I am trying to programatically generate an

op

using the

OpDefinition

instantiation but I am struggling to provide

compute_fn

parameter for that. As I understand, it cannot directly be the base function that you use the

@op

decorator on. But not sure how to generate a valid

compute_fn

to pass to

OpDefinition

. Any ideas or references?

Hi @Anoop Sharma I wrote up a quick example of creating an op using

OpDefinition

. However, in almost all cases you should define ops using the

@op

decorator. If you can tell us a bit more about your use case, we might be able to help figure out how to do it using

@op

!

def my_func(context, _):
    yield Output(1, "my_out")

op_def = OpDefinition(name="op_def", input_defs=[], compute_fn=my_func, output_defs=[OutputDefinition(name="my_out", dagster_type=int)])

ok. from that description I'd imagine you could do something like this (semi-pseudocode)

@op    
def run_script(context, script_file):
    # code to run the script (subprocess.call(script_file), etc)

@op(out=DynamicOut())
def get_scripts():
    for f in directory:
         yield DynamicOut(f, mapping_key=f)

@graph     
def run_all_scripts():
    scripts = get_scripts()
    scripts.map(run_script)

This will collect all of the scripts in some directory in

get_scripts

and then because you are working with dynamic outputs, a

run_script

op will run once for each script returned from

get_scripts

. Then in

run_script

you can write whatever logic you need to execute the contents of a script