FWIW, I used MathCAD extensively around that period while in grad school (I taught physics lab courses that were 100% structured around MathCAD workflows).
I hated it, and Jupyter is explicitly informed by that experience. So it's not like MathCAD very much by design, not by lack of knowledge.
We acknowledge there's a lot to improve in Jupyter, and some discussions in this post make excellent points (many of which we'd like to make progress on in the future). But the Jupyter team did probably use most/all of the modern scientific computing platforms, MathCAD included (and Maple, Mathematica, IDL, Matlab, Gnuplot, ...) at some point in our careers. We typically make our choices with reasonably good knowledge of the landscape.
We make mistakes, or our tradeoffs may be different than the optimal ones for your use case. But lack of knowledge of these tools is rarely the reason :)
+1 to the team that's been doing a phenomenal job on the project... These days I'm just an email answering machine :)
But yes, JLab is shaping up quite nicely, opening up a lot of interesting possibilities. For advanced users/early adopters I think it's time to start playing with it (and filing issues for anything that's broken/sub-optimal, we really want to provide a great user experience with it once we hit 1.0).
And btw, it's worth mentioning that in JupyterLab, we just merged a PR that will make embedding the Monaco editor (the editing component of VS code) much easier: https://github.com/jupyterlab/jupyterlab/pull/1140.
We all want stronger editing capabilities, but it doesn't make sense for the Jupyter team to get into the business of writing text editors (plenty of better folks doing a great job on that already). So we're just trying to make it easier to integrate other text editors into the everyday workflow.
We acknowledge there's a lot to improve in Jupyter, and some discussions in this post make excellent points (many of which we'd like to make progress on in the future). But the Jupyter team did probably use most/all of the modern scientific computing platforms, MathCAD included (and Maple, Mathematica, IDL, Matlab, Gnuplot, ...) at some point in our careers. We typically make our choices with reasonably good knowledge of the landscape.
We make mistakes, or our tradeoffs may be different than the optimal ones for your use case. But lack of knowledge of these tools is rarely the reason :)