@Scout I have an

@op

that fans out multiple

DynamicOutput()

to run in separate

@op

functions. The second

@op

produces multiple

DynamicOutput()

. How do I consolidate the outputs from the second

@op

?

To consolidate the outputs from an

@op

that produces multiple

DynamicOutput

instances, you can use the

collect

method. The

collect

method creates a fan-in dependency over all the dynamic copies of an op, allowing the dependent op to receive a list containing all the values from the dynamic outputs. Here's a step-by-step explanation based on the documentation: 1. Define your first

@op

that fans out multiple

DynamicOutput

instances. Each

DynamicOutput

should have a unique

mapping_key

. 2. Define your second

@op

that also produces multiple

DynamicOutput

instances, again with unique

mapping_keys

. 3. To consolidate the outputs from the second

@op

, you would use the

collect

method on the dynamic output from the second

@op

. This will gather all the dynamic outputs into a list that can be passed to another

@op

. Here is a conceptual example based on the documentation:

python @op(out=DynamicOut()) def first_op():     # ... logic to produce multiple DynamicOutput instances     yield DynamicOutput(value, mapping_key=str(key))  @op(out=DynamicOut()) def second_op(input_value):     # ... logic to produce multiple DynamicOutput instances based on the input_value     yield DynamicOutput(transformed_value, mapping_key=str(new_key))  @op def consolidate_op(collected_values):     # ... logic to process the list of collected values from the dynamic outputs  @job def my_job():     dynamic_results = first_op().map(second_op)     consolidated_result = dynamic_results.collect()     consolidate_op(consolidated_result)

In this example,

first_op

fans out multiple dynamic outputs, which are then individually processed by

second_op

in parallel. The

collect

method is called on the dynamic output from

second_op

to gather all the results into a list, which is then passed to

consolidate_op

for further processing. Please note that the actual implementation will depend on your specific use case and the structure of your data and operations. The provided example is a high-level conceptual guide based on the documentation.

@Scout How do I write a

collect

method to collect

DynamicOutput()

from another

@op

to process the outputs together downstream in an

@op

?

To collect

DynamicOutput

instances from an

@op

and process them together downstream in another

@op

, you don't need to write a

collect

method yourself. Instead, you use the

collect

method provided by Dagster's API to create a fan-in dependency. The

collect

method is called on the dynamic output from an

@op

, and it gathers all the dynamic outputs into a list that can be passed to another

@op

. Here's how you can use the

collect

method in your Dagster job: 1. Define your

@op

that produces multiple

DynamicOutput

instances. 2. Use the

collect

method on the dynamic output from the

@op

. 3. Define another

@op

that takes the collected list of values and processes them. Here is a conceptual example:

python from dagster import job, op, DynamicOut, DynamicOutput  @op(out=DynamicOut()) def produce_dynamic_outputs():     # Replace with your logic to produce dynamic outputs     for i in range(5):         yield DynamicOutput(value=i, mapping_key=str(i))  @op def process_collected_outputs(collected_values):     # This op will receive a list of all values from the dynamic outputs     # Replace with your logic to process the collected values     total = sum(collected_values)     return total  @job def my_job():     dynamic_outputs = produce_dynamic_outputs()     collected = dynamic_outputs.collect()     process_collected_outputs(collected)

In this example,

produce_dynamic_outputs

yields multiple

DynamicOutput

instances. The

collect

method is used to gather these dynamic outputs into a list. The

process_collected_outputs

op then takes this list as input and processes it (in this case, by summing the values). When you run

my_job

, Dagster will automatically handle the collection of dynamic outputs and pass them as a list to the

process_collected_outputs

op.