Yeah, I'd say there's definite interest in providing a DBI interface. See
the link Sean posted for more of the discussion. It's on my to-do list :)

-Jacob

On Tue, Dec 30, 2014 at 4:12 PM, Sean Marshallsay <[email protected]>
wrote:

> 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
>>>
>>

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