more yahoo test errors

[cpcloud]

i love a good game of whack-a-mole.

https://travis-ci.org/pydata/pandas/jobs/8900734

[jtratner]

Is there a reason to actually download the data each time? Would it make
sense to store the data and then check that it generates:

1. The appropriate url for the request.
2. The appropriate output given various data (output from wrong symbol,
   output with correct symbol, etc)

Might require some refactoring of io/DataReader to use classes conforming
to a consistent interface but could be worth it both to guide new
contributors and to make it easier to test.

Could probably shrink it to two required functions generated request,
process response and then abstract actual request handling to TV with
base class.
On Jul 9, 2013 4:47 PM, "Phillip Cloud" notifications@github.com wrote:

i love a good game of whack-a-mole.

https://travis-ci.org/pydata/pandas/jobs/8900734

—
Reply to this email directly or view it on GitHubhttps://github.com//issues/4182
.

[cpcloud]

@jtratner

i hadn't seen u around these parts in a while; was wondering where ya went :)

you're right on all points, want to put up a PR? i would be eternally grateful. i'm so tired of dealing with these errors and i never use this functionality.

but...what you're describing is a major rewrite of data.py. in the long term is great

these fails are actually "bugs" (sort of)...if all are nan Panel cannot convert e.g., Panel({'a': np.nan}) will generate these errors. nans only propagate if there's at least a single 2D non nan value in the dict.

@jreback do you have any suggestions here? this issue will show up again since when no data are found there's a Panel from a "1D" dict which rightly fails.

i'm a torn between wanting to get the release out and fixing this for real™, the for real fix is going to be something similar to @jtratner's ideas but will probably take a few iterations to get right...

[jreback]

what is the Panel that fails? can you show an example?

[cpcloud]

d = {}
keys = 'a', 'b', 'c' # pretend these are stocks
for k in keys:
    d[k] = np.nan
p = Panel(d)  # fails because there are no 2D items in the dict

[cpcloud]

error message is bit cryptic, but i'm ignoring that issue for now

[cpcloud]

code that fails is not that different from my example

    stocks = {}
    for sym_group in _in_chunks(symbols, chunksize):
        for sym in sym_group:
            try:
                stocks[sym] = method(sym, start, end, retry_count, pause)
            except IOError:
                warnings.warn('Failed to read symbol: {0!r}, replacing with '
                              'NaN.'.format(sym), SymbolWarning)
                stocks[sym] = np.nan

    return Panel(stocks).swapaxes('items', 'minor')

[jreback]

yep...you could do it like this

Panel(stocks,major_axis=major_axis,minor_axis=minor_axis

the items are the keys in the dict (the syms)

but a-prior you prob don't know the major_axis (dates) nor minor_axis (fields)

so maybe

any(not np.isnan(v) for k,v in stocks.items())

or just keep a flag if there are any valid stocks

or catch the construction error on the Panel

[cpcloud]

i'll throw a RemoteDataError, joy

[jtratner]

@cpcloud haha, yeah...definitely been on the lighter side recently. I have to work and am taking CS classes on the side, so I have a busy schedule (+ I'm waiting for 0.12 to come out to push some of those PRs 😄).

I'd be happy to work something up in the long-term, I just don't have time this week (or next week).

Personally, I think you should monkey-patch this to work for now (e.g., by having it catch the failure with Panel construction and throw a graceful error) and get the release out. My guess is that io/data is going to be a constantly moving target anyways until we piece apart the bigger functions and force 'em to do smaller tasks.

[jtratner]

On a similar note, I'm always struck by how much time you and @jreback put into pandas. pretty neat.

[jreback]

@jtratner its magic! :)

[cpcloud]

@jtratner @jreback indeed! pandas FTW!!