I've started to use jupyter with kdb on the back end for analysis. For me I have some hope it will hit the sweet spot because: 1. kdb is "too obtuse" for many

I've started to use jupyter with kdb on the back end for analysis. For me I have some hope it will hit the sweet spot because: 1. kdb is "too obtuse" for many and python glue makes it more amenable 2. I can still have kdb functions in source code and call them from jupyter with pyq 3. I can do most of my "editing" in emacs to the kdb back-end, write python "libs" for parsing results, and just use jupyter as a fairly thin presentation layer 4. I can share notebooks with analysts who run the same jupyter server virtual env, so finally we can share notes Will this add more value than just using kdb? Time will tell, hard to know right now. I agree that the "ide" experience absolutely sucks.