[Numpy-discussion] Possible roadmap addendum: building better text file readers
Thu Feb 23 14:24:28 CST 2012
On Thu, Feb 23, 2012 at 3:19 PM, Warren Weckesser
> On Thu, Feb 23, 2012 at 2:08 PM, Travis Oliphant <firstname.lastname@example.org>
>> This is actually on my short-list as well --- it just didn't make it to
>> the list.
>> In fact, we have someone starting work on it this week. It is his first
>> project so it will take him a little time to get up to speed on it, but he
>> will contact Wes and work with him and report progress to this list.
>> Integration with np.loadtxt is a high-priority. I think loadtxt is now
>> the 3rd or 4th "text-reading" interface I've seen in NumPy. I have no
>> interest in making a new one if we can avoid it. But, we do need to make
>> it faster with less memory overhead for simple cases like Wes describes.
> I have a "proof of concept" CSV reader written in C (with a Cython
> wrapper). I'll put it on github this weekend.
Sweet, between this, Continuum folks, and me and my guys I think we
can come up with something good and suits all our needs. We should set
up some realistic performance test cases that we can monitor via
vbench (wesm/vbench) while we're work on the project.
>> On Feb 23, 2012, at 1:53 PM, Pauli Virtanen wrote:
>> > Hi,
>> > 23.02.2012 20:32, Wes McKinney kirjoitti:
>> > [clip]
>> >> To be clear: I'm going to do this eventually whether or not it
>> >> happens in NumPy because it's an existing problem for heavy
>> >> pandas users. I see no reason why the code can't emit structured
>> >> arrays, too, so we might as well have a common library component
>> >> that I can use in pandas and specialize to the DataFrame internal
>> >> structure.
>> > If you do this, one useful aim could be to design the code such that it
>> > can be used in loadtxt, at least as a fast path for common cases. I'd
>> > really like to avoid increasing the number of APIs for text file
>> > loading.
>> > --
>> > Pauli Virtanen
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