_deep_deannotate and aliased, joined tables

[Christoph Rauch]

Hello List,

the problem I am facing is that _deep_deannotate, which is used in ColumnProperty.__init__, breaks the FROM clause of my select() object if this select() has a JOIN (either left or right, doesn't matter) as from_obj in it, _where the initial table is aliased_.

To illustrate I'll append my testcase. I traced it down to Select._copy_internals(), line 4907 in sqlalchemy.sql.expression, where the call to s._from_obj.union(s._froms) will happily add an the initial table _a second time_ to the FROM clause, (it is already part of the join object) resulting in an error from the database because the alias is duplicated in the generated SQL.

Taking any hints on how to fix this. :)

Reproduced in 0.7.6

thanks,

Christoph

[Michael Bayer]

well the good news is that these cloning bugs, which have the property that each time I spend four hours fixing one I'm absolutely convinced it's the last (a process which began at least four years ago), are my highest priority since there are usually zero workarounds and also indicate there's many other places that they can be occurring.   

The call to s._from_obj.union(s._froms) regards keeping a set around of all the copies of from objects.  At the end of the day a particular FROM can be in these sets any number of times as various clones of itself and is normal - the actual list of FROMs to be rendered always has a unique list.   

The issue here centers around Select._froms at line 4769.    What happens here is a SELECT that contains a selectable Q, and a JOIN of Q to R, should be "hiding" the instance of Q by itself.  But the "hiding" logic in this case isn't matching up the cloned join of Q to R to the Q by itself, so you get "Q, Q JOIN R" in the FROM clause.   The point of _from_cloned is to keep track of all the copies of Q.

anyway its ticket http://www.sqlalchemy.org/trac/ticket/2453, I'd like to get this out today but hopefully it won't be too hard.

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<deep_deannotate_and_aliased_tables.py>

[Michael Bayer]

really great news, without even any coffee I came up with a patch for this one in less than 30 minutes.  I need to create some tests, maybe try to figure out why this hasn't been seen more frequently and something should be committed today.  It's on the ticket here: http://www.sqlalchemy.org/trac/ticket/2453#comment:1

[Christoph Rauch]

Awesome! Thank you very much. :)