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There's no python vs python3 decision to make. There's no (sane) reason to pick Python 2 in 2018 for new projects.

Conda installer comes with Python prepackaged. So it's really a single exe and one CMD to get a Tensorflow env setup. And, of course, you have access to numpy, pandas, jupyter, PIL ...



+ virtualenv

I always forget to set that up. Also I never learned python packaging, with npm it was trivial.


The basic rule of thumb is npm is 'virtualenv by default' while pip is 'global by default'.


This kind of thing is why people are saying npm is easier...


Yes, npm installs libraries locally so it avoids the need for something like virtualenv in the first place. Coming from Python, that immediately struck me as a better approach to package management.


If you use pipenv it takes care of the virtualenv stuff behind the scenes for you.


You say this, but coremltools (convert from industry standard to Apple's ML framework) initially only supported python 2, so it was annoying to work with some code in Python 2 and some in 3.5.


ES5 and ES6 differ a lot. There's reverse compatibility, but they do differ.




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