Hi Team, I’m new to Dagster, and I’m trying to get independent Meltano taps and targets running in parallel. I’m curious how others using Meltano have their jobs setup and would appreciate any feedback on how I’m currently using it.

from dagster import job, DynamicOut,DynamicOutput, op
from dagster_meltano import meltano_command_op, meltano_resource
import os 

meltano_info = [
    {
        "tap": "tap-xx",
        "target": "target-xx",
        "catalog_path": "dagster_project/meltano/meltano_catalogs/tap-xx/xxx.json",
        "dagster_name": "xx",
    },
    {
        "tap": "tap-xx",
        "target": "target-xx",
        "catalog_path": "dagster_project/meltano/meltano_catalogs/tap-xx/xxx.json",
        "dagster_name": "xx",
    }  
]

@op(out=DynamicOut())
def create_run_commands_op():
    DAGSTER_PROJECT_ROOT = os.environ['DAGSTER_PROJECT_ROOT']
    commands = []
    for info in meltano_info:
        command_string = f'elt {info["tap"]} {info["target"]} --catalog {DAGSTER_PROJECT_ROOT}/{info["catalog_path"]}, dagster_name="{info["dagster_name"]}"'
        dagster_name = info["dagster_name"]
              commands.append(DynamicOutput(str(command_string)), mapping_key=str(dagster_name))
    return commands



@job(resource_defs={"meltano": meltano_resource})
def meltano_job():
    contents = create_run_commands_op()
    contents.map(meltano_command_op)