Thanks, passing cheers to QuickML developement team! We were using a Windows pre-release within 2019.4. Staying tuned to the GA news from the development team. On our end, we will include the new version of CAMPAIGN showcase (the one from the screenshot) on our community repos (public/private/internal) very soon, will update the documentation as well.

PS: the QuickML functionality being on its way to GA, we nevertheless could set up 1:1 info sessions with those that are interested in having an overview of how ML Toolkit functions and, specifically, how it allows to embed QuickML in analytic processes. If you are interested, please write us at MLToolkit@intersystems.com

Thanks, we should publish an update of the ML Toolkit user guide this week that includes this automation showcase, will be sharing the code as well among the showcases in Convergent Analytics (internal users) and ML Toolkit user group on GitHub (send us your 2fa-enabled GitHub account at MLToolkit@intersystems.com to join). The original example can be found here.

In addition to Eduard's answer, a short example based on sending Python's exec command to Python (assuming Python 3.*) to execute a Python script stored in a file:

(1)  Create a testfile.py in some folder that Python has access to, add the following lines to testfile.py:

f=open('disk:/path/to/your/folder/output.txt','w')
print('Hello Python Gateway',file=f)
f.close()

Save and close testfile.py

(2)  Open  IRIS Terminal, type and execute one by one the following commands:

set sc=##class(isc.py.Callout).Setup()

set sc=##class(isc.py.Main).SimpleString("exec(open('disk:/path/to/your/folder/testfile.py').read())",,,.sc)

(3) Check the output.txt file that has been created in your folder

Hi Alex, for an unlimited tooling consider trying ML Toolkit (Python Gateway and R Gateway). These extensions enable usage of Python and R in-IRIS (terminal, COS classes, Ensemble BPLs). The results obtained via Python and R (can be combined in one class/BPL) are written to a Caché table and can be visualized using DeepSee (as a Dashboard or as a graphical image formed in Python/R). Like this one, for example:

The BPL that generates the above example (please, note that the particular step is implemented in R while the surrounding steps are in Python):