[SciPy-user] [Timeseries] Linux installation error
Thu Apr 2 19:21:32 CDT 2009
Ok, just tested the code you sent me and it works just fine (had to
kill numpy 1.2 though)
Some simple copy / pastable examples would be great to get new users
(that's me) going :-)
Is there any possibility to use python's decimal data type? I saw you
used it in your sql example on the database side, but I'm guessing
numpy doesn't allow for this? I sometimes have problems with equality
testing after several divisions / multiplications, so at the moment I
revert to the "is kind of" instead of the "is equal to" approach of
2009/4/3 Christiaan Putter <firstname.lastname@example.org>:
> Hi Pierre,
> Thanks for your swift reply, I'll test the code tomorrow.
> I'm looking forward to using your timeseries module. I'm writing a
> finance app using Enthought's tool suite and it seems timeseries will
> come in quite handy. Up until now I've been using normal numpy arrays
> with pytables for storing actual historical data and postgres (with
> SQLAlchemy) for storing some 'higher' level information about stocks
> and the results of analysis done on said historical data. I've found
> it's a pretty good combination since hdf5 compression keeps the data
> size down to only a few hundred megs and SQLAlchemy is simply awesome
> for running queries.
> Pytables doesn't play well with threading though even though I'm using
> locks in any block of code that so much as sniffs at the hdf5 file
> (strangely though it's rather stable on linux but crashes horribly on
> windows without even the courtesy of a trace back). I'll test h5py
> some time next week and if it performs better (which they claim on
> their site :-) I'll see if I can cook something up similar to what you
> did for integrating timeseries and pytables. I'll send it along to
> you once it's usable.
> In case that doesn't work I'll probably resort to storing the
> historical data in sql as well. Can someone give me some pointers on
> how I would go about that perhaps? It's about 20 000 - 30 000 stocks
> with on average about a decades worth of daily data. Would I dump all
> of that into a single table? 20 000 tables? hdf5 certainly is much
> better suited for something like that...
> Hope everyone is having a great day.
> 2009/4/3 Pierre GM <email@example.com>:
>> On Apr 2, 2009, at 6:43 PM, Christopher Barker wrote:
>>> Pierre GM wrote:
>>>> On Apr 2, 2009, at 6:19 PM, Tim Michelsen wrote:
>>>>> Indeed, the newly organised documentation with its logo is just
>>> where to I find these impressive docs?
>> (or google "scikits timeseries" and feel lucky)
>> SciPy-user mailing list
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