Comments (5)
Hey @rafaelpierre, this is for syntactic sugar? We don't seem to access any resources in the cluster.
Adding something like this to Cluster...
class Cluster(BaseModel):
...
def __enter__(self) -> Cluster:
return self
def __exit__(self, *args):
pass
We can use it like this...
with Cluster(...) as cluster:
task_1 = NotebookTask(
...
cluster=cluster)
I've seen with
syntax used quite differently in the kubeflow dsl though, ExitHandler & ParallelFor for example.
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Yes, exactly @aaravind100 - this is more syntactic sugar :)
we should keep both flavors available: 1. assigning clusters to tasks (which basically maps the cluster_key
to the task payload) and 2. with the context manager - with Cluster(...) as cluster
as you pointed out
wanna take a stab at it?
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Yep, I can take this. I'll create a pr in sometime.
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Amazing @aaravind100!
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Closed with #14
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Related Issues (10)
- increase test coverage
- project documentation HOT 1
- support for notebook tasks HOT 5
- Ability to do `display(workflow)` from a Jupyter notebook and visualize a graphical representation of the workflow HOT 1
- Ability to define task dependencies with rshift and lshift (e.g. like in Airflow DAGs) HOT 1
- Support for Databricks SDK HOT 1
- Airflow DAG converter
- Add an option to export JSON / YAML
- implicit context managers HOT 6
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