On Mon, Jan 20, 2014 at 10:28 PM, Charles R Harris <charlesr.har...@gmail.com> wrote: > > > > On Mon, Jan 20, 2014 at 2:27 PM, Oscar Benjamin <oscar.j.benja...@gmail.com> > wrote: >> >> >> On Jan 20, 2014 8:35 PM, "Charles R Harris" <charlesr.har...@gmail.com> >> wrote: >> > >> > I think we may want something like PEP 393. The S datatype may be the >> > wrong place to look, we might want a modification of U instead so as to >> > transparently get the benefit of python strings. >> >> The approach taken in PEP 393 (the FSR) makes more sense for str than it >> does for numpy arrays for two reasons: str is immutable and opaque. >> >> Since str is immutable the maximum code point in the string can be >> determined once when the string is created before anything else can get a >> pointer to the string buffer. >> >> Since it is opaque no one can rightly expect it to expose a particular >> binary format so it is free to choose without compromising any expected >> semantics. >> >> If someone can call buffer on an array then the FSR is a semantic change. >> >> If a numpy 'U' array used the FSR and consisted only of ASCII characters >> then it would have a one byte per char buffer. What then happens if you put >> a higher code point in? The buffer needs to be resized and the data copied >> over. But then what happens to any buffer objects or array views? They would >> be pointing at the old buffer from before the resize. Subsequent >> modifications to the resized array would not show up in other views and vice >> versa. >> >> I don't think that this can be done transparently since users of a numpy >> array need to know about the binary representation. That's why I suggest a >> dtype that has an encoding. Only in that way can it consistently have both a >> binary and a text interface. > > > I didn't say we should change the S type, but that we should have something, > say 's', that appeared to python as a string. I think if we want transparent > string interoperability with python together with a compressed > representation, and I think we need both, we are going to have to deal with > the difficulties of utf-8. That means raising errors if the string doesn't > fit in the allotted size, etc. Mind, this is a workaround for the mass of > ascii data that is already out there, not a substitute for 'U'.
If we're going to be taking that much trouble, I'd suggest going ahead and adding a variable-length string type (where the array itself contains a pointer to a lookaside buffer, maybe with an optimization for stashing short strings directly). The fixed-length requirement is pretty onerous for lots of applications (e.g., pandas always uses dtype="O" for strings -- and that might be a good workaround for some people in this thread for now). The use of a lookaside buffer would also make it practical to resize the buffer when the maximum code point changed, for that matter... Though, IMO any new dtype here would need a cleanup of the dtype code first so that it doesn't require yet more massive special cases all over umath.so. -n -- Nathaniel J. Smith Postdoctoral researcher - Informatics - University of Edinburgh http://vorpus.org _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
