> > Do you think it would make sense to extract some common functionality and > function names in a DB package? >
There was some discussion about that here <https://github.com/JuliaDB/DBDSQLite.jl/issues/1> but the problem is SQLite.jl is currently slightly too SQLite-specific for this to be an easy task and I don't think any of us really have the impetus to do it. No harm opening an issue though if it's something you're interested in. Heck you could even give it a go yourself if you want. Great work! Thanks! On Monday, 29 December 2014 16:39:01 UTC, Valentin Churavy wrote: > > Great work! > > Do you think it would make sense to extract some common functionality and > function names in a DB package? There is https://github.com/JuliaDB/DBI.jl > . > I like the interface you provided and would like to use parts of it for > the Postgres driver I am working on. > > - Valentin > > > On Monday, 29 December 2014 07:57:20 UTC+1, Jacob Quinn wrote: >> >> Hey all, >> >> We've been working on a fairly major upgrade of the SQLite.jl package >> over the last few months and are happy to announce a new release. This is a >> breaking change with the most recent tagged version in METADATA, so if you >> wish to stay on the old API version, just run `Pkg.pin("SQLite")`. >> Otherwise, to see the updates, you can simply run `Pkg.update()` if the >> `SQLite.jl` package is already installed, or run `Pkg.add("SQLite")` to >> install the package for the first time. >> >> The newer package boasts some great updates including a more Julian >> interface (the older package was modeled after the sqldf R package), the >> removal of DataFrames dependency making the package much more lightweight, >> but still easy to feed the new `SQLite.ResultSet` type into a DataFrame; >> there are also some awesome features allowing the use of custom julia >> scalar and aggregate functions in SQL statements by registering the julia >> function. Usage of custom Julia types is also supported for storing and >> loading in SQL tables (using the serialization interface). >> >> We've tried to put in many more tests and push the docs further along, >> but are of course always looking to improve. >> >> For those unfamiliar, SQLite is a lightweight, relational database system >> easy to run on a local machine. It's extremely handy for working with >> medium to large datasets that still fit on a single machine (MBs to GBs). >> It supports SQL statements to create, update, and delete relational tables, >> as well as select statements to perform calculations, or subset specific >> datasets. >> >> -Jacob Quinn and Sean Marshallsay >> >
