| From: | Daniele Varrazzo <daniele(dot)varrazzo(at)gmail(dot)com> |
|---|---|
| To: | Jim Nasby <Jim(dot)Nasby(at)bluetreble(dot)com> |
| Cc: | "Koenig, Michael" <Michael(dot)Koenig(at)blue-yonder(dot)com>, "Uwe L(dot) Korn" <uwelk(at)xhochy(dot)com>, Adrian Klaver <adrian(dot)klaver(at)aklaver(dot)com>, Wes McKinney <wesmckinn(at)gmail(dot)com>, Matthew Rocklin <mrocklin(at)continuum(dot)io>, "psycopg(at)postgresql(dot)org" <psycopg(at)postgresql(dot)org> |
| Subject: | Re: Turbo ODBC |
| Date: | 2017-01-17 18:34:22 |
| Message-ID: | CA+mi_8Z5texpMHckgmrQbHSQ2jzUcPfcFBnrqDoOYHHi1QzDzg@mail.gmail.com |
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| Lists: | psycopg |
ISTM there has to be a fundamental switch in how psycopg uses the
libpq: it should use, at least for what these large objects are
concerned, a binary data type and asking for a binary result
(https://www.postgresql.org/docs/9.6/static/libpq-exec.html#LIBPQ-PQEXECPARAMS)
right?
-- Daniele
On Tue, Jan 17, 2017 at 4:31 PM, Jim Nasby <Jim(dot)Nasby(at)bluetreble(dot)com> wrote:
> On 1/17/17 9:16 AM, Koenig, Michael wrote:
>>
>> For the NumPy functionality, NULL values are handled by returning masked
>> arrays (https://docs.scipy.org/doc/numpy/reference/maskedarray.html) instead
>> of plain arrays.
>
>
> Oh, interesting. That's the same representation Postgres uses internally as
> well. I hope to explore this further in plpython at some point.
>
> --
> Jim Nasby, Data Architect, Blue Treble Consulting, Austin TX
> Experts in Analytics, Data Architecture and PostgreSQL
> Data in Trouble? Get it in Treble! http://BlueTreble.com
> 855-TREBLE2 (855-873-2532)
>
>
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