[Docs] [Tests] Example for using dag defaults when declaring multiple dags within the same file

[cmarteepants]

We should document that we support using dag defaults when declaring multiple dags within the same file. Using this methodology, users can extend defaults as well as override them. It is even possible to have identical dags with different dag ids! We should also expand our test cases to account for these scenarios.

For example, if we define dags like this:

default:
  catchup: false
  default_args:
    start_date: "2024-01-01"
  schedule_interval: "0 0 * * *"
  tasks:
    extract:
      operator: airflow.operators.python.PythonOperator
      python_callable_file: /usr/local/airflow/include/etl_helpers.py
      python_callable_name: extract_helper
    load:
      dependencies:
      - transform
      operator: airflow.operators.python.PythonOperator
      python_callable_file: /usr/local/airflow/include/etl_helpers.py
      python_callable_name: load_helper
    transform:
      dependencies:
      - extract
      op_kwargs:
        ds_nodash: '{{ds_nodash}}'
      operator: airflow.operators.python.PythonOperator
      python_callable_file: /usr/local/airflow/include/etl_helpers.py
      python_callable_name: transform_helper


business_analytics:
  schedule_interval: "@daily"
  tasks:
    load:
      op_kwargs:
        database_name: BA
        table_name: inventory

data_science:
  tasks:
    load:
      op_kwargs:
        database_name: DS
        table_name: daily_sales

machine_learning:
  tasks:
    load:
      op_kwargs:
        database_name: ML
        table_name: training_data

They will be generated like this:

Note that the schedule for business_analytics dag is using the override value.

Not sure how realistic this scenario is, but there is also support for generating the same dag with different ids, like this:

...
default:
  ...
business_analytics: {}

data_science: {}

machine_learning: {}

Let's update our readme, and make sure we have test cases that cover this.