Hey Adrian --
In general, I think this is a pretty good idea. However, I've got
quite a bit of code the does something similar to the following:
obj = SomeObject()
for field in some_dict:
setattr(obj, field, some_dict[field])
obj.save()
i.e. build up on abject incrementally -- actual code usually does
some operations in the loop, of course. This is especially common in
code that's parsing XML to produce an object. Yes, I could save up
the attributes in a dict and apply it later, but this approach feels
right to me when I've used it.
Also, I can see this being very tricky in cases where validators are
dependant on other fields. Consider the following situation:
class MyModel(models.Model):
field1 =
meta.CharField(validator_list=[RequiredIfOtherFieldNotGiven
('field2')])
field2 =
meta.CharField(validator_list=[RequiredIfOtherFieldNotGiven
('field1')])
obj = MyModel(field1="whatever") # Works since field2 is only
required
# if field1 is empty
obj.field1 = '' # Fails - field1 is required
obj.field2 = 'some_value' # As a group, these two
statements should
work
Given this, I'm pretty sure that validation should be performed upon
obj.save() -- and also possibly voluntarily without saving through a
method like obj.validate().
I'm totally OK with silent up-conversion of (say) date values from
strings to datetime objects -- as long as there's NEVER silent data
loss. So if an invalid format is passed in to a date field's
__setattr__ an exception should be raised at that point.
I'm also OK with not exposing edit-inline for exactly the same
reasons you are.
See you at pycon!
Jacob
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