Hello, I'm using web2py with a relatively large legacy database. We have about 70 tables, and models/db.py is close to 1000 lines long.
The problem I'm facing is that all of these Field() constructors and define_table() calls take about 150-200ms to execute, and this overhead occurs each time any request is made to web2py. Compare this to a minimal web2py app, which might have a (reasonable) 10-30ms of overhead before response data starts flowing to the client. I was hoping that a simple solution would be to declare the DAL structure once in an importable module, which would be run once on web2py startup rather than at each request. I could then deepcopy it in my model file (which I think would be faster than all the calls to define_table(), Field(), etc.), and then establish a connection to the database from this copied DAL. Unfortunately, there are a few problems with this: 1. If a DAL instance is to be connected to the database, it must happen in the constructor. It doesn't seem that you can do "db = DAL(None)" and then establish a connection after the fact. Also, it looks like some db-specific behavior is set up in the DAL constructor based on the connection URL - this wouldn't happen in the case of DAL(None). 2. Table and Field instances have a reference to db, so it seems that define_table() needs to be called *after* the DAL connection has been established in order to set up these references. I suppose it would be possible to deepcopy a DAL(None) instance that has been established with Tables and Fields, and monkey-patch the db references thoughout the DAL structure, but chances seem good that this will create subtle bugs down the road if the internal DAL implementation ever changes. Can anyone suggest a better way to speed up DAL creation for large schemas? Thanks, Kevin
