deprecate fromstring() for text reading?
There was just a question about a bug/issue with scipy.fromstring (which is numpy.fromstring) when used to read integers from a text file. https://mail.scipy.org/pipermail/scipy-user/2015-October/036746.html fromstring() is bugging and inflexible for reading text files -- and it is a very, very ugly mess of code. I dug into it a while back, and gave up -- just to much of a mess! So we really should completely re-implement it, or deprecate it. I doubt anyone is going to do a big refactor, so that means deprecating it. Also -- if we do want a fast read numbers from text files function (which would be nice, actually), it really should get a new name anyway. (and the hopefully coming new dtype system would make it easier to write cleanly) I'm not sure what deprecating something means, though -- have it raise a deprecation warning in the next version? -CHB -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception Chris.Barker@noaa.gov
I think it would be good to keep the usage to read binary data at least. Or is there a good alternative to `np.fromstring(<bytes>, dtype=...)`? -- Marten On Thu, Oct 22, 2015 at 1:03 PM, Chris Barker <chris.barker@noaa.gov> wrote:
There was just a question about a bug/issue with scipy.fromstring (which is numpy.fromstring) when used to read integers from a text file.
https://mail.scipy.org/pipermail/scipy-user/2015-October/036746.html
fromstring() is bugging and inflexible for reading text files -- and it is a very, very ugly mess of code. I dug into it a while back, and gave up -- just to much of a mess!
So we really should completely re-implement it, or deprecate it. I doubt anyone is going to do a big refactor, so that means deprecating it.
Also -- if we do want a fast read numbers from text files function (which would be nice, actually), it really should get a new name anyway.
(and the hopefully coming new dtype system would make it easier to write cleanly)
I'm not sure what deprecating something means, though -- have it raise a deprecation warning in the next version?
-CHB
--
Christopher Barker, Ph.D. Oceanographer
Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception
Chris.Barker@noaa.gov
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
I think it would be good to keep the usage to read binary data at least. Agreed -- it's only the text file reading I'm proposing to deprecate. It was kind of weird to cram it in there in the first place. Oh, fromfile() has the same issues. Chris Or is there a good alternative to `np.fromstring(<bytes>, dtype=...)`? -- Marten On Thu, Oct 22, 2015 at 1:03 PM, Chris Barker <chris.barker@noaa.gov> wrote:
There was just a question about a bug/issue with scipy.fromstring (which is numpy.fromstring) when used to read integers from a text file.
https://mail.scipy.org/pipermail/scipy-user/2015-October/036746.html
fromstring() is bugging and inflexible for reading text files -- and it is a very, very ugly mess of code. I dug into it a while back, and gave up -- just to much of a mess!
So we really should completely re-implement it, or deprecate it. I doubt anyone is going to do a big refactor, so that means deprecating it.
Also -- if we do want a fast read numbers from text files function (which would be nice, actually), it really should get a new name anyway.
(and the hopefully coming new dtype system would make it easier to write cleanly)
I'm not sure what deprecating something means, though -- have it raise a deprecation warning in the next version?
-CHB
--
Christopher Barker, Ph.D. Oceanographer
Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception
Chris.Barker@noaa.gov
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
On Thu, Oct 22, 2015 at 5:47 PM, Chris Barker - NOAA Federal < chris.barker@noaa.gov> wrote:
I think it would be good to keep the usage to read binary data at least.
Agreed -- it's only the text file reading I'm proposing to deprecate. It was kind of weird to cram it in there in the first place.
Oh, fromfile() has the same issues.
Chris
Or is there a good alternative to `np.fromstring(<bytes>, dtype=...)`? -- Marten
On Thu, Oct 22, 2015 at 1:03 PM, Chris Barker <chris.barker@noaa.gov> wrote:
There was just a question about a bug/issue with scipy.fromstring (which is numpy.fromstring) when used to read integers from a text file.
https://mail.scipy.org/pipermail/scipy-user/2015-October/036746.html
fromstring() is bugging and inflexible for reading text files -- and it is a very, very ugly mess of code. I dug into it a while back, and gave up -- just to much of a mess!
So we really should completely re-implement it, or deprecate it. I doubt anyone is going to do a big refactor, so that means deprecating it.
Also -- if we do want a fast read numbers from text files function (which would be nice, actually), it really should get a new name anyway.
(and the hopefully coming new dtype system would make it easier to write cleanly)
I'm not sure what deprecating something means, though -- have it raise a deprecation warning in the next version?
There was discussion at SciPy 2015 of separating out the text reading abilities of Pandas so that numpy could include it. We should contact Jeff Rebeck and see about moving that forward. Chuck
On Oct 23, 2015, at 6:13 PM, Charles R Harris <charlesr.harris@gmail.com> wrote:
On Thu, Oct 22, 2015 at 5:47 PM, Chris Barker - NOAA Federal <chris.barker@noaa.gov> wrote:
I think it would be good to keep the usage to read binary data at least.
Agreed -- it's only the text file reading I'm proposing to deprecate. It was kind of weird to cram it in there in the first place.
Oh, fromfile() has the same issues.
Chris
Or is there a good alternative to `np.fromstring(<bytes>, dtype=...)`? -- Marten
On Thu, Oct 22, 2015 at 1:03 PM, Chris Barker <chris.barker@noaa.gov> wrote: There was just a question about a bug/issue with scipy.fromstring (which is numpy.fromstring) when used to read integers from a text file.
https://mail.scipy.org/pipermail/scipy-user/2015-October/036746.html
fromstring() is bugging and inflexible for reading text files -- and it is a very, very ugly mess of code. I dug into it a while back, and gave up -- just to much of a mess!
So we really should completely re-implement it, or deprecate it. I doubt anyone is going to do a big refactor, so that means deprecating it.
Also -- if we do want a fast read numbers from text files function (which would be nice, actually), it really should get a new name anyway.
(and the hopefully coming new dtype system would make it easier to write cleanly)
I'm not sure what deprecating something means, though -- have it raise a deprecation warning in the next version?
There was discussion at SciPy 2015 of separating out the text reading abilities of Pandas so that numpy could include it. We should contact Jeff Rebeck and see about moving that forward.
Chuck _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
IIRC Thomas Caswell was interested in doing this :) Jeff
On Oct 23, 2015 3:30 PM, "Jeff Reback" <jeffreback@gmail.com> wrote:
On Oct 23, 2015, at 6:13 PM, Charles R Harris <charlesr.harris@gmail.com>
wrote:
On Thu, Oct 22, 2015 at 5:47 PM, Chris Barker - NOAA Federal <
I think it would be good to keep the usage to read binary data at
least.
Agreed -- it's only the text file reading I'm proposing to deprecate.
It was kind of weird to cram it in there in the first place.
Oh, fromfile() has the same issues.
Chris
Or is there a good alternative to `np.fromstring(<bytes>,
chris.barker@noaa.gov> wrote: dtype=...)`? -- Marten
On Thu, Oct 22, 2015 at 1:03 PM, Chris Barker <chris.barker@noaa.gov>
wrote:
There was just a question about a bug/issue with scipy.fromstring
(which is numpy.fromstring) when used to read integers from a text file.
https://mail.scipy.org/pipermail/scipy-user/2015-October/036746.html
fromstring() is bugging and inflexible for reading text files -- and
it is a very, very ugly mess of code. I dug into it a while back, and gave up -- just to much of a mess!
So we really should completely re-implement it, or deprecate it. I
doubt anyone is going to do a big refactor, so that means deprecating it.
Also -- if we do want a fast read numbers from text files function
(which would be nice, actually), it really should get a new name anyway.
(and the hopefully coming new dtype system would make it easier to
write cleanly)
I'm not sure what deprecating something means, though -- have it
raise a deprecation warning in the next version?
There was discussion at SciPy 2015 of separating out the text reading abilities of Pandas so that numpy could include it. We should contact Jeff Rebeck and see about moving that forward.
IIRC Thomas Caswell was interested in doing this :)
When he was in Berkeley a few weeks ago he assured me that every night since SciPy he has dutifully been feeling guilty about not having done it yet. I think this week his paltry excuse is that he's "on his honeymoon" or something. ...which is to say that if someone has some spare cycles to take this over then I think that might be a nice wedding present for him :-). (The basic idea is to take the text reading backend behind pandas.read_csv and extract it into a standalone package that pandas could depend on, and that could also be used by other packages like numpy (among others -- I thing dato's SFrame package has a fork of this code as well?)) -n
On Oct 23, 2015, at 6:49 PM, Nathaniel Smith <njs@pobox.com> wrote:
On Oct 23, 2015 3:30 PM, "Jeff Reback" <jeffreback@gmail.com> wrote:
On Oct 23, 2015, at 6:13 PM, Charles R Harris <charlesr.harris@gmail.com> wrote:
On Thu, Oct 22, 2015 at 5:47 PM, Chris Barker - NOAA Federal <chris.barker@noaa.gov> wrote:
I think it would be good to keep the usage to read binary data at least.
Agreed -- it's only the text file reading I'm proposing to deprecate. It was kind of weird to cram it in there in the first place.
Oh, fromfile() has the same issues.
Chris
Or is there a good alternative to `np.fromstring(<bytes>, dtype=...)`? -- Marten
On Thu, Oct 22, 2015 at 1:03 PM, Chris Barker <chris.barker@noaa.gov> wrote:
There was just a question about a bug/issue with scipy.fromstring (which is numpy.fromstring) when used to read integers from a text file.
https://mail.scipy.org/pipermail/scipy-user/2015-October/036746.html
fromstring() is bugging and inflexible for reading text files -- and it is a very, very ugly mess of code. I dug into it a while back, and gave up -- just to much of a mess!
So we really should completely re-implement it, or deprecate it. I doubt anyone is going to do a big refactor, so that means deprecating it.
Also -- if we do want a fast read numbers from text files function (which would be nice, actually), it really should get a new name anyway.
(and the hopefully coming new dtype system would make it easier to write cleanly)
I'm not sure what deprecating something means, though -- have it raise a deprecation warning in the next version?
There was discussion at SciPy 2015 of separating out the text reading abilities of Pandas so that numpy could include it. We should contact Jeff Rebeck and see about moving that forward.
IIRC Thomas Caswell was interested in doing this :)
When he was in Berkeley a few weeks ago he assured me that every night since SciPy he has dutifully been feeling guilty about not having done it yet. I think this week his paltry excuse is that he's "on his honeymoon" or something.
...which is to say that if someone has some spare cycles to take this over then I think that might be a nice wedding present for him :-).
(The basic idea is to take the text reading backend behind pandas.read_csv and extract it into a standalone package that pandas could depend on, and that could also be used by other packages like numpy (among others -- I thing dato's SFrame package has a fork of this code as well?))
-n
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
I can certainly provide guidance on how/what to extract but don't have spare cycles myself for this :(
Grabbing the pandas csv reader would be great, and I hope it happens sooner than later, though alas, I haven't the spare cycles for it either. In the meantime though, can we put a deprecation Warning in when using fromstring() on text files? It's really pretty broken. -Chris On Oct 23, 2015, at 4:02 PM, Jeff Reback <jeffreback@gmail.com> wrote: On Oct 23, 2015, at 6:49 PM, Nathaniel Smith <njs@pobox.com> wrote: On Oct 23, 2015 3:30 PM, "Jeff Reback" <jeffreback@gmail.com> wrote:
On Oct 23, 2015, at 6:13 PM, Charles R Harris <charlesr.harris@gmail.com>
wrote:
On Thu, Oct 22, 2015 at 5:47 PM, Chris Barker - NOAA Federal <
I think it would be good to keep the usage to read binary data at
least.
Agreed -- it's only the text file reading I'm proposing to deprecate.
It was kind of weird to cram it in there in the first place.
Oh, fromfile() has the same issues.
Chris
Or is there a good alternative to `np.fromstring(<bytes>,
chris.barker@noaa.gov> wrote: dtype=...)`? -- Marten
On Thu, Oct 22, 2015 at 1:03 PM, Chris Barker <chris.barker@noaa.gov>
wrote:
There was just a question about a bug/issue with scipy.fromstring
(which is numpy.fromstring) when used to read integers from a text file.
https://mail.scipy.org/pipermail/scipy-user/2015-October/036746.html
fromstring() is bugging and inflexible for reading text files -- and
it is a very, very ugly mess of code. I dug into it a while back, and gave up -- just to much of a mess!
So we really should completely re-implement it, or deprecate it. I
doubt anyone is going to do a big refactor, so that means deprecating it.
Also -- if we do want a fast read numbers from text files function
(which would be nice, actually), it really should get a new name anyway.
(and the hopefully coming new dtype system would make it easier to
write cleanly)
I'm not sure what deprecating something means, though -- have it
raise a deprecation warning in the next version?
There was discussion at SciPy 2015 of separating out the text reading abilities of Pandas so that numpy could include it. We should contact Jeff Rebeck and see about moving that forward.
IIRC Thomas Caswell was interested in doing this :)
When he was in Berkeley a few weeks ago he assured me that every night since SciPy he has dutifully been feeling guilty about not having done it yet. I think this week his paltry excuse is that he's "on his honeymoon" or something. ...which is to say that if someone has some spare cycles to take this over then I think that might be a nice wedding present for him :-). (The basic idea is to take the text reading backend behind pandas.read_csv and extract it into a standalone package that pandas could depend on, and that could also be used by other packages like numpy (among others -- I thing dato's SFrame package has a fork of this code as well?)) -n _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion I can certainly provide guidance on how/what to extract but don't have spare cycles myself for this :( _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
FWIW, when I needed a fast Fixed Width reader for a very large dataset last year, I found that np.genfromtext() was faster than pandas' read_fwf(). IIRC, pandas' text reading code fell back to pure python for fixed width scenarios. On Fri, Oct 23, 2015 at 8:22 PM, Chris Barker - NOAA Federal < chris.barker@noaa.gov> wrote:
Grabbing the pandas csv reader would be great, and I hope it happens sooner than later, though alas, I haven't the spare cycles for it either.
In the meantime though, can we put a deprecation Warning in when using fromstring() on text files? It's really pretty broken.
-Chris
On Oct 23, 2015, at 4:02 PM, Jeff Reback <jeffreback@gmail.com> wrote:
On Oct 23, 2015, at 6:49 PM, Nathaniel Smith <njs@pobox.com> wrote:
On Oct 23, 2015 3:30 PM, "Jeff Reback" <jeffreback@gmail.com> wrote:
On Oct 23, 2015, at 6:13 PM, Charles R Harris <charlesr.harris@gmail.com>
wrote:
On Thu, Oct 22, 2015 at 5:47 PM, Chris Barker - NOAA Federal <
I think it would be good to keep the usage to read binary data at
least.
Agreed -- it's only the text file reading I'm proposing to deprecate.
It was kind of weird to cram it in there in the first place.
Oh, fromfile() has the same issues.
Chris
Or is there a good alternative to `np.fromstring(<bytes>,
chris.barker@noaa.gov> wrote: dtype=...)`? -- Marten
On Thu, Oct 22, 2015 at 1:03 PM, Chris Barker <chris.barker@noaa.gov>
wrote:
There was just a question about a bug/issue with scipy.fromstring
(which is numpy.fromstring) when used to read integers from a text file.
https://mail.scipy.org/pipermail/scipy-user/2015-October/036746.html
fromstring() is bugging and inflexible for reading text files -- and
it is a very, very ugly mess of code. I dug into it a while back, and gave up -- just to much of a mess!
So we really should completely re-implement it, or deprecate it. I
doubt anyone is going to do a big refactor, so that means deprecating it.
Also -- if we do want a fast read numbers from text files function
(which would be nice, actually), it really should get a new name anyway.
(and the hopefully coming new dtype system would make it easier to
write cleanly)
I'm not sure what deprecating something means, though -- have it
raise a deprecation warning in the next version?
There was discussion at SciPy 2015 of separating out the text reading abilities of Pandas so that numpy could include it. We should contact Jeff Rebeck and see about moving that forward.
IIRC Thomas Caswell was interested in doing this :)
When he was in Berkeley a few weeks ago he assured me that every night since SciPy he has dutifully been feeling guilty about not having done it yet. I think this week his paltry excuse is that he's "on his honeymoon" or something.
...which is to say that if someone has some spare cycles to take this over then I think that might be a nice wedding present for him :-).
(The basic idea is to take the text reading backend behind pandas.read_csv and extract it into a standalone package that pandas could depend on, and that could also be used by other packages like numpy (among others -- I thing dato's SFrame package has a fork of this code as well?))
-n
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
I can certainly provide guidance on how/what to extract but don't have spare cycles myself for this :(
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
On Tue, Oct 27, 2015 at 7:30 AM, Benjamin Root <ben.v.root@gmail.com> wrote:
FWIW, when I needed a fast Fixed Width reader
was there potentially no whitespace between fields in that case? In which case, it really isn a different use-case than delimited text -- if it's at all common, a version written in C would be nice and fast. and nat hard to do. But fromstring never would have helped you with that anyway :-) -CHB
for a very large dataset last year, I found that np.genfromtext() was faster than pandas' read_fwf(). IIRC, pandas' text reading code fell back to pure python for fixed width scenarios.
On Fri, Oct 23, 2015 at 8:22 PM, Chris Barker - NOAA Federal < chris.barker@noaa.gov> wrote:
Grabbing the pandas csv reader would be great, and I hope it happens sooner than later, though alas, I haven't the spare cycles for it either.
In the meantime though, can we put a deprecation Warning in when using fromstring() on text files? It's really pretty broken.
-Chris
On Oct 23, 2015, at 4:02 PM, Jeff Reback <jeffreback@gmail.com> wrote:
On Oct 23, 2015, at 6:49 PM, Nathaniel Smith <njs@pobox.com> wrote:
On Oct 23, 2015 3:30 PM, "Jeff Reback" <jeffreback@gmail.com> wrote:
On Oct 23, 2015, at 6:13 PM, Charles R Harris <
charlesr.harris@gmail.com> wrote:
On Thu, Oct 22, 2015 at 5:47 PM, Chris Barker - NOAA Federal <
I think it would be good to keep the usage to read binary data at
least.
Agreed -- it's only the text file reading I'm proposing to deprecate.
It was kind of weird to cram it in there in the first place.
Oh, fromfile() has the same issues.
Chris
Or is there a good alternative to `np.fromstring(<bytes>,
chris.barker@noaa.gov> wrote: dtype=...)`? -- Marten
On Thu, Oct 22, 2015 at 1:03 PM, Chris Barker <chris.barker@noaa.gov>
wrote:
> > There was just a question about a bug/issue with scipy.fromstring (which is numpy.fromstring) when used to read integers from a text file. > > https://mail.scipy.org/pipermail/scipy-user/2015-October/036746.html > > fromstring() is bugging and inflexible for reading text files -- and it is a very, very ugly mess of code. I dug into it a while back, and gave up -- just to much of a mess! > > So we really should completely re-implement it, or deprecate it. I doubt anyone is going to do a big refactor, so that means deprecating it. > > Also -- if we do want a fast read numbers from text files function (which would be nice, actually), it really should get a new name anyway. > > (and the hopefully coming new dtype system would make it easier to write cleanly) > > I'm not sure what deprecating something means, though -- have it raise a deprecation warning in the next version? >
There was discussion at SciPy 2015 of separating out the text reading abilities of Pandas so that numpy could include it. We should contact Jeff Rebeck and see about moving that forward.
IIRC Thomas Caswell was interested in doing this :)
When he was in Berkeley a few weeks ago he assured me that every night since SciPy he has dutifully been feeling guilty about not having done it yet. I think this week his paltry excuse is that he's "on his honeymoon" or something.
...which is to say that if someone has some spare cycles to take this over then I think that might be a nice wedding present for him :-).
(The basic idea is to take the text reading backend behind pandas.read_csv and extract it into a standalone package that pandas could depend on, and that could also be used by other packages like numpy (among others -- I thing dato's SFrame package has a fork of this code as well?))
-n
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
I can certainly provide guidance on how/what to extract but don't have spare cycles myself for this :(
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
-- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception Chris.Barker@noaa.gov
Correct, there were entries that would sometimes take up their entire width. The delimited text readers could not read this particular dataset. The dataset I am referring to is the processed ISD data: https://www.ncdc.noaa.gov/isd As for fromstring() not being able to help there, I didn't mean to imply that it would. I was more aiming to point out a situation where the NumPy's text file reader was significantly better than the Pandas version, so we would want to make sure that we properly benchmark any significant changes to NumPy's text reading code. Who knows where else NumPy beats Pandas? Ben On Mon, Nov 2, 2015 at 6:44 PM, Chris Barker <chris.barker@noaa.gov> wrote:
On Tue, Oct 27, 2015 at 7:30 AM, Benjamin Root <ben.v.root@gmail.com> wrote:
FWIW, when I needed a fast Fixed Width reader
was there potentially no whitespace between fields in that case? In which case, it really isn a different use-case than delimited text -- if it's at all common, a version written in C would be nice and fast. and nat hard to do.
But fromstring never would have helped you with that anyway :-)
-CHB
for a very large dataset last year, I found that np.genfromtext() was faster than pandas' read_fwf(). IIRC, pandas' text reading code fell back to pure python for fixed width scenarios.
On Fri, Oct 23, 2015 at 8:22 PM, Chris Barker - NOAA Federal < chris.barker@noaa.gov> wrote:
Grabbing the pandas csv reader would be great, and I hope it happens sooner than later, though alas, I haven't the spare cycles for it either.
In the meantime though, can we put a deprecation Warning in when using fromstring() on text files? It's really pretty broken.
-Chris
On Oct 23, 2015, at 4:02 PM, Jeff Reback <jeffreback@gmail.com> wrote:
On Oct 23, 2015, at 6:49 PM, Nathaniel Smith <njs@pobox.com> wrote:
On Oct 23, 2015 3:30 PM, "Jeff Reback" <jeffreback@gmail.com> wrote:
On Oct 23, 2015, at 6:13 PM, Charles R Harris <
charlesr.harris@gmail.com> wrote:
On Thu, Oct 22, 2015 at 5:47 PM, Chris Barker - NOAA Federal <
> I think it would be good to keep the usage to read binary data at
least.
Agreed -- it's only the text file reading I'm proposing to
deprecate. It was kind of weird to cram it in there in the first place.
Oh, fromfile() has the same issues.
Chris
> Or is there a good alternative to `np.fromstring(<bytes>,
chris.barker@noaa.gov> wrote: dtype=...)`? -- Marten
> > On Thu, Oct 22, 2015 at 1:03 PM, Chris Barker < chris.barker@noaa.gov> wrote: >> >> There was just a question about a bug/issue with scipy.fromstring (which is numpy.fromstring) when used to read integers from a text file. >> >> https://mail.scipy.org/pipermail/scipy-user/2015-October/036746.html >> >> fromstring() is bugging and inflexible for reading text files -- and it is a very, very ugly mess of code. I dug into it a while back, and gave up -- just to much of a mess! >> >> So we really should completely re-implement it, or deprecate it. I doubt anyone is going to do a big refactor, so that means deprecating it. >> >> Also -- if we do want a fast read numbers from text files function (which would be nice, actually), it really should get a new name anyway. >> >> (and the hopefully coming new dtype system would make it easier to write cleanly) >> >> I'm not sure what deprecating something means, though -- have it raise a deprecation warning in the next version? >>
There was discussion at SciPy 2015 of separating out the text reading abilities of Pandas so that numpy could include it. We should contact Jeff Rebeck and see about moving that forward.
IIRC Thomas Caswell was interested in doing this :)
When he was in Berkeley a few weeks ago he assured me that every night since SciPy he has dutifully been feeling guilty about not having done it yet. I think this week his paltry excuse is that he's "on his honeymoon" or something.
...which is to say that if someone has some spare cycles to take this over then I think that might be a nice wedding present for him :-).
(The basic idea is to take the text reading backend behind pandas.read_csv and extract it into a standalone package that pandas could depend on, and that could also be used by other packages like numpy (among others -- I thing dato's SFrame package has a fork of this code as well?))
-n
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
I can certainly provide guidance on how/what to extract but don't have spare cycles myself for this :(
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
--
Christopher Barker, Ph.D. Oceanographer
Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception
Chris.Barker@noaa.gov
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I was more aiming to point out a situation where the NumPy's text file reader was significantly better than the Pandas version, so we would want to make sure that we properly benchmark any significant changes to NumPy's text reading code. Who knows where else NumPy beats Pandas? Indeed. For this example, I think a fixed-with reader really is a different animal, and it's probably a good idea to have a high performance one in Numpy. Among other things, you wouldn't want it to try to auto-determine data types or anything like that. I think what's on the table now is to bring in a new delimited reader -- I.e. CSV in its various flavors. CHB Ben On Mon, Nov 2, 2015 at 6:44 PM, Chris Barker <chris.barker@noaa.gov> wrote:
On Tue, Oct 27, 2015 at 7:30 AM, Benjamin Root <ben.v.root@gmail.com> wrote:
FWIW, when I needed a fast Fixed Width reader
was there potentially no whitespace between fields in that case? In which case, it really isn a different use-case than delimited text -- if it's at all common, a version written in C would be nice and fast. and nat hard to do.
But fromstring never would have helped you with that anyway :-)
-CHB
for a very large dataset last year, I found that np.genfromtext() was faster than pandas' read_fwf(). IIRC, pandas' text reading code fell back to pure python for fixed width scenarios.
On Fri, Oct 23, 2015 at 8:22 PM, Chris Barker - NOAA Federal < chris.barker@noaa.gov> wrote:
Grabbing the pandas csv reader would be great, and I hope it happens sooner than later, though alas, I haven't the spare cycles for it either.
In the meantime though, can we put a deprecation Warning in when using fromstring() on text files? It's really pretty broken.
-Chris
On Oct 23, 2015, at 4:02 PM, Jeff Reback <jeffreback@gmail.com> wrote:
On Oct 23, 2015, at 6:49 PM, Nathaniel Smith <njs@pobox.com> wrote:
On Oct 23, 2015 3:30 PM, "Jeff Reback" <jeffreback@gmail.com> wrote:
On Oct 23, 2015, at 6:13 PM, Charles R Harris <
charlesr.harris@gmail.com> wrote:
On Thu, Oct 22, 2015 at 5:47 PM, Chris Barker - NOAA Federal <
> I think it would be good to keep the usage to read binary data at
least.
Agreed -- it's only the text file reading I'm proposing to
deprecate. It was kind of weird to cram it in there in the first place.
Oh, fromfile() has the same issues.
Chris
> Or is there a good alternative to `np.fromstring(<bytes>,
chris.barker@noaa.gov> wrote: dtype=...)`? -- Marten
> > On Thu, Oct 22, 2015 at 1:03 PM, Chris Barker < chris.barker@noaa.gov> wrote: >> >> There was just a question about a bug/issue with scipy.fromstring (which is numpy.fromstring) when used to read integers from a text file. >> >> https://mail.scipy.org/pipermail/scipy-user/2015-October/036746.html >> >> fromstring() is bugging and inflexible for reading text files -- and it is a very, very ugly mess of code. I dug into it a while back, and gave up -- just to much of a mess! >> >> So we really should completely re-implement it, or deprecate it. I doubt anyone is going to do a big refactor, so that means deprecating it. >> >> Also -- if we do want a fast read numbers from text files function (which would be nice, actually), it really should get a new name anyway. >> >> (and the hopefully coming new dtype system would make it easier to write cleanly) >> >> I'm not sure what deprecating something means, though -- have it raise a deprecation warning in the next version? >>
There was discussion at SciPy 2015 of separating out the text reading abilities of Pandas so that numpy could include it. We should contact Jeff Rebeck and see about moving that forward.
IIRC Thomas Caswell was interested in doing this :)
When he was in Berkeley a few weeks ago he assured me that every night since SciPy he has dutifully been feeling guilty about not having done it yet. I think this week his paltry excuse is that he's "on his honeymoon" or something.
...which is to say that if someone has some spare cycles to take this over then I think that might be a nice wedding present for him :-).
(The basic idea is to take the text reading backend behind pandas.read_csv and extract it into a standalone package that pandas could depend on, and that could also be used by other packages like numpy (among others -- I thing dato's SFrame package has a fork of this code as well?))
-n
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I can certainly provide guidance on how/what to extract but don't have spare cycles myself for this :(
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--
Christopher Barker, Ph.D. Oceanographer
Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception
Chris.Barker@noaa.gov
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
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On 3 Nov 2015, at 6:03 pm, Chris Barker - NOAA Federal <chris.barker@noaa.gov> wrote:
I was more aiming to point out a situation where the NumPy's text file reader was significantly better than the Pandas version, so we would want to make sure that we properly benchmark any significant changes to NumPy's text reading code. Who knows where else NumPy beats Pandas? Indeed. For this example, I think a fixed-with reader really is a different animal, and it's probably a good idea to have a high performance one in Numpy. Among other things, you wouldn't want it to try to auto-determine data types or anything like that.
I think what's on the table now is to bring in a new delimited reader -- I.e. CSV in its various flavors.
To add my own handful of change or at least another data point, I had been looking into both the pandas and the Astropy fast readers as a fast loadtxt/genfromtxt replacement; at the time I found the Astropy cparser source somewhat easier to dig into, although looking now Pandas' parser.pyx seems clear enough as well. Some comparison of the two can be found at http://astropy.readthedocs.org/en/stable/io/ascii/fast_ascii_io.html#speed-g... Unfortunately the Astropy fast reader currently does not support fixed-width format either, and adding this functionality would require modifications to the tokenizer C code - not sure how extensive. Cheers, Derek
participants (8)
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Benjamin Root -
Charles R Harris -
Chris Barker -
Chris Barker - NOAA Federal
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Derek Homeier -
Jeff Reback -
Marten van Kerkwijk -
Nathaniel Smith