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Comment by TylerE | Hacker News Reader

We're not all building web apps in python - virtualenv is not universally useful.

(Edit: Not that I don't like virtualenv when it's appropriate, but it really bugs me the wrong way when people just throw out generalizations like that)

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I'm not a web developer, but I do data analysis with Python, and I use virtualenv heavily. For one thing, it increases reproducibility to have a record (pip freeze) of which versions of each package I used.

Having tried various ways of distributing desktop apps / non-web daemons, I've found virtualenvs useful there too (with the one fairly large caveat that installing wxWidgets in a virtualenv is a world of pain :( But then in those cases I use the OS-provided packages with the OS package manager, so I still never use virtualenv and pip independently)

Exactly! I am currently working on a machine learning task. Python is great for this, but most of the scripts that I am writing are run-once scripts. VirtualEnv would be overkill of this usecase.

> We're not all building web apps in python - virtualenv is not universally useful.

Huh, fair enough. I work on non-webapps too -- could you explain more about your use case?

Libraries that are very build-finicky (like various image processing libs) I've had bad luck with virtualenv, or env pip. Usually end up building by hand.

If you're doing data analysis, where most libraries are serious about backwards compatibility and you don't necessarily care whether your code still runs two years from now... virtualenvs are sometimes just not worth the bother. (Though I'd still recommend them.)

I build web apps, but almost anything else I do, including a full Python based backend for $WORK is all done in a virtualenv. Virtualenv's are not just for web apps.

fully agreed. the numpy, scipy, matplotlib, PyQt4 stack in particular is very indifferent to virtualenvs: you're going to need to install a whole ton of dependencies system-wide regardless.

i recommend it to everyone i work with, but it is significantly more useful when all your dependencies are pure python.

I agree with paulgb and others -- most of my past work with python could be called scientific programming in one way or another and pip has been enormously useful.

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