Execute Workflow with Python - Inspect Output

[mlauber71]

@Brock_Tibert you would need a Container Output (Table) – KNIME Community Hub in the knime workflow to use the syntax

output_table = wf.data_table_outputs[0] # output_table will be a pd.DataFrame

Otherwise the python module would not know what data to use.

KNIME and Jupyter | KNIME

Another approach could be to try and call the workflow from another one and apply the input and output port and then see if everything would work.

Call Workflow - Main – mlauber71

So you might have to tell your students to use these container outputs.

Workflows can also be stored and being re-used like in this AutoML example. You will have to toy around how to use the input saved with the original workflow. If you want to re-use it with other data you will have to configure it:

Auto-ML. Output port has no data to display.

One remark about AutoML. It seems that when you want to store the resulting workflow and load it again you will have to remove the input and output that has been stored with the workflow so as to allow the use of the new data. [image] Also then with the Workflow Executor you will have to adjust the input and output sessions once. [image] Now the Executor is ready to receive the new data (which obviously has to have the same structure as the training data). And will give the results: [ima…