Can you provide an example of using the execute_docker_container while creating an op?

Certainly! According to the documentation, you can create your own op that executes a Docker container by calling the

execute_docker_container

function inside your op definition. Here's an example provided in the documentation:

python from dagster import op from dagster_docker import execute_docker_container  @op def my_docker_op(context):     execute_docker_container(         context,         image="busybox",         command=["echo", "HELLO"],         # You can specify additional parameters here as needed     )

In this example,

my_docker_op

is an op that, when executed, will run a Docker container using the

busybox

image and execute the command

echo HELLO

inside that container. You can pass additional parameters to

execute_docker_container

as needed, such as

entrypoint

,

networks

,

registry

,

env_vars

, and

container_kwargs

. Please note that the

execute_docker_container

function is marked as experimental, which means that its API may change in future versions, even between dot releases.

can you provide an example of using that in a job?

Certainly! To use the

my_docker_op

within a job, you would define a job that includes this op as one of its steps. Here's an example of how you might define a job that uses the `my_docker_op`:

python from dagster import job  @job def my_docker_job():     my_docker_op()

In this example,

my_docker_job

is a job that consists of a single step, which is the execution of

my_docker_op

. When you run

my_docker_job

, it will execute the Docker container as specified in the

my_docker_op

definition. To run the job, you would use Dagster's command line interface or the Dagit UI. For example, to execute the job from the command line, you would use the following command:

shell dagster job execute -f my_docker_job.py

Make sure that the file

my_docker_job.py

contains both the op definition and the job definition as shown above. Please remember to have Docker installed and running on your machine, and ensure that Dagster has the necessary permissions to interact with Docker. Additionally, if you're using resources or configurations, you'll need to define and pass them accordingly within your job and op definitions.

@Scout Do I need to pass in a context argument when using it in a job?

No, you do not need to pass in a context argument when using an op within a job. In Dagster, the context is automatically provided to the op when the job is executed. The context includes information about the current run and the resources available to the op. Here's an example of a job definition without explicitly passing a context:

python from dagster import job  @job def my_docker_job():     my_docker_op()

When

my_docker_job

is executed, Dagster will take care of providing the appropriate context to

my_docker_op

. The context is used internally by the op to access configurations, resources, and logging, among other things. If you need to access the context within your op for some reason, you can define your op to accept a context parameter, and Dagster will provide the context when the op is invoked:

python from dagster import op  @op def my_docker_op(context):     # You can use the context here, for example:     <http://context.log.info|context.log.info>("Executing my_docker_op")     # ... rest of your op logic ...

However, when defining the job, you still do not need to pass the context manually; Dagster handles this automatically during execution.