[Numpy-discussion] datetime dtype possible regression

Charles R Harris charlesr.harris@gmail....
Sun Apr 29 18:12:44 CDT 2012


On Sun, Apr 29, 2012 at 3:45 PM, Wes McKinney <wesmckinn@gmail.com> wrote:

> On Sat, Apr 28, 2012 at 11:18 AM, Charles R Harris
> <charlesr.harris@gmail.com> wrote:
> >
> >
> > On Sat, Apr 28, 2012 at 9:13 AM, Wes McKinney <wesmckinn@gmail.com>
> wrote:
> >>
> >> On Fri, Apr 27, 2012 at 4:57 PM, Robert Kern <robert.kern@gmail.com>
> >> wrote:
> >> > On Fri, Apr 27, 2012 at 21:52, Travis Vaught <travis@vaught.net>
> wrote:
> >> >> With NumPy 1.6.1 (from EPD 7.2-2) I get this behavior:
> >> >>
> >> >>
> >> >> ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
> >> >>
> >> >> In [1]: import numpy as np
> >> >>
> >> >> In [2]: schema = np.dtype({'names':['symbol', 'date', 'open', 'high',
> >> >> 'low',
> >> >>    ...:                        'close', 'volume', 'adjclose'],
> >> >>    ...:                    'formats':['S8', 'M8', float, float,
> float,
> >> >> float,
> >> >>    ...:                        float, float]})
> >> >>
> >> >> In [3]: data = [("AAPL", "2012-04-12", 600.0, 605.0, 598.0, 602.0,
> >> >> 50000000,
> >> >> 602.0),]
> >> >>
> >> >> In [4]: recdata = np.array(data, dtype=schema)
> >> >>
> >> >> In [5]: recdata
> >> >> Out[5]:
> >> >> array([ ('AAPL', datetime.datetime(2012, 4, 12, 0, 0), 600.0, 605.0,
> >> >> 598.0,
> >> >> 602.0, 50000000.0, 602.0)],
> >> >>       dtype=[('symbol', '|S8'), ('date', ('<M8[us]', {})), ('open',
> >> >> '<f8'),
> >> >> ('high', '<f8'), ('low', '<f8'), ('close', '<f8'), ('volume', '<f8'),
> >> >> ('adjclose', '<f8')])
> >> >>
> >> >>
> >> >> ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
> >> >>
> >> >>
> >> >> With numpy-1.7.0.dev_3cb783e I get this:
> >> >>
> >> >>>>> import numpy as np
> >> >>
> >> >>>>> schema =
> >> >>>>>
> >> >>>>>
> np.dtype({'names':['symbol','data','open','high','low','close','volume','adjclose'],
> >> >>>>> 'formats':['S8','M8',float,float,float,float,float,float]})
> >> >>
> >> >>>>> data =  [("AAPL", "2012-04-12", 600.0, 605.0, 598.0, 602.0,
> >> >>>>> 50000000,
> >> >>>>> 602.0),]
> >> >>
> >> >>>>> recdata = np.array(data, dtype=schema)
> >> >> Traceback (most recent call last):
> >> >>   File "<stdin>", line 1, in <module>
> >> >> ValueError: Cannot create a NumPy datetime other than NaT with
> generic
> >> >> units
> >> >>
> >> >>>>> np.version.version
> >> >> '1.7.0.dev-3cb783e'
> >> >>
> >> >> ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
> >> >>
> >> >> Any hints about a regression I can check for? Or perhaps I missed an
> >> >> api
> >> >> change for specifying datetime dtypes?
> >> >
> >> > Judging from the error message, it looks like an intentional API
> change.
> >> >
> >> > --
> >> > Robert Kern
> >> > _______________________________________________
> >> > NumPy-Discussion mailing list
> >> > NumPy-Discussion@scipy.org
> >> > http://mail.scipy.org/mailman/listinfo/numpy-discussion
> >>
> >> Maybe this should be raised as a bug (where do we report NumPy bugs
> >> these days, still Trac?). As I'm moving to datetime64 in pandas if
> >> NumPy 1.6.1 data has unpickling issues on NumPy 1.7+ it's going to be
> >> very problematic.
> >
> >
> > I was wondering what datetime you were using since the version in 1.6 had
> > issues. Have you tested with both?
> >
> > Chuck
> >
> >
> > _______________________________________________
> > NumPy-Discussion mailing list
> > NumPy-Discussion@scipy.org
> > http://mail.scipy.org/mailman/listinfo/numpy-discussion
> >
>
> Could you define issues? I haven't had a chance to make the library
> compatible with both 1.6.1 and 1.7.0 yet (like Travis I'm using NumPy
> 1.6.1 from EPD); it's important though as pandas will be the first
> widely used library I know of that will make heavy use of datetime64.
>
>
I'm not sure myself, but Travis asked Mark to get datetime fixed up. Mark
would probably be the best to answer the question. You might ping him
offline if he isn't watching the list at the moment.

Chuck
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