The idea is to keep the amount of global state as low as possible. Pluto.jl creates a dependency graph between cells: If cell A defines foo, and cell B uses foo, then cell B depends on cell A. Whenever cell A is updated, cell B will automatically be re-evaluated.
(edit: I suppose it's not really global state I'm talking about as much as hidden state left over from overwritten or deleted cells)
For example, I typically create tonnes of code cells when I visualize and try to get a sense of some data. The large majority of cells (probably >80%) are then deleted, and whenever I find a trivial bug in some code, I fix the cell where the bug occured.
But now - which cells had I rerun after fixing the bug? And did any of the run cells depend on some variable in a deleted cell? If so, the notebook will no longer be reproducible when I re-run it? It's impossible to keep track of. So when I use Jupyter, I frequently press the "restart kernel and run all" option. But of course, that is slow. So I need to serialize a lot of data, which is troublesome. Pluto completely circumvents that problem.
(edit: I suppose it's not really global state I'm talking about as much as hidden state left over from overwritten or deleted cells)
For example, I typically create tonnes of code cells when I visualize and try to get a sense of some data. The large majority of cells (probably >80%) are then deleted, and whenever I find a trivial bug in some code, I fix the cell where the bug occured.
But now - which cells had I rerun after fixing the bug? And did any of the run cells depend on some variable in a deleted cell? If so, the notebook will no longer be reproducible when I re-run it? It's impossible to keep track of. So when I use Jupyter, I frequently press the "restart kernel and run all" option. But of course, that is slow. So I need to serialize a lot of data, which is troublesome. Pluto completely circumvents that problem.