When you change a dataset type, this has implications for the entire set, as different datatypes have different components to store. E.g labelcheck stores quantfilechannel, other datatypes store samplesheet. That and acquisition etc.
Make it either impossible to change the datatype if e.g samples or other components have already been stored, or very hard with warnings etc - but correct so it removes the old stuff!
I am leaning towards that it would be better to delete a dataset and release its files, and create a new dataset, instead of allowing the old dataset to change its type.
Anyway, right now datatype changes error on a faulty old_dtcs = existing_dtcstates.get(dtcomp__component_id=...) call (wrong name of FK, there is no _id since it is an Integer with choices)
When you change a dataset type, this has implications for the entire set, as different datatypes have different components to store. E.g labelcheck stores quantfilechannel, other datatypes store samplesheet. That and acquisition etc.
Make it either impossible to change the datatype if e.g samples or other components have already been stored, or very hard with warnings etc - but correct so it removes the old stuff!
I am leaning towards that it would be better to delete a dataset and release its files, and create a new dataset, instead of allowing the old dataset to change its type.
Anyway, right now datatype changes error on a faulty
old_dtcs = existing_dtcstates.get(dtcomp__component_id=...)call (wrong name of FK, there is no_idsince it is an Integer with choices)