1. Yes, literal_column does the trick.
2. I have tried with hybrid_method. It also works with literal_column, but
the problem here is that it's not including the field automatically in the
query? I suspect this is by design, but in my case it's required to execute
function so that I get a value from database and not from python method.
Can I force hybrid_method to always get a value from database?
On Sunday, 17 May 2020 16:37:25 UTC+2, Mike Bayer wrote:
>
>
>
> On Sun, May 17, 2020, at 6:54 AM, Erol Merdanović wrote:
>
> Hi
>
> First thank you for your reply.
>
> @Mike, yes. I wish to pass the row products row. I'm attaching working SQL
>
> SELECT *, get_product_price(products) FROM products;
>
>
> This works great in postgres. I tried it also on Mysql but they support
> only scalar values. I suspect that might work with other databases. I don't
> need to pass any dynamic arguments to column_property, it just needs to
> reference to existing row. I'll try with hybrid and let you know.
>
>
>
> oh is that a fixed expression ? you can probably get away with it like
> this then:
>
>
> from sqlalchemy import literal_column
>
> Product.base_price = column_property(
> cast(func.get_product_price(literal_column("products")), Numeric(15,
> 5)).label("base_price")
> )
>
> that is, if you want exactly the word "products" to appear in the SQL, and
> nothing else about it matters, you can just do it that way.
>
>
>
>
>
>
> @Jonathan
>
> Yes, if I pass the ID it works great. I'm just worried about the
> performance. If I want to execute then function in huge SELECT, I would
> need to do reselect on each row.
>
>
> On Saturday, 16 May 2020 21:42:54 UTC+2, Jonathan Vanasco wrote:
>
> It’s been a while since I’ve worked on stuff like this, but IIRC the
> simplest way was to use a function that accepts an ID and to flush in
> SqlAlchemy before executing it. Then you select the necessary row fields
> within the sql function, instead of passing args in or trying to pass a row
> in.
>
> In my experience, when you pass multiple args in, the function becomes
> very fragile and prone to break as your model changes.
>
>
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