SQLite

I recently needed to organise and filter a heap of data from a new client. I didn’t want to deal with the overhead of a full-blown database and decided to try sqlite3. As it turns out, it was really easy to work with since the bindings are included with Python2.6. All I needed to do was read a bit on how to interface Python with sqlite here: http://docs.python.org/library/sqlite3.html#module-sqlite3 and I was good to go! I also installed a nice database management utility called SQLite Database Browser v2.0b 1 which you can get here: http://sqlitebrowser.sourceforge.net. It makes managing the structure of the database a bit easier than working in a windows command prompt and you can write SQL on-the-fly if you’re having some problems with your Python. I find that it is pretty stable (though some of my poorly written SQL queries do send it into a tizzy and I need to kill it and reopen).

Now, I’ve decided to create a sqlite database and integrate it with the Excel front-end for one of our solvers (used when clients require desktop deployment). I anticipated that integration with an SQL database would greatly simplify and speed-up the reporting (with the added bonus of a significant reduction in the need for me to write complex vba code). Initially I banged around getting really frustrated with Excel, and DAO (even after I installed the ODBC driver available here: http://www.ch-werner.de/sqliteodbc/). Then I discovered SQLite for Excel here: http://sqliteforexcel.codeplex.com/. Whew! So far, I have found it very easy to work with and I am busy completing my reporting tool.