I have a couple of tables that I want to reflect. The first is a data table
where one of the columns is a foreign key to the second table.
If I used SQLAlchemy declarative_base, a query might look something like
this:
session.query(Client.name, Suburb.label).join(Suburb) # In the Client class
there is an attribute suburb_id = Column(Integer, ForeignKey(Suburb.id))
However, this foreign key is not specified in the schema (we're using
postgres 9.2) but we know all the columns that look like something_id are
foreign keys, so I've been defining them that way using SQLAlchemy.
My problem is, although we have a fixed number of property tables (suburb,
country, join_date, ...) - each data table (per client) can have a
different set of columns.
This hasn't been much of a problem so far, since we only have a few *types* of
client data tables, so the combinations have been limited. However, I'd
like to cater for changes in the future.
If I reflect the table using SQLAlchemy, the resultant table will not have
the ForeignKey columns compared to if I did it manually. Is there a way to
add these in after reflection?
Or is my only option to use reflected tables and explicit join conditions?
Something like:
client_table_1 = Table('client_table_1', metadata, autoload=True,
autoload_with=engine, schema='client_1')
session.query(client_table_1.c.name,Suburb.label).join(Suburb,
client_table_1.c.suburb_id == Suburb.id) # Explicit joins only from now on
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