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#ask-ai
Title
# ask-ai
d

David de Meij

02/19/2024, 3:39 PM
Can I pass a retry policy in to_job()?
s

Scout

02/19/2024, 3:39 PM
No, according to the documentation, you cannot directly pass a
RetryPolicy
to the
to_job()
method. However, you can set a retry policy on individual ops within a job or on the entire job using the
@job
decorator. Here are the ways you can configure retries: 1. On Individual Ops: You can define a
RetryPolicy
on individual ops using the
@op
decorator:
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python from dagster import op, RetryPolicy  @op(retry_policy=RetryPolicy(max_retries=3, delay=0.2)) def my_op():     # op implementation
2. On the Entire Job: You can apply a
RetryPolicy
to all ops within a job using the
@job
decorator:
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python from dagster import job, RetryPolicy  @job(op_retry_policy=RetryPolicy(max_retries=1)) def my_job():     # job definition
3. On Specific Invocations of an Op: You can also set a retry policy on specific invocations of an op within a job:
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python from dagster import job, RetryPolicy  default_policy = RetryPolicy(max_retries=1) flakey_op_policy = RetryPolicy(max_retries=10)  @job(op_retry_policy=default_policy) def my_job():     my_op.with_retry_policy(flakey_op_policy)()
4. Using Tags: Additionally, you can configure retries using tags either on job definitions or in the Dagster UI Launchpad:
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python from dagster import job  @job(tags={"dagster/max_retries": 3}) def my_job_with_tags():     # job definition
These are the documented ways to configure retry policies in Dagster. If you need to convert a graph to a job and want to specify a retry policy, you would typically use the
@job
decorator on the function that returns the graph, and specify the retry policy there.
d

David de Meij

02/19/2024, 3:41 PM
how do I create a job from a graph without using .to_job?