In what sense? A lot of people like to do data analysis with jupyter, pandas, scikit-learn, etc. They don't need to be treated like children with half-baked "integrations", instead they know how to read industry standard data files
The intended context of the question, which admittedly could be more clear-- is for a data product that could be used for any data. Take Cockroach DB for example, which already has python integration ( https://www.cockroachlabs.com/blog/sample-app-python-and-coc... )
With platforms like DataBricks and Airflow that are heavily inclined towards python, it feels somewhat unavoidable to need to offer a way to access the product via "import" in python.
So the question is: in that scenario, could a commercial product still survive-- or even thrive-- without doing so?
If your product is a database (I make a query, you return results) then I think many users are going to want Python bindings to the database.
If this product is going to "thrive" people are going to need some way to connect with it. What alternative to using Python to do you imagine somebody wants?
1. use "un-integrated" python code e.g. run a subprocess independently that just runs an external binary / shared lib / etc
2. avoid solutions that do not require a python environment entirely, or, use them in a less-commonly-employed manner that would not run the product through python (e.g. Airflow bash operator)
Both of the above seem perfectly reasonable to me, but I'm not sure whether others would agree.