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_COLOR = Arg(
    ('--color',),
    help="Do emit colored output (default: auto)",
    choices={ColorMode.ON, ColorMode.OFF, ColorMode.AUTO},
    default=ColorMode.AUTO,
)
ARG_DAG_ID_OPT = Arg(("-d", "--dag-id"), help="The id of the dag")
ARG_NO_BACKFILL = Arg(
    ("--no-backfill",), help="filter all the backfill dagruns given the dag id", action="store_true"
)
ARG_STATE = Arg(("--state",), help="Only list the dag runs corresponding to the state")
ARG_LIMIT = Arg(("--limit",), help="Return a limited number of records")
ARG_NUM_EXECUTIONS = Arg(
    ("-n", "--num-executions"),
    default=1,
    type=positive_int(allow_zero=False),
    help="The number of next execution datetimes to show",
)
ARG_MARK_SUCCESS = Arg(
    ("-m", "--mark-success"), help="Mark jobs as succeeded without running them", action="store_true"
)
ARG_VERBOSE = Arg(("-v", "--verbose"), help="Make logging output more verbose", action="store_true")
ARG_LOCAL = Arg(("-l", "--local"), help="Run the task using the LocalExecutor", action="store_true")
ARG_DONOT_PICKLE = Arg(
    ("-x", "--donot-pickle"),
    help=(
        "Do not attempt to pickle the DAG object to send over "
        "to the workers, just tell the workers to run their version "
        "of the code"