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Read numpy input, preview code, test_run/quick_run #88
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Communication using the files is a use basic case. This way is easier to distribute computation across cluster of workers, also using operations written in different languages. |
Actually not the first time people are asking about removing an operation! Thanks for noting, because I need more information about use cases |
Currently you can click "preview" and run the resulting script locally... Not best option but definitely easiest for now |
I've created 2 operations.
One creates a numpy array:
data_output = np.arange(15).reshape([3,5])
And another one adds 10 to that array:
output_data = input_data + 10
I don't understand how to do that - and can't find examples to learn from.
Can someone help me with that or point to better docs?
How to preview an operation's code from within the workflow graph?
Does it always using un-depreciated version or one can still point to depreciated one? Id's are non-human readable - so navigating in operations tab might get more difficult with many similarly named operations.
2.5. How to completely delete an operation or perform a cleanup by removing unused ones into some sort of archive?
It would be great to create a quick run option before approving an operation for the final workflow.
Technically speaking I could of created a simple workflow to test my currently-in-developement-not-yet-approved operation, and once it's tested I could approve it and push to the actual workflow where it could be used.
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