KlongPy has a lot of other features beyond pure NumPy operations (such as IPC and web server), which you could see as a kind of making use of array operations in some application. You could look at the core Klong language as what you suggest.
You can do realtime in the sense that you can build Numpy arrays in memory from realtime data and then use these as columns in DuckDb. This is approach I took when designing KlongPy to interop array operations with DuckDb.
Thanks the insights. Not to over do self promotion, but aside from learning, the main reason I made KlongPy was to allow for optionality with the ecosystem. Use Klong for array operations and other libraries for standard stuff.
Arthur Whitney is showing how to build an array language using C in array language form.
AW is known for kdb+ which is often used in finance due to its extreme performance properties and ability for quants to quickly explore ideas.
Personally, to get a better handle on how array languages worked, I implemented KlongPy which is a python implementation of Klong, which descends from K (which AW wrote).
You have to play with this stuff to understand it intuitively.
Just gonna say, this is why i wrote KlongPy - an array language in Python that lets you interop with Python while also getting some array lang. efficiencies. Klong isn't as smooth as K, but it's still quite useful.