Hi Rick,

>Well if you're doing an in-memory database - why not skip the database all together and just build up data structures in memory?

I just try to be lazy:)

The intention is to try to replicate a significant part of the VFP code into the python application. Since the VFP application does a lot of cursor-based mangling, I intend to re-implement part or the VFP cursor-based pseudo-code within python.

Of course python has a wide array of in-memory data structures, but that means a significant rewrite of the algos. As python is a basically interpreter with roughly the same perf at VFP, the first rewrite may be a bit slow, I expect. Base looping with python is of course as dismal as VFP or nearly so. And I may have to resort then to cython (vfp fll) or one of the many alternatives to achieve a decent perf.

Since I'd like to avoid any sort of useless or premature optimization at all cost, the level of performance of the sqlite engine is possibly part of the solution.

>For WebSurge in .NET I basically created large lists in memory and query them with LINQ which is very fast since it's all in memory - even when running against several >gigabytes of data search perf is super fast. I suspect the same will be true in other environments assuming there's an efficient query interface like LINQ in .NET.

Do you know of equivalent to LINQ in the python world? I do not. I expect python experts - I am certainly not at this stage - tend to resort to the wide of high-level data construct available within the python eco-system at first. Of course the choice is extremely wide here. When perf is still missing, cython and/or numpy use should speed things up.

Daniel