Hi,
I posted
http://stackoverflow.com/questions/9729175/multidimensional-arrays-in-sqlalchemy
to StackOverflow. Reproduced below. Please CC me on any reply. Thanks.
Regards, Faheem
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I'm using SQLAlchemy 0.6.3 with PostgreSQL 8.4 on Debian squeeze. I want a
table where one column stores something in PostgreSQL that shows up in
Python as a list of integer lists or tuples of integer tuples. E.g.
((1,2), (3,4), (5,6,7))
In the example below the column is `model`. I thought that a reasonable
approach might be to store stuff as an PG 2 dimensional table, which in PG
looks like `integer[][]`. I don't know in what form SQLA will return this
to Python, but I'm hoping it is something like a tuple of tuples.
However, I can't figure out how to tell SQLA to give me a two dimensional
Integer array. The
[documentation](http://docs.sqlalchemy.org/en/rel_0_6/dialects/postgresql.html#postgresql-data-types)
for `sqlalchemy.dialects.postgresql.ARRAY` says
item_type – The data type of items of this array. Note that
dimensionality is irrelevant here, so multi-dimensional arrays like
INTEGER[][], are constructed as ARRAY(Integer), not as
ARRAY(ARRAY(Integer)) or such. The type mapping figures out on the fly.
Unfortunately, I have no idea what that means. How can the type mapping
figure this out on the fly? It needs to create the correct DDL.
My first and only guess for how to do this would have been
`ARRAY(ARRAY(Integer))`. Currently I have
crossval_table = Table(
name, meta,
Column('id', Integer, primary_key=True),
Column('created', TIMESTAMP(), default=now()),
Column('sample', postgresql.ARRAY(Integer)),
Column('model', postgresql.ARRAY(Integer)),
Column('time', Float),
schema = schema,
This creates the following DDL
CREATE TABLE crossval (
id integer NOT NULL,
created timestamp without time zone,
sample integer[],
model integer[],
"time" double precision
);
which isn't right, of course. What am I missing?
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