![]() Recently I've had some success with speeding up (up to 4 threads) on scaling reads - e.g. Off course if memory usage becomes a problem, simply switching from :memory: to some kind of temp file per process would do it. This is done, since changes can be made in-memory which might not have to be written back. ![]() db from the OS into the memory, work on it, and "copy" it back. It is also cross platform, and is present in many Linux package repos.įrom the less little known things I love is the sqlite backup api. It's the best I've seen, and the developers are very responsive to bug reports and pull requests. Those looking for a GUI to view SQLite databases should check out sqlitebrowser. I also found this StackOverflow answer that explains how to easily change a column name in place. I agree that migrations can be a pain, but thankfully our tables are usually small enough that we can alter tables simply be recreating them. Writing GUI models and views over the database on the Python end of things is very straightforward, once you have your SQLAlchemy models set up. Our core simulator is written in Matlab for historical reasons, and we can communicate data easily using the database. Our application is an engineering simulation application. I also read this article entitled "SQLite As An Application File Format," which was the final straw for me to take the plunge. I decided to use SQLite after realizing I was slowly reimplementing many features of a database. We use SQLite as a file format for our desktop application (based on PySide) using SQLAlchemy.
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