I'm seeking advice. The scientific application I'm developing stores chemical, biotic, and other attributes in a postgres database. This will be a client/server application, not Web based. Some queries will be hard coded because they'll be commonly asked (similar to the balance sheet and income statement reports from an accounting application), and other queries will be specified by the users where they set the criteria using checkboxes, text boxes for dates, and similar wxPython widgets.
What I want to learn from those with experience is whether there might be advantages for me in this application by learning and using SQLalchemy rather than psycopg2. I've scanned the SQLA docs and wiki but have not seen any advantage from my using it. Then again, I'm not a professional python programmer or postgres DBA/application developer so I may very well be missing critical information. SQLA seems to have a longer learning curve than does psycopg2 (which is so similar to the pysqlite I've used that there should be minimal learning involved in using it). Your thoughts? Rich _______________________________________________ Portland mailing list [email protected] http://mail.python.org/mailman/listinfo/portland
