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Setting up a node env is arguably easier. An installer from the NodeJS downloads page includes both the Node runtime and NPM. One executable to get started.

• Phrodo_00 9y ago
  But some version python comes pretty much with every system, then you only need to install tensorflow with pip.
  • kalefranz 9y ago
    Best practice is to leave the system python alone. If you have to put sudo in front of pip, you're probably doing it wrong.
    • Phrodo_00 9y ago
      I agree with that, but for a beginner, using `pip -u` is less friction. They can use virtualenvs for their second project.
  • fnord123 9y ago
    I've come across benchmarks claiming a 7x speedup if you build Tensorflow from source. So you basically don't want to install using a binary wheel.
• cjalmeida 9y ago
  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 ...
  • darknoon 9y ago
    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.
  • jopsen 9y ago
    + virtualenv I always forget to set that up. Also I never learned python packaging, with npm it was trivial.
    • woolvalley 9y ago
      The basic rule of thumb is npm is 'virtualenv by default' while pip is 'global by default'.
      • JBReefer 9y ago
        This kind of thing is why people are saying npm is easier...
        • 3131s 9y ago
          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.
    • cx1000 9y ago
      If you use pipenv it takes care of the virtualenv stuff behind the scenes for you.
  • partycoder 9y ago
    ES5 and ES6 differ a lot. There's reverse compatibility, but they do differ.
• FridgeSeal 9y ago
  pipenv --three shell pipenv install pkg_1 pkg_ pkg_3 etc. Seems pretty easy to me. Plus, no one should be using Python 2 for any new project now, so that's not even a decision to bother with anymore.
  • ricardobeat 9y ago
    What's pipenv? Same as conda? Not using the system python also means installing python3 beforehand.
    • FridgeSeal 9y ago
      Pipenv is like virtualenv's but improved: https://docs.pipenv.org/ https://docs.pipenv.org/ Conda is like pip, but focused only on the sciences/data stuff. Pip has everything that Conda has and more as it's the standard packaging solution for Python.
      • dagw 9y ago
        Conda is like pip Conda is more like pipenv in that it does both package management and environment/version management. And while it's true that not every python package is in conda, that vast majority are and conda and pip play nicely together if you want to use pip to install some packages. Also conda can be used to install both surrounding tooling (like gcc and make, super useful on Windows) and, in many cases, build dependencies and necessary C libraries. Something pip doesn't handle. Doing for example "pip install gdal" will very likely leave you chasing down third party dependencies, while doing "conda install gdal" will just work. Finally, conda has recently added R support. So you can now manage your R packages and environments with the same tools as python. Super handy if you have project that uses both R and python.