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Yeah I agree here. If you're doing mostly transactional work then it can work for the 99%. As soon as you step towards analytics queries you start to see things
by BeefWellington 3y ago
Yeah I agree here. If you're doing mostly transactional work then it can work for the 99%. As soon as you step towards analytics queries you start to see things fall apart and it's better to hand-tune your queries.
In my recent projects that's essentially what I do - I use SQLAlchemy for very basic CRUD and then anything analytical gets handcrafted.
- TX81Z 3y agoDoesn’t that increase complexity? I just have a database wrapper class and keep all my db code segregated there. In my case also using an ORM would blow up that segregated approach.
- ubercore 3y agoIt's very very easy to keep the sql alongside models and other business logic. SqlAlchemy lets you drop down to fairly complex sql while remaining in Python, and will even take in a direct sql query as well. The added complexity has always been a non-issue for me. Even a simple `sql.py` next to `models.py` works really well, for a pretty straightforward solution.