Kind of request
None
Enhancement Description
As you probably know, numba allows caching the njit compiled version of a function so that it doesn't have to be compiled next run.
I would like to ask whether it would be good to turn on this caching in pyflwdir. If you think so, I am happy to make a PR for this.
Use case
Models go brrr
GEB uses pyflwdir during model initalization. The repeated compilation is currently about 2/3 of model initializaton in small test regions that we use for debugging (the impact is of course much smaller in large regions).
Additional Context
No response
Kind of request
None
Enhancement Description
As you probably know, numba allows caching the njit compiled version of a function so that it doesn't have to be compiled next run.
I would like to ask whether it would be good to turn on this caching in pyflwdir. If you think so, I am happy to make a PR for this.
Use case
Models go brrr
GEB uses pyflwdir during model initalization. The repeated compilation is currently about 2/3 of model initializaton in small test regions that we use for debugging (the impact is of course much smaller in large regions).
Additional Context
No response