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
args=(
            ARG_QUEUES,
            ARG_CONCURRENCY,
            ARG_CELERY_HOSTNAME,
            ARG_PID,
            ARG_DAEMON,
            ARG_UMASK,
            ARG_STDOUT,
            ARG_STDERR,
            ARG_LOG_FILE,
            ARG_AUTOSCALE,
            ARG_SKIP_SERVE_LOGS,
        ),
    ),
    ActionCommand(
        name='flower',
        help="Start a Celery Flower",
        func=lazy_load_command('airflow.cli.commands.celery_command.flower'),
        args=(
            ARG_FLOWER_HOSTNAME,
            ARG_FLOWER_PORT,
            ARG_FLOWER_CONF,
            ARG_FLOWER_URL_PREFIX,
            ARG_FLOWER_BASIC_AUTH,
            ARG_BROKER_API,
            ARG_PID,
            ARG_DAEMON,
            ARG_STDOUT,
            ARG_STDERR,
            ARG_LOG_FILE,