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Is your feature request related to a problem? Please describe.
Given a (running or complete?) batch task, it is unclear if all of the jobs have returned all bitstrings and no further query to remote is needed
Describe the solution you'd like
job.status() for batchtask, with the same functionality as for single tasks
Describe alternatives you've considered return np.logical_and([task.status() for task in job.tasks])
The text was updated successfully, but these errors were encountered:
In general the status of the tasks is not simply just Queued and Completed there are actually around 8 possible states a task can be in so its hard to map communicate the general status of the batch in a single status. One thing you can do is filter a batch by status codes, e.g. if I want just completed tasks I can filter based on Completed status:
also batch.tasks_metric() returns a pandas Dataframe that contains the current knowledge of the tasks in the batch so you can get more fine grain information about the batch from that object.
Additionally, if the task report already has all bitstring measurements accounted for, there would be no need to query remote
Thanks, we've already thought of that so we're all set!
Is your feature request related to a problem? Please describe.
Given a (running or complete?) batch task, it is unclear if all of the jobs have returned all bitstrings and no further query to remote is needed
Describe the solution you'd like
job.status() for batchtask, with the same functionality as for single tasks
Describe alternatives you've considered
return np.logical_and([task.status() for task in job.tasks])
The text was updated successfully, but these errors were encountered: