thanks
robert
Michael Bayer schrieb:
> its not built into Query() at the moment so the closest you could get
> would be query.from_statement(some_statement). you can probably go
> from query->select()->back to query again doing something like this:
>
> q = query.<build up your query>
>
> session.query(...).from_statement(q.statement.prefix_with
> ("SQL_CALC_FOUND_ROWS..."))
>
>
>
> On Aug 29, 2009, at 2:47 AM, robert rottermann wrote:
>
>> Michael Bayer schrieb:
>>> use the "prefixes" argument to select() for this.
>>>
>> thanks very much.
>> it it possible to use this somehow with session.query?
>>
>> I do not use select at all, but do construct the queries dynamically
>> like so:
>>
>> q = session.query(tblNewsletteremail)
>> c = tblNewsletteremail.__table__.c
>> for k,v in info.items():
>> if isinstance(v, tuple):
>> op, v = v
>> if op == 'like':
>> q = q.filter(c[k].like('%' + v + '%'))
>> if op == 'in':
>> q = q.filter(c[k].in_(v))
>> else:
>> q = q.filter(c[k] == v)
>> if order_by:
>> for e in order_by:
>> q = q.order_by(c[e])
>> if limit:
>> q = q.limit(limit)
>> result = q.all()
>> now I would like to "apply" SQL_CALC_FOUND_ROWS to the query object
>> before
>> executing it. is this possible?
>>
>> thanks again
>> robert
>>
>>> On Aug 23, 2009, at 4:23 PM, robert rottermann wrote:
>>>
>>>> Hi there,
>>>>
>>>> I would like to create a batching functionality for a web based
>>>> aplication that
>>>> uses a mysql database.
>>>>
>>>> mysql offeres SQL_CALC_FOUND_ROWS for this purpose.
>>>> how can I use it, or is there a generic way to have sqlalchemy
>>>> return the number
>>>> of rows a query would have returned without limit.
>>>>
>>>> thanks
>>>> robert
>>>>
>>>
>>
>
>
> >
>
--~--~---------~--~----~------------~-------~--~----~
You received this message because you are subscribed to the Google Groups
"sqlalchemy" group.
To post to this group, send email to [email protected]
To unsubscribe from this group, send email to
[email protected]
For more options, visit this group at
http://groups.google.com/group/sqlalchemy?hl=en
-~----------~----~----~----~------~----~------~--~---
