I thought interfacing with important data science libraries would be a pro, but of course it has to be done first, it's quite a lot of work and not always that easy, even if it's C, not to mention C++.
I guess you are right about the popularity of Lisp ... pd <eukel...@gmail.com> schrieb am Di., 23. Feb. 2021, 08:57: > In my opinion picolisp has two disadvantages to be a scientific > programming language: > > 1 lack of flota support > 2 lack of libraries > > Both together make far easier to develop a science app in Python rather > than picolisp > > For sure It has got adventages too like db and pil but disadvantages are a > heavy stone > > Also lisp is not a fancy language, at least most people thinks it's weird > compared to Python and similars and this sure doesn't helps. This is the > reason for "science languages" are so similar in syntax (python,R...) > > Greets > > > El lun., 22 feb. 2021 22:40, Thorsten Jolitz <tjol...@gmail.com> escribió: > >> Maybe we should sponsor Alex (3 month work?) to build that "killer app" >> with the clear goals >> >> - for all those millions of (data) scientists that work with R etc, it >> should be the easiest (because fully integrated) way to build applications >> on top of their data >> - for those who like Picolisp it should be the Pil App to potentially >> make money with (without being superstar programmers). >> >> If Alex charges moderate rates (and doesn't think the idea is a waste ;-) >> I would be willing to take over one month of development ... ;-) >> >> >> >> >> <andr...@itship.ch> schrieb am Mo., 22. Feb. 2021, 21:51: >> >>> Yeah I had kinda similiar ideas, Thorsten. >>> >>> PicolispDB is certainly a killer feature - multi-paradigm database >>> (Key-Value, Object, Document, Graph, Relational.. really everything >>> covered), ACID (transactions), many indexing capabilities (including >>> text and spatial indexing), performant, extremely flexible and nicely >>> well maintainable. >>> >>> In the past, a lack of (digitalized) data was often an obstacle to get >>> useful (business) insights with software. >>> This changed, we are drowning in data. >>> >>> Now, and for the foreseeable future, the problem is to make sense of the >>> data, to be able to filter, map and connect various formats and data >>> sources together - while requirements change all the time. >>> >>> I believe Picolisp Database is a tool outstandingly suited for this. >>> >>> On 22.02.21 17:04, Thorsten Jolitz wrote: >>> > hallo list, >>> > I always thought a "killer app" would be nice, to make those "killer >>> > features" popular, and I always thought that could be a "data science >>> > application builder" with 3 features: >>> > >>> > - easy data import into a Picolisp DB >>> > - ffi/java wrappers for many data science libs (Rmath, Weka, ...) >>> > - easy web app development >>> > >>> > because for data scientists it seems often quite difficult to build >>> > applications on top of their data, and with Picolisp it would be all >>> > integrated into one single tool. >>> > >>> > But then I should be the one who implements that, and I made some >>> > attempts, but never had the time/energy/stamina/skills to bring it on
