On Wednesday, 7 September 2016 at 19:19:23 UTC, data pulverizer
wrote:
For some time I have been considering a problem to do with
creating tables with unbounded types, one of the failed
attempts is here:
https://forum.dlang.org/thread/gdjaoxypicsxlfvzw...@forum.dlang.org?page=1
I then exchanged emails with Lucian, Sparrows creator and he
very quickly and simply outlined the solution to the problem.
Thereafter I read his PhD thesis - one of the most informative
texts in computer science I have read and very well written.
At the moment, there are lots of languages attempting to solve
the dynamic-static loop, being able to have features inherent
in dynamic programming languages, while keeping the safety and
performance that comes with a static compiled programming
language, and then doing so in a language that doesn't cause
your brain to bleed. The "One language to rule them all" motif
of Julia has hit the rocks; one reason is because they now
realize that their language is being held back because the
compiler cannot infer certain types for example:
http://www.johnmyleswhite.com/notebook/2015/11/28/why-julias-dataframes-are-still-slow/
I don't see any reason why D can't implement pandas DataFrames
without needing to change the language at all
http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html
It's just a lot of work.
The simplest I can think of is a struct containing a tuple that
contains slices of equal length and an array of strings
containing column names. You could have a specialization with a
two-dimensional array (or ndslice).
