Dear all, I have a requirement that makes me think that I need to "mass patch" some ORM objects. However, I am open to any suggestions regarding the way to answer my requirements.
I have defined an ORM object which represents a user, holding longitude and latitude (among other attributes). At some point, I want to query many of those users, and send them back holding the geographical distance from a certain point (defined by longitude and latitude) along with their other data. Computing the distance is computationally heavy, and I noticed that I could greatly improve performance by mass computing those distances, using numpy for example. My question is: would it be possible to split my flow in 2 : - a flow that queries the data that is simply available in the database, as ORM entities - a flow that queries lon/lat as a numpy array, perform the distance computation and afterward merge those 2 in the queried ORM entities? It is important to me that I finally get back a list of ORM entities fully populated, because my whole downstream process is built around this assumption. Thanks a lot for your insights on the matter! Regards, Pierre PS: giving me a "SQLAlchemy fast distance computation" won't do the trick, because I have other kinds of computations that may not be optimizable this way. -- 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 view this discussion on the web visit https://groups.google.com/d/msgid/sqlalchemy/CAH4TWVuJWP9WsSYNScPH%2BK9JJ3PqbOwxkm%3D_PXbPtYXzpBdvcg%40mail.gmail.com.
