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Sergey Lukyanchikov · Dec 13, 2019 go to post

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

Sergey Lukyanchikov · Dec 16, 2019 go to post

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.

Sergey Lukyanchikov · Jan 22, 2020 go to post

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

Sergey Lukyanchikov · May 8, 2019 go to post

Hi Mads, if building your Python code right in Caché is an option, please check PythonGateway - this is  another way to deploy Python (and R - check RGateway). If you can also use Ensemble, then you will be able to create "adaptive processes" using those extensions. PyhtonGateway has also a docker packaging, if needed.

Sergey Lukyanchikov · Jul 29, 2019 go to post

Hi Arjun, I use directly Ensemble (see below). Takes a couple of days to get the full taste, but afterwards it is hard to get back to "linear" IDEs.

Sergey Lukyanchikov · Aug 22, 2019 go to post

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):

Sergey Lukyanchikov · Feb 9, 2020 go to post

With Python Gateway you "drive" your Python context by sending to it the portions of your script and retrieving to your IRIS context the Python objects you need:

When the Python object is retrieved into IRIS context, you are free to decide how to harvest it, for example:

Sergey Lukyanchikov · Mar 21, 2020 go to post

Dear All, we are planning to have it (same headline) in English on April 28th. The landing page for registrations is in the works, we will publish an announcement very soon. Huge thanks!