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For larger databases, using export_timeseries_data() on a ixmp.Platform object can take multiple hours.
With this in mind, it would be very beneficial to log some feedback or show a progress bar, such that users can at least tell what is going on and whether anything is going wrong or not while waiting.
The text was updated successfully, but these errors were encountered:
# TODO: replace with passing list of models/scenarios
# to the method above
run_ids= [s['run_id'] forsinscen_list
if (len(scenarios) ==0ors['scenario'] inscenarios)
and (len(models) ==0ors['model'] inmodels)]
self.jobj.exportTimeseriesData(to_jlist(run_ids),
to_jlist(variables),
to_jlist(units),
to_jlist(regions),
str(path))
To display a progress indicator, the Python side / CLI code would require some kind of state variable(s) to be synchronized & checked, while that Java function continued running, i.e. this would need to be multi-threaded, something we currently don't do anywhere. Not impossible, but would require more advanced code than we currently have.
For larger databases, using
export_timeseries_data()
on aixmp.Platform
object can take multiple hours.With this in mind, it would be very beneficial to log some feedback or show a progress bar, such that users can at least tell what is going on and whether anything is going wrong or not while waiting.
The text was updated successfully, but these errors were encountered: