In their definition of programming languages types, I'm not sure I see how SQL which they cateogrize as declarative really differs from FP, especially with lazy evaluation. Both are a succession of functions applied onto a previously declared variable : just think of a long SQL query with many ctes modifying the previous ones; each of them can be thought of as a variable which takes its value from the application of a function on other variable (a bit like the let function in ocaml).
I always thought of LaTeX as being the prime example of declarative programming.
Yes Excel lately is turning into a really compelling product, using functions such as sequence (dynamic arrays), lambda (pure functions) and let (defining sub-variables). You'd think you're coding in a pure functional language, and that's great! Now, ff only Excel had a convolution function! But nonetheless it's a great GUI, everybody knows how to use it and sharing it is dead simple.
The one downside I can find is the lack of a good plotting library. And yes comments as well is something I miss a lot.
Interesting. I heard many good things about Pycharm, but it kind of looks bloated? How does it compare to VS Code (which is quite good (notebook and repl support mostly), but not great, in particular regarding the debugging experience)?
Recently stumbled upon this quite good YT channel, which also brands itself as aimed towards beginners, although in my opinion both the Susskind lectures and these 'physics mini lessons' would be best appreciated with at least some prior knowledge of undergrad physics.
Well you can manage to run the Wolfram Engine through a jupyter kernel directly in VS Code. Although, I believe when I set it up the output was an image, no matter the object being returned (for instance 2+3 would return an image of 5 black on white).
Totally unrelated since I can't access the website, but one thing that I'd like to see in a typing system used in data analysis is to be able to see the dimension of the data structures used. For instance, to be able to tell at compile time if a matrix multiplication is going to crash due to dimension mismatch.
So far, in Python at least, at best I can tell that it's a float array, without specifying the dimension (for example 2d for a matrix) or better, specifying its dimension is (n,p) where n and p are both type variables.