Fetching a single row and producing objects, even if a chain of eagerly loaded
many-to-ones, is a relatively cheap operation, and it still sounds like network
overhead of rows is the main problem.If any columns fetch large binary
objects or large amounts textual data, that can take a long ti
Using the discriminator_on_association.py example, if I create a
Customer instance without specifying the addresses attribute, the for-
loop at the end will throw exception:
AttributeError: 'NoneType' object has no attribute 'addresses'
It works if I specify "addresses=[]", but that sounds like t
