[SciPy-User] scipy central comments
Mon Sep 5 20:01:44 CDT 2011
On Mon, Sep 5, 2011 at 8:40 PM, Kevin Dunn <firstname.lastname@example.org> wrote:
> Hi everyone, SciPy Central maintainer here - sorry for the slow reply.
> On Mon, Sep 5, 2011 at 19:57, Collin Stocks <email@example.com> wrote:
>> Also in favour of a comments system.
> This is been bumped on the priority list. Django, which is used for
> SciPy Central, has a built-in commenting system. I will look at
> integrating it in the next while (just a bit busy at work with other
> things, but will get to it soon).
> My current highest priority is to complete library submissions, which
> are uploaded via a ZIP file. This will allow visitors to see the
> contents of the library by clicking on the file names (kind of like
> browsing a repo on GitHub).
> The next highest priority is commenting. So if you've got any requests
> for how commenting should look and behave:
>> On 09/05/2011 03:39 AM, Michael Klitgaard wrote:
>>> Would it be possible to include data files on SciPy-Central?
> Absolutely. I've already got some Django code for this on my company's
> site (shameless plug: http://datasets.connectmv.com).
We could also make the statsmdels datasets module independently
distributable and available, if there's interest.
> By the way, does SciPy/NumPy have a way to load data from a URL like R?
> I've looked for this but can't seem to find anything on it. In R it is
> so nice to be able to say to someone:
> data = read.table('http://datasets.connectmv.com/file/ammonia.csv')
> rather that doing a two step: download and load.
There is the DataSource class, though there are other ways this could
be accomplished. I'm not sure that there's a function to do it yet.
ds = np.lib.DataSource()
fp = ds.open('http://datasets.connectmv.com/file/ammonia.csv')
from StringIO import StringIO
arr = np.genfromtxt(StringIO(fp.read()), names=True)
Or you could use urllib
fp2 = urllib.urlopen('http://datasets.connectmv.com/file/ammonia.csv')
arr2 = np.genfromtxt(StringIO(fp2.read()), names=True)
If there's nothing else
def loadurl(url, *args, **kwargs):
from urllib import urlopen
from cStringIO import StringIO
fp = urlopen(url)
return np.genfromtxt(StringIO(fp.read()), *args, **kwargs)
arr3 = loadurl('http://datasets.connectmv.com/file/ammonia.csv')
>>> In this case the file 'ct.raw'. I believe it would improve the quality
>>> of the program to include the sample_data.
>>> This could perhaps make scipy central evem more usefull than other
>>> code sharing sites.
> Thanks for the idea!
>> The problem I see with data files is that they could be potentially
>> large. There may be a way around the problems associated with this, though.
> Bandwidth on my host shouldn't be an issue. Right now I use less than
> 0.5% of my monthly 1200 Gb allocation, so there's plenty of room to
>> Maybe I am a bit naive, but I can't think of many common circumstances
>> where a code fragment or program which is potentially useful to many
>> people would be more helpful by providing a data file, since most people
>> who would find said code useful would already have access to their own
>> data set.
>> I do, however, see the benefit of having some set of sample data on
>> SciPy-Central, but perhaps this data set should be generic in that many
>> different code contributions could reference it in a useful way.
> Agreed. Which is why I was asking about loading data from a URL above.
>> My two cents.
>> -- Collin
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