[Numpy-discussion] Managing Python with NumPy and many external libraries on multiple Windows machines
Mon Apr 27 16:05:21 CDT 2009
I am wondering if anyone can offer some suggestions on this problem. Over
the last year or so I have been building a number of libraries on top of
NumPy + SciPy + matplotlib and other libraries which are being used for
investigative research for my company's problem domain in place of, say,
Matlab and R (which are more "ready out of the box" systems). I have
approximately 20 users, all of whom are running Windows on a very
Microsoft-centric network with databases, etc. Has anyone had any luck
managing a standardized Python environment on lots of Windows machines with
a large number of 3rd-party Python libraries? Upgrading packages right now
involves getting 20 people to click through an .exe installer, which is
hardly a good solution. For example, I was recently forced to upgrade
everyone's NumPy to 1.3 after I discovered that a DLL I had built against
1.3 was incompatible with 1.2.x.
It seems like on a Unix / OS X environment with root access this problem
would be fairly easy to script away, but on Windows it's rather painful. Any
advice would be much appreciated.
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