On Tue, Jan 21, 2014 at 7:37 AM, Aldcroft, Thomas < aldcroft@head.cfa.harvard.edu> wrote:
On Tue, Jan 21, 2014 at 8:55 AM, Charles R Harris < charlesr.harris@gmail.com> wrote:
On Tue, Jan 21, 2014 at 5:54 AM, Aldcroft, Thomas < aldcroft@head.cfa.harvard.edu> wrote:
On Mon, Jan 20, 2014 at 6:12 PM, Charles R Harris < charlesr.harris@gmail.com> wrote:
On Mon, Jan 20, 2014 at 3:58 PM, Charles R Harris < charlesr.harris@gmail.com> wrote:
On Mon, Jan 20, 2014 at 3:35 PM, Nathaniel Smith <njs@pobox.com>wrote:
On Mon, Jan 20, 2014 at 10:28 PM, Charles R Harris <charlesr.harris@gmail.com> wrote: > > > > On Mon, Jan 20, 2014 at 2:27 PM, Oscar Benjamin < oscar.j.benjamin@gmail.com> > wrote: >> >> >> On Jan 20, 2014 8:35 PM, "Charles R Harris" < charlesr.harris@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...
The more I think about it, the more I think we may need to do that. Note that dynd has ragged arrays and I think they are implemented as pointers to buffers. The easy way for us to do that would be a specialization of object arrays to string types only as you suggest.
Is this approach intended to be in *addition to* the latin-1 "s" type originally proposed by Chris, or *instead of* that?
Well, that's open for discussion. The problem is to have something that is both compact (latin-1) and interoperates transparently with python 3 strings (utf-8). A latin-1 type would be easier to implement and would probably be a better choice for something available in both python 2 and python 3, but unless the python 3 developers come up with something clever I don't see how to make it behave transparently as a string in python 3. OTOH, it's not clear to me how to make utf-8 operate transparently with python 2 strings, especially as the unicode representation choices in python 2 are ucs-2 or ucs-4 and the python 3 work adding utf-16 and utf-8 is unlikely to be backported. The problem may be unsolvable in a completely satisfactory way.
Since it's open for discussion, I'll put in my vote for implementing the easier latin-1 version in the short term to facilitate Python 2 / 3 interoperability. This would solve my use-case (giga-rows of short fixed length strings), and presumably allow things like memory mapping of large data files (like for FITS files in astropy.io.fits).
I don't have a clue how the current 'U' dtype works under the hood, but from my user perspective it seems to work just fine in terms of interacting with Python 3 strings. Is there a technical problem with doing basically the same thing for an 's' dtype, but using latin-1 instead of UCS-4?
I think there is a technical problem. We may be able masquerade latin-1 as utf-8 for some subset of characters or fool python 3 in some other way. But in anycase, I think it needs some research to see what the possibilities are. Chuck