[Numpy-discussion] Managing Python with NumPy and many external libraries on multiple Windows machines

Robert Kern robert.kern@gmail....
Mon Apr 27 18:40:39 CDT 2009

On Mon, Apr 27, 2009 at 18:36, Wes McKinney <wesmckinn@gmail.com> wrote:
> On Mon, Apr 27, 2009 at 5:59 PM, Charles R Harris
> <charlesr.harris@gmail.com> wrote:
>> On Mon, Apr 27, 2009 at 3:05 PM, Wes McKinney <wesmckinn@gmail.com> wrote:
>>> Hello,
>>> 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.
>> Out of curiosity, what was the nature of the incompatibility?
>> Chuck
> A Cython DLL using the NumPy include and buffer interface (which worked fine
> in 1.2.x, too) caused a hard crash on import, I wasn't able to diagnose
> further.

We have also encountered a number of segfaults upon import_array() on
multiple platforms due to an extension module being built against
numpy 1.3 but being imported after numpy 1.2.

Robert Kern

"I have come to believe that the whole world is an enigma, a harmless
enigma that is made terrible by our own mad attempt to interpret it as
though it had an underlying truth."
  -- Umberto Eco

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