python - How to efficiently manage frequent schema changes using sqlalchemy?

Question

I'm programming a web application using sqlalchemy. Everything was smooth during the first phase of development when the site was not in production. I could easily change the database schema by simply deleting the old sqlite database and creating a new one from scratch.

Now the site is in production and I need to preserve the data, but I still want to keep my original development speed by easily converting the database to the new schema.

So let's say that I have model.py at revision 50 and model.py a revision 75, describing the schema of the database. Between those two schema most changes are trivial, for example a new column is declared with a default value and I just want to add this default value to old records.

Eventually a few changes may not be trivial and require some pre-computation.

How do (or would) you handle fast changing web applications with, say, one or two new version of the production code per day ?

By the way, the site is written in Pylons if this makes any difference.

Answer 1

Alembic is a new database migrations tool, written by the author of SQLAlchemy. I've found it much easier to use than sqlalchemy-migrate. It also works seamlessly with Flask-SQLAlchemy.

Auto generate the schema migration script from your SQLAlchemy models:

alembic revision --autogenerate -m "description of changes"

Then apply the new schema changes to your database:

alembic upgrade head

More info here: http://readthedocs.org/docs/alembic/