Thanks.
So far I've worked out a solution iterating through the dataset. It's
slow and the hard drive pins, but this report is only intended to be run
once a year so performance isn't exactly a priority:
<code>
for i in range(self.oraData2.Tables[0].Rows.Count -1):
title = self.oraData2.Tables[0].Rows[i][0]
bcode = self.oraData2.Tables[0].Rows[i][1]
callno = str(self.oraData2.Tables[0].Rows[i][2])
stat1 = str(self.oraData2.Tables[0].Rows[i][3])
stat2 = str(self.oraData2.Tables[0].Rows[i][4])
(prep and execute SQL)
</code>
I'm on a bit of a timeline with this project before the end of the
semester so I'll explore a more performance friendly method once our
library gets underway with this version.
To be honest; System.Data.SQLite wasn't working because I've no idea how
to do it! :0 I kept translating code examples from VB and C# but it
didn't work. I'm sure it can be done quite well, I'm just a little too
green on the subject. :)
- Sven
> -----Original Message-----
> From: Jeff Hardy [mailto:jdha...@gmail.com]
> Sent: March-16-12 10:49 AM
> To: Vernon Cole
> Cc: Sven Thomas; ironpython-users@python.org
> Subject: Re: [Ironpython-users] DataSet --> SQLite
>
> On Wed, Mar 14, 2012 at 3:34 PM, Vernon Cole
> <vernondc...@gmail.com> wrote:
> > I would suggest opening both databases in their native form, then
do
> > the comparison using Python code rather than a complex SQL query.
It
> > may take a while to run, but should work okay. SQLite select
statements
> are quite fast.
> > Trying to do the whole thing in one swallow may be too much.
Better to
> > do lots of querys sequentially and build your result set as you
go.
>
> I agree with Vernon, but of course it depends on the operations you
need
> to do.
>
> You'll need to provide a little more information about why
> System.Data.SQLite isn't working for you. You could also try
2.7.2's
> sqlite3 support, which is more Pythonic.
>
> - Jeff
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