My team has a similar library called Loman, which we open-sourced. Instead of nodes representing tasks, they represent data, and the library keeps track of which nodes are up-to-date or stale as you provide new inputs or change how nodes are computed. Each node is either an input node with a provided value, or a computed node with a function to calculate its value. Think of it as a grown-up Excel calculation tree. We've found it quite useful for quant research, and in production it works nicely because you can serialize entire computation graph which gives an easy way to diagnose what failed and why in hundreds of interdependent computations. It's also useful for real-time displays, where you can bind market and UI inputs to nodes and calculated nodes back to the UI - some things you want to recalculate frequently, whereas some are slow and need to happen infrequently in the background.

[1] Github: https://github.com/janushendersonassetallocation/loman

[2] Docs: https://loman.readthedocs.io/en/latest/

[3] Examples: https://github.com/janushendersonassetallocation/loman/tree/...