sqlalchemy dynamic schema on entity at runtime

Question

I'm using SQL Alchemy and have some schema's that are account specific. The name of the schema is derived using the account ID, so I don't have the name of the schema until I hit my application service or repository layer. I'm wondering if it's possible to run a query against an entity that has it's schema dynamically set at runtime?

I know I need to set the __table_args__['schema'] and have tried doing that using the type() built-in, but I always get the following error:

could not assemble any primary key columns for mapped table

I'm ready to give up and just write straight sql, but I really hate to do that. Any idea how this can be done? I'm using SA 0.99 and I do have a PK mapped.

Thanks

Answer 1

One option would be to reflect the particular account-dependent tables. Here is the SqlAlchemy Documentation on the matter.

Alternatively, You can create the table with a static schema attribute and update it as needed at runtime and run the queries you need to. I can't think of a non-messy way to do this. So here's the messy option

Use a loop to update the schema property in each table definition whenever the account is switched.

1. add all the tables that are account-specific to a list.

2. • if the tables are expressed in the declarative syntax, then you have to modify the DeclarativeName.__table__.schema attribute. I'm not sure if you need to also modify DeclarativeName.__table_args__['schema'], but I guess it won't hurt.
   • If the tables are expressed in the old style Table syntax, then you have to modify the Table.schema attribute.

3. If you're using text for any relationships or foreign keys, then that will break, and you have to inspect each table for such hard coded usage and change them
   example

   • user_id = Column(ForeignKey('my_schema.user.id')) needs to be written as user_id = Column(ForeignKey(User.id)). Then you can change the schema of User to my_new_schema. Otherwise, at query time sqlalchemy will be confused because the foreign key will point to my_schema.user.id while the query would point to my_new_schema.user.

4. I'm not sure if more complicated relationships can be expressed without the use of plain text, so I guess that's the limit to my proposed solution.

Here's an example I wrote up in the terminal:

>>> from sqlalchemy import Column, Table, Integer, String, select, ForeignKey
>>> from sqlalchemy.orm import relationship, backref
>>> from sqlalchemy.ext.declarative import declarative_base
>>> B = declarative_base()
>>> 
>>> class User(B):
...   __tablename__ = 'user'
...   __table_args__ = {'schema': 'first_schema'}
...   id = Column(Integer, primary_key=True)
...   name = Column(String)
...   email = Column(String)
... 
>>> class Posts(B):
...   __tablename__ = 'posts'
...   __table_args__ = {'schema':'first_schema'}
...   id = Column(Integer, primary_key=True)
...   user_id = Column(ForeignKey(User.id))
...   text = Column(String)
... 
>>> str(select([User.id, Posts.text]).select_from(User.__table__.join(Posts)))
'SELECT first_schema."user".id, first_schema.posts.text \nFROM first_schema."user" JOIN first_schema.posts ON first_schema."user".id = first_schema.posts.user_id'
>>> account_specific = [User, Posts]
>>> for Tbl in account_specific:
...   Tbl.__table__.schema = 'second_schema'
... 
>>> str(select([User.id, Posts.text]).select_from(User.__table__.join(Posts)))
'SELECT second_schema."user".id, second_schema.posts.text \nFROM second_schema."user" JOIN second_schema.posts ON second_schema."user".id = second_schema.posts.user_id'

As you see the same query refers to the second_schema after I update the table's schema attribute.

Answer 2

from sqlalchemy 1.1, this can be done easily using using schema_translation_map.

https://docs.sqlalchemy.org/en/11/changelog/migration_11.html#multi-tenancy-schema-translation-for-table-objects