[Numpy-discussion] compatibility for supporting more than 2 versions of numpy
josef.pktd at gmail.com
josef.pktd at gmail.com
Tue Jan 18 10:22:58 EST 2011
On Tue, Jan 18, 2011 at 10:09 AM, Ralf Gommers
<ralf.gommers at googlemail.com> wrote:
> On Tue, Jan 18, 2011 at 2:27 AM, <josef.pktd at gmail.com> wrote:
>> On Mon, Jan 17, 2011 at 12:18 PM, Bruce Southey <bsouthey at gmail.com>
>> > Scipy release notes usually state the supported numpy version eg from
>> > the current 0.8.0 release notes
>> > "This release requires Python 2.4 - 2.6 and NumPy 1.4.1 or greater."
>> > Consequently if you want to support different numpy versions, then you
>> > will need to maintain your own branch with that type of patch. That can
>> > get rather complex to maintain.
>> I'm not doing the work of maintaining a scipy that conflicts with numpy.
>> But *if* we want to support users that run numpy 1.3 with scipy 0.7,
>> then we need to use different arguments for calls into numpy and
>> scipy for depreciated and changed function arguments.
>> > It would be better that you change the code calling numpy/scipy
>> > functions rather than the functions themselves such as passing the
>> > appropriate *args and **kwargs to the function.
>> > I would expect that a try/except block would be more general as well as
>> > numpy.__version__ being a str.
>> Comparing strings is not a good idea, but I couldn't find anymore the
>> function that parses a version string.
> There's parse_numpy_version in pavement.py. The relevant lines are:
> a = re.compile("^([0-9]+)\.([0-9]+)\.([0-9]+)")
> return tuple([int(i) for i in a.match(out).groups()[:3]])
>> As it might be obvious on the mailing list, I'm not a fan of frequent
>> updates. With semi-annual releases, two versions only last a year.
> Maybe you don't like the deprecation policy, but how can frequent (if
> semi-annual can be called frequent) releases be a bad thing? No one likes to
> write code that doesn't get released for ages.
Sorry, this was an ambiguous phrasing. I meant I don't like to update
*my* computer very often, because I never know how much time it will
take to get everything compatible again.
I'm not criticizing the release policy, and I think you are doing a
very good job (much better than we do with statsmodels.)
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