[traeblain]

I also have to disagree with quite a bit of this guide. Most windows systems are configured to simply do a `pip install numpy` since they often are missing the specific compiling tools to properly install these packages. For Windows vets, we've probably all seen the "Unable to find vcvarsall.bat" at one point or another.

I've found the easiest way it to point to 3rd party installers that often already have the key c-based tools you'll most often use. PythonXY, WinPython, PortablePython or Continuum's Anaconda. But you have to take the "bloat" with many of these, although PythonXY and WinPython allow you to select what you want and don't want.

[karamazov]

Package managers are great until you want something that isn't provided. I used numpy as an example, but our users are just as likely to work with web scraping, SQL, or REDIS as with numerical computations; in that case, they still need to know how to manage packages themselves.

[traeblain]

The installers don't stop the user from learning how to manage their packages. Other than Anaconda, the installers still emphasis using easy_install or pip. But what these do that many people don't understand is that when you do hit a compiling problem, it's often easier to find a pre-compiled package and simply install. So for you other examples, lxml is another notoriously difficult to get running on Windows. So you are stuck with a less efficient BeautifulSoup or not able to use PyQuery. So an installer for young python users is a godsend. As they dig deeper into python, the items you highlight are naturally developed.

(Don't get me wrong, by the way, props for helping out the often less technical Windows crowd.)