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Title
# ask-ai
p

Peter Lim

03/11/2024, 4:15 PM
how do I pass io managers into ops and jobs
s

Scout

03/11/2024, 4:15 PM
To pass I/O managers into ops and jobs in Dagster, you can follow these steps: 1. Define the I/O Manager: First, you need to define your I/O manager. This can be done by extending the
IOManager
class or using the
@io_manager
decorator. If you need to configure your I/O manager, you can extend
ConfigurableIOManager
instead. 2. Assign I/O Manager to Outputs: For each op, you can specify which I/O manager to use for its outputs by setting the
io_manager_key
on the
Out
object. This key will reference the I/O manager you want to use. 3. Bind I/O Managers to Jobs: When defining a job, you bind I/O managers to it by including them in the
resource_defs
argument. The keys used in
resource_defs
should match the
io_manager_key
specified in the ops. Here's an example based on the documentation:
Copy code
python from dagster import job, op, Out, IOManager, ResourceDefinition  # Define your custom I/O manager class MyIOManager(IOManager):     def handle_output(self, context, obj):         # Logic to store the output         pass      def load_input(self, context):         # Logic to load the input         pass  # Define an op and specify the io_manager_key for its output @op(out=Out(io_manager_key="my_io_manager_key")) def my_op():     return "data"  # Define a job and bind the custom I/O manager to it @job(resource_defs={"my_io_manager_key": ResourceDefinition.hardcoded_io_manager(MyIOManager())}) def my_job():     my_op()  # Now, when you execute the job, the custom I/O manager will be used for the op's output result = my_job.execute_in_process()
In this example,
MyIOManager
is a custom I/O manager that you would define according to your storage and retrieval needs. The
my_op
op specifies that it uses an I/O manager with the key
"my_io_manager_key"
. The
my_job
job then binds the custom I/O manager to that key using
ResourceDefinition.hardcoded_io_manager(MyIOManager())
. Remember that each op can have its own I/O manager, or multiple ops can share the same I/O manager. The I/O manager that's used for handling a particular op output is automatically used for loading it in downstream ops or assets.
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