dagster-docker

from dagster import Definitions, asset, define_asset_job from dagster_docker import docker_executor import os # Define a simple asset @asset def my_docker_asset(): """An asset whose execution will be managed by a Docker executor.""" message = os.environ.get("GREETING", "Hello from default asset!") print(message) return message # Define a job that uses the docker_executor. # The configuration demonstrates how to specify Docker image and environment variables # for the container in which the asset will run. my_docker_job = define_asset_job( name="my_docker_job", selection=[my_docker_asset], executor_def=docker_executor.configured( { "container_kwargs": { # This image needs to have Python and your Dagster code installed. # For a minimal example, we use a basic Python image. In production, # you'd build an image with your specific Dagster code and dependencies. "image": os.environ.get("DOCKER_IMAGE", "python:3.10-slim-buster"), "environment": { "GREETING": "Hello from inside the Docker container!" }, # Optional: specify a Docker network if your Dagster instance # is also running in Docker and needs to communicate. "network_mode": "bridge" }, # If you want to pass host environment variables directly to the container, # list them here. The values will be taken from the environment where Dagster runs. "env_vars": ["HOST_VAR"] } ), ) # To make these definitions loadable by Dagster (e.g., `dagster dev -f my_file.py`) # you would typically expose them via a Definitions object: # defs = Definitions( # jobs=[my_docker_job], # )