Hello,

I changed the format of the tables a long time ago so that they could be parsed in standard Linux tools such as AWK.
https://github.com/apache/airflow/pull/8409
For example, to list the files that contain the DAG, I could run the command below.
```
airflow dags list | grep -v "dag_id" | awk '{print $2}' | sort | uniq
```
To pause all dags:
```bash
airflow dags list | awk '{print $1}' | grep -v "dag_id"| xargs airflow dags pause
```
Unfortunately [that has changed](https://github.com/apache/airflow/pull/12704) and we now have more fancy tables, but harder to use in standard Linux tools.

Alternatively, we can use JSON output, but I don't always have JQ installed on production environment, so performing administrative tasks is difficult for me.
```bash
$  docker run apache/airflow:2.0.1 bash -c "jq"

/bin/bash: jq: command not found
```

Best regards,
Kamil Breguła

CC: @turbaszek 
airflow/cli/cli_parser.py
name='show',
        help="Displays DAG's tasks with their dependencies",
        description=(
            "The --imgcat option only works in iTerm.\n"
            "\n"
            "For more information, see: https://www.iterm2.com/documentation-images.html\n"
            "\n"
            "The --save option saves the result to the indicated file.\n"
            "\n"
            "The file format is determined by the file extension. "
            "For more information about supported "
            "format, see: https://www.graphviz.org/doc/info/output.html\n"
            "\n"
            "If you want to create a PNG file then you should execute the following command:\n"
            "airflow dags show <DAG_ID> --save output.png\n"
            "\n"
            "If you want to create a DOT file then you should execute the following command:\n"
            "airflow dags show <DAG_ID> --save output.dot\n"
        ),
        func=lazy_load_command('airflow.cli.commands.dag_command.dag_show'),
        args=(
            ARG_DAG_ID,
            ARG_SUBDIR,
            ARG_SAVE,
            ARG_IMGCAT,
        ),
    ),
    ActionCommand(
        name='backfill',
        help="Run subsections of a DAG for a specified date range",