[Numpy-discussion] [SciPy-user] Managing Python with NumPy and many external libraries on multiple Windows machines
Charles R Harris
Tue Apr 28 11:13:08 CDT 2009
On Tue, Apr 28, 2009 at 9:57 AM, David Cournapeau <email@example.com>wrote:
> On Wed, Apr 29, 2009 at 12:45 AM, Charles R Harris
> <firstname.lastname@example.org> wrote:
> > On Tue, Apr 28, 2009 at 9:41 AM, David Cournapeau <email@example.com>
> > wrote:
> >> On Tue, Apr 28, 2009 at 11:58 PM, Travis Oliphant
> >> <firstname.lastname@example.org> wrote:
> >> >
> >> > On Apr 27, 2009, at 4:05 PM, Wes McKinney 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.
> >> >
> >> > There has been a good discussion of this with others. I'm pretty
> >> > sure we had fixed this in NumPy so at least you would get a sane error
> >> > instead of a segfault. The solution may not be ideal and it can be
> >> > hard to remember to edit the right place in the headers when a change
> >> > is made so it may not have been done for 1.3
> >> Maybe we could supplement the manual editing: the code generators
> >> should guarantee the order of each item of the API, so the number of
> >> items in the array is enough to compare to API. So if we implement a
> >> guard in the PyArray_API, we could dynamically check the number of
> >> items in the array, and check it against the pre-computed number. A
> >> different number means incompatible API.
> > That will work as long as we maintain backward compatibility. If we
> > the ABI at some point we will need something stronger.
> I was only suggesting to supplement the current scheme. The current
> scheme is necessary in any case. But manually editing some macro in
> the header file is not very reliable. More generally, I think we
> should have a way to track C API and ABI relatively to the number
> version, as well as automatically generate the related documentation.
> While working on the split_comp branch, I notice several undocumented
> functions, several functions wrongly documented, etc... All this
> should be handled as automatically as possible.
I don't disagree with that, something in a release script perhaps? The
current NPY_VERSION number only tracks the ABI, so we need some fixups in
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