... virtualenv.

If you're doing more than one project on your machine then you need to concern yourself with dependencies across projects. In python the old-school way of doing this is to use virtualenv and pip. These tools get the job done, but they may have some caveats you should be aware of.


To re-iterate. When we run this;

jupyter lab

then we are technically at risk of launching the wrong jupyter lab reference even when pip freeze suggests we've installed it in our virtualenv. It can therefore be much safer to run this instead;

python -m jupyter lab

This way we don't fail silently anymore.

Feedback? See an issue? Something unclear? Feel free to mention it here.

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