I have a strategy that works pretty consistently - close your eyes and ignore the best practices like using Anaconda, Python 3, virtualenv (or venv in py3... oh wait it's a module?) and just install Python 2.7 with pip into default locations (I even run pip with sudo, the horror). It works really well! I run all sorts of CV, ML, deep learning notebooks with no problems.
I agree, I never use virtualenv. I might if I was building a production system, but for my own laptop I feel perfectly capable of remember/tracking/checking what is in my ~/.local. (I always install with `--user`)
If I really need to containerize something, I use Docker.
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It is hard to overstate just how ferociously bad the experience of getting Jupyter from blank computer to the equivalent of "Hello world" actually is.
I have a strategy that works pretty consistently - close your eyes and ignore the best practices like using Anaconda, Python 3, virtualenv (or venv in py3... oh wait it's a module?) and just install Python 2.7 with pip into default locations (I even run pip with sudo, the horror). It works really well! I run all sorts of CV, ML, deep learning notebooks with no problems.
I agree, I never use virtualenv. I might if I was building a production system, but for my own laptop I feel perfectly capable of remember/tracking/checking what is in my ~/.local. (I always install with `--user`)
If I really need to containerize something, I use Docker.
I couldn't agree any less:
(not sure if all of them are really necessary)