On: Python, Machine Learning, and Language Wars (2015)

[a3n]

I have anaconda installed at work/windows and home/linux. One minor annoyance is that it doesn't play well (at all?) with virtualenv. They worked so hard to get a huge suite of off the shelf third party libraries integrated, it's curious that they would come up with a replacement for virtualenv.

I'm halfway hoping that I don't know what I'm talking about.

[spdustin → a3n]

http://conda.pydata.org/docs/using/envs.html

Glad to help :)

[a3n → spdustin]

Right, I know about that. What I'm pointing out is that anaconda doesn't support http://docs.python-guide.org/en/latest/dev/virtualenvs/

It's nice that they have an env tool, but why didn't they just use the existing virtualenv?

[spdustin → a3n]

Because using theirs means not having to recompile numpy (for example) with each environment.

Why doesn't anaconda's env work for you?

[a3n → spdustin]

Not saying it doesn't work, just wondering why the duplication of functionality. Which you answered, thanks.

[spdustin → a3n]

conda env also installs other dependencies for code. Really, the whole point of it all is that conda replaces pip and virtualenv.

Conda manages more than just Python packages, but other dependencies as well. For example, here's list of packages in a new environment I created with

  $ conda create -n hn python
  $ source activate hn
  $ conda list -c

  openssl-1.0.2g-0
  pip-8.1.1-py35_0
  python-3.5.1-0
  readline-6.2-2
  setuptools-20.3-py35_0
  sqlite-3.9.2-0
  tk-8.5.18-0
  wheel-0.29.0-py35_0
  xz-5.0.5-1
  zlib-1.2.8-0

setuptools and wheel are the only Python packages installed. The others are non-Python packages that conda is managing for my environment.

For all the talk of vendoring in package manager tools these days, I really, really like the way conda manages this stuff.