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
)
ARG_ERROR_LOGFILE = Arg(
    ("-E", "--error-logfile"),
    default=conf.get('webserver', 'ERROR_LOGFILE'),
    help="The logfile to store the webserver error log. Use '-' to print to stderr",
)
ARG_ACCESS_LOGFORMAT = Arg(
    ("-L", "--access-logformat"),
    default=conf.get('webserver', 'ACCESS_LOGFORMAT'),
    help="The access log format for gunicorn logs",
)
ARG_NUM_RUNS = Arg(
    ("-n", "--num-runs"),
    default=conf.getint('scheduler', 'num_runs'),
    type=int,
    help="Set the number of runs to execute before exiting",
)
ARG_DO_PICKLE = Arg(
    ("-p", "--do-pickle"),
    default=False,
    help=(
        "Attempt to pickle the DAG object to send over "
        "to the workers, instead of letting workers run their version "
        "of the code"
    ),
    action="store_true",
)
ARG_QUEUES = Arg(
    ("-q", "--queues"),
    help="Comma delimited list of queues to serve",