datetime

from airflow.decorators import task
from airflow import DAG

DEFAULT_DAG_CONFIG = {
'schedule_interval': None,
'catchup': False,
'start_date': datetime.datetime.fromisoformat('2025-04-29'),
'default_args': {
'depends_on_past': False
},
'max_active_tasks': 1,
'max_active_runs': 1
}

def reusable_dag_generator(
dag_obj: DAG,
printable_msg: str
):
"""Reusable dag generator used as a template for DAG generation"""

with dag_obj:

@task()
def start_dag():
pass

@task()
def print_msg():
print(printable_msg)

@task()
def finish_dag():
pass

start_dag() >> print_msg() >> finish_dag()
return dag_obj

# dag0.py

from airflow import DAG
from reusable_dag import reusable_dag_generator, DEFAULT_DAG_CONFIG

dag = reusable_dag_generator(
dag_obj=DAG(
dag_id='test0',
**DEFAULT_DAG_CONFIG
),
printable_msg='Hello DAG0!'
)

# dag1.py

from airflow import DAG
from reusable_dag import reusable_dag_generator, DEFAULT_DAG_CONFIG

dag = reusable_dag_generator(
dag_obj=DAG(
dag_id='test1',
**DEFAULT_DAG_CONFIG
),
printable_msg='Hello DAG1!'
)
```

### Anything else

If provided way looks convenient, I would be glad to make a PR for docs enhancements.

### Are you willing to submit PR?

- [x] 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)

Start by reading the linked Dynamic DAG Generation documentation and compare the proposed reusable_dag.py pattern with the approaches already described there. Done means deciding whether this pattern belongs in the official docs and, if so, documenting it with a clear example and explanation.

Written by the indexing model from the issue text.