I am trying to set up a software architecture in order to be able to navigate easily between a test environment (where I will try out many methods in DSS) and a production environment without DSS.
The architecture that I want to set up is the following:
The idea is that, in the production environment, the main file will take into account production-specific I/O, while it will use dataiku I/O in the test environment. However, importing another source file in Python DSS is not supported as far as I know.
I saw that you have global variables and scenarii, but they are not flexible enough for me.
My question is therefore : is there any way to do what I want that is integrated in DSS, so without messing with the files in the filesystem?
See the documentation on the Python Environment, you can add .py files in DATA_DIR/lib/python.
You can also look into plugins, to develop a custom recipe that has the same name, within the same plugin ID, but with different rreleases for dev & production.