I'm trying to work on a universal table generator based on in-memory table objects. The code is based on the work from the pandas to_sql.
I'll be targeting Oracle, Postgres, MySQL, and SQLite for sure. It seems like making sure to use Float(53) is the best way to guarantee that a column will be generated with a double-precision Floating point in all of these database backends without introspecting the engine at runtime. Pandas does that here: https://github.com/pandas-dev/pandas/blob/master/pandas/io/sql.py#L879 Is this generally true? Also, should I use the generic Float type, or the SQL FLOAT type? It doesn't seem like there's a huge functional difference. Brian -- SQLAlchemy - The Python SQL Toolkit and Object Relational Mapper http://www.sqlalchemy.org/ To post example code, please provide an MCVE: Minimal, Complete, and Verifiable Example. See http://stackoverflow.com/help/mcve for a full description. --- You received this message because you are subscribed to the Google Groups "sqlalchemy" group. To unsubscribe from this group and stop receiving emails from it, send an email to sqlalchemy+unsubscr...@googlegroups.com. To post to this group, send email to sqlalchemy@googlegroups.com. Visit this group at https://groups.google.com/group/sqlalchemy. For more options, visit https://groups.google.com/d/optout.
