[Numpy-discussion] Managing Python with NumPy and many external libraries on multiple Windows machines
Mon Apr 27 18:40:39 CDT 2009
On Mon, Apr 27, 2009 at 18:36, Wes McKinney <firstname.lastname@example.org> wrote:
> On Mon, Apr 27, 2009 at 5:59 PM, Charles R Harris
> <email@example.com> wrote:
>> On Mon, Apr 27, 2009 at 3:05 PM, Wes McKinney <firstname.lastname@example.org> wrote:
>>> 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?
> 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
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.
"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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