Hi guys, I'm using multiprocess executor and launching my pipeline from the jupyter notebook, multiprocess requires me to make my pipeline reconstructable

dagster.reconstructable(mypipeline)

. It works fine, except now I can't reload my pipeline without restarting python, somehow

reconstructable

always returns the same pipeline, any ideas how to force it to reload? Here is what I mean with examples in ipython:

In [1]: import tst_pipe

In [2]: import dagster
In [4]: orig_solids = [s.name for s in tst_pipe.pipe.solids]
   ...: recons = [s.name for s in dagster.reconstructable(tst_pipe.pipe).get_definition().solids]
   ...: print('original', orig_solids)
   ...: print('recons', recons)
original ['c', 'b', 'a']
recons ['c', 'b', 'a']

looks fine, now I add new step to my file and relaunch the same code:

In [5]: orig_solids = [s.name for s in tst_pipe.pipe.solids]
   ...: recons = [s.name for s in dagster.reconstructable(tst_pipe.pipe).get_definition().solids]
   ...: print('original', orig_solids)
   ...: print('recons', recons)
original ['c', 'b', 'd', 'a']
recons ['c', 'b', 'a']

get_definition

is using

@lru_cache

so I believe you can use

cache_clear

on it https://stackoverflow.com/questions/37653784/how-do-i-use-cache-clear-on-python-functools-lru-cache

it works, thanks! had to clear cache for the repository and pipeline

dagster.reconstructable(tst_pipe.pipe).repository.get_definition.cache_clear()

dagster.reconstructable(tst_pipe.pipe).get_definition.cache_clear()