Hello,

I found my ankser in own code ^^

static PyArray_Descr * create_datetime64_ms_dtype()
{
        // Extrapolated from numpy sources
        PyArray_Descr * dtype = PyArray_DescrFromType(NPY_DATETIME);
        reinterpret_cast<PyArray_DatetimeDTypeMetaData 
*>(dtype->c_metadata)->meta.base = NPY_FR_ms;
        return dtype;
}



On Thu, 2022-01-20 at 09:20 +0100, Benoit Gschwind wrote:
> Hello,
> 
> How can I create np.dtype("datetime64[ms]") in C to get the
> coresponding PyArray_Descr ?
> 
> Thank you by advance
> 
> On Wed, 2022-01-19 at 10:08 +0100, Benoit Gschwind wrote:
> > Hello Sebastian,
> > 
> > Thanks for the precision 
> > 
> > Best regards
> > 
> > On Tue, 2022-01-18 at 11:52 -0600, Sebastian Berg wrote:
> > > On Tue, 2022-01-18 at 18:29 +0100, Benoit Gschwind wrote:
> > > > Hello Sebastian,
> > > > 
> > > > Thanks for detail.
> > > > 
> > > > The last call has the NPY_ARRAY_C_CONTIGUOUS and
> > > > NPY_ARRAY_ALIGNED,
> > > > thus I guess it can be no-op most of the time but for some
> > > > unknown
> > > > case
> > > > it's may be safer ?
> > > 
> > > Ah, yes, you are right, and it should indeed by very quick,
> > > anyway. 
> > > My
> > > guess is, that you can do _only_ the last call with the appropriate
> > > `datetime64[ms]` descriptor passed in.
> > > (Since whatever C-code that follows is allowed to work with
> > > datetime64
> > > as if it were int64.)
> > > 
> > > Cheers,
> > > 
> > > Sebastian
> > > 
> > > 
> > > > 
> > > > Best regards
> > > > 
> > > > On Tue, 2022-01-18 at 09:22 -0600, Sebastian Berg wrote:
> > > > > On Tue, 2022-01-18 at 14:56 +0100, Benoit Gschwind wrote:
> > > > > > Hello,
> > > > > > 
> > > > > > I using the following code:
> > > > > > 
> > > > > > if (PyArray_TYPE(arr1) == NPY_DATETIME) {
> > > > > >         // Ensure datetime64[ms]
> > > > > >         auto tmp =
> > > > > > reinterpret_cast<PyArrayObject*>(PyObject_CallMethod(reinterp
> > > > > > re
> > > > > > t_
> > > > > > ca
> > > > > > st
> > > > > > <PyObject*>(arr1), "astype", "(s)", "datetime64[ms]"));
> > > > > >         std::swap(arr1, tmp);
> > > > > >         Py_XDECREF(tmp);
> > > > > >         // Ensure integer
> > > > > >         tmp =
> > > > > > reinterpret_cast<PyArrayObject*>(PyObject_CallMethod(reinterp
> > > > > > re
> > > > > > t_
> > > > > > ca
> > > > > > st
> > > > > > <PyObject*>(arr1), "astype", "(s)", "i8"));
> > > > > >         std::swap(arr1, tmp);
> > > > > >         Py_XDECREF(tmp);
> > > > > >         tmp =
> > > > > > reinterpret_cast<PyArrayObject*>(PyArray_FromArray(arr1,
> > > > > > PyArray_DescrFromType(NPY_INT64), NPY_ARRAY_IN_ARRAY));
> > > > > >         std::swap(arr1, tmp);
> > > > > >         Py_XDECREF(tmp);
> > > > > > }
> > > > > > 
> > > > > > First, if something is wrong with my code let me known. Then
> > > > > > I
> > > > > > wonder
> > > > > > if I can have a safe shortcut to avoid converting datetime64
> > > > > > to
> > > > > > i8.
> > > > > > I
> > > > > > guess the internal data of datetime64[ms] is i8 thus copying
> > > > > > and
> > > > > > casting the array may be avoided.
> > > > > 
> > > > > Yes, you can assume datetime64 is stored as an i8 with the unit
> > > > > and
> > > > > possible byteswapping.  Both of which, your initial cast will
> > > > > ensure.
> > > > > 
> > > > > The internal data is i8, except for the special NaT value.
> > > > > 
> > > > > Code-wise, you can avoid calling `astype`, but if you do (also
> > > > > in
> > > > > python), I suggest to pass `copy=False`, so that it does not
> > > > > copy
> > > > > if
> > > > > it
> > > > > clearly is not necessary (I am hoping to improve on the
> > > > > "clearly"
> > > > > here
> > > > > at some point).
> > > > > 
> > > > > The last call again seems to be a no-op?  Just the last call
> > > > > with
> > > > > the
> > > > > correct `datetime64[ms]` descriptor could be enough.
> > > > > 
> > > > > Cheers,
> > > > > 
> > > > > Sebastian
> > > > >  
> > > > > 
> > > > > > 
> > > > > > Thanks by advance
> > > > > > Best regards.
> > > > > > 
> > > > > > 
> > > > > > _______________________________________________
> > > > > > NumPy-Discussion mailing list -- numpy-discussion@python.org
> > > > > > To unsubscribe send an email to
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> > > > > > https://mail.python.org/mailman3/lists/numpy-discussion.python.org/
> > > > > > Member address: sebast...@sipsolutions.net
> > > > > > 
> > > > > 
> > > > > _______________________________________________
> > > > > NumPy-Discussion mailing list -- numpy-discussion@python.org
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> > > > > numpy-discussion-le...@python.org
> > > > > https://mail.python.org/mailman3/lists/numpy-discussion.python.org/
> > > > > Member address: gschw...@gnu-log.net
> > > > 
> > > > 
> > > > _______________________________________________
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> > > 
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> > 
> > 
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> 
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