Hi
I need to take advantage of the performance boost available using
lazy_table=True.
My problem is that I have lots of table definitions in db.py that look like
this:
productSequenceTag = db.define_table('productSequenceTag',
Field('productSequenceTagId', 'id',
readable=False),
Field('productId', db.product, label=
'ProductId',
requires=IS_IN_DB(db,
'product.id', '%(productNumber)s - %(productName)s',
zero='..')),
Field('sequenceTagId', db.sequenceTag,
label='Sequence Tag', ondelete='RESTRICT'),
plural='Seq Tags')
There isn't much on the subject in the book, but there are a number of good
threads here in the group. However, it is really hard (for me at least) to
sift through all this info and know definitively what is the best way to
define a table and make sure it is lazy.
Has anyone successfully implemented lazy_tables on a large db project?
I've got 155 tables in my application.
I really need to find a way to make this load quicker. Any help would
really be appreciated.
-Jim
--
Resources:
- http://web2py.com
- http://web2py.com/book (Documentation)
- http://github.com/web2py/web2py (Source code)
- https://code.google.com/p/web2py/issues/list (Report Issues)
---
You received this message because you are subscribed to the Google Groups
"web2py-users" group.
To unsubscribe from this group and stop receiving emails from it, send an email
to [email protected].
For more options, visit https://groups.google.com/d/optout.
