Comment by rmah

Our firm uses python extensively and the virtual environment for every script or script is ... difficult. We have dozens of python scripts running for team research and in production, from small maintenance tools to rather complex daemons. Add to that the hundreds of Jupyter notebooks used by various people. Some have a handful of dependencies, some dozens of dependencies. While most of those scripts/notebooks are only used by a handful of people, many are used company-wide.

Further, we have a rather largish set of internal libraries most of our python programs rely on. And some of those rely on external 3rd party API's (often REST). When we find a bug or something changes, more often than not, we want to roll out the changed internal lib so that all programs that use it get the fix. Having to get everyone to rebuild and/or redeploy everything is a non-starter as many of the people involved are not primarily software developers.

We usually install into the system dirs and have a dependency problem maybe once a year. And it's usually trivially resolved (the biggest problem was with some google libs which had internally inconsistent dependencies at one point).

I can understand encouraging the use of virtual environments, but this movement towards requiring them ignores what, I think, is a very common use case. In short, no one way is suitable for everyone.