On Dec 28, 2008, at 10:54 AM, Alan Shields wrote:
>
> Let me check my understanding of what you're suggesting. The result
> would look something like:
>
> crates2apples = select([ crate_table.c.id,
> apple_table.c.id,
> apple_table.c.description,
> apple_table.c.stem_length ],
> from_obj = <join here>)
> crates2apples_mapper = mapper(Apples, crates2apples, non_primary=True)
>
> mapper(Crates, crate_table, properties={
> 'apples': relation(Apples, <actually, I have no clue what would go
> here>),
> })
>
> And, just to be clear, I could eagerload the Crates.apples relation
> under this configuration?
you'd put
"primaryjoin=crate_table.c.crate_id==crates2apples.c.some_column"
inside of the relation(). This approach usually makes the
eagerload's job easier, as far as constructing a join from crate_table
to Apple.
Of course the only way to know the best approach is to know exactly
what data you need to be loading. Its often the case that the best
approach overall is to use just a plain Crate->Apple relation with
nothing special, then just use a simple in-python property to give you
a particular "view" of that collection. If you're dealing with small
numbers of records that's how I'd usually do something like this. I
think the docs try to make a similar point on this.
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