Ryan Patet

Thank you - I can confirm Chiragasourabh's solution removing the Replace statement from my push worked. I have not tried Kin How's solution, yet.

I have used DataLab to create and push Conditions in a Workbook based on signal properties. I am not pushing this in as a formula, but rather using Start and End times calculated in DataLab. In developing my code, I've ended up with multiple Conditions with the same name. I can ultimately find the correct one which I pushed in, but would like to "Delete" or "Archive" those incorrect Conditions. I have been able to achieve this with Signals by setting the Archived parameter to True. I would like to do the equivalent for my conditions. My attempt, which does not seem to be working, is as follows: condition_df = spy.search('worksheet_url') condition_df.set_index('Name', inplace=True, drop=False) condition_df['Maximum Duration'] = '1mo' condition_df['Archived'] = True spy.push(metadata=condition_df, replace={'Start': start_time, 'End': end_time}, workbook=workbook_id) This deletes all capsules in my date range, but if I search for my conditions in the Data tab, the attempt to archive these conditions does not seem to have worked.

Thank you, Mark. Read through the docs but missed that paragraph when reading through. Knowing that it was in there helped me find it - and your solution sped up the data push, as expected.

I am using Seeq DataLab to pull in data from multiple processing units running in parallel. I am assessing the states of each of these units, and building a set of capsules for when each individual unit is running. I then am pushing these capsules as a condition back into a workbook. I am able to successfully achieve this using a for loop and using separate data pushes for each unit. I find that the time for the data to push back to the Workbook takes the longest, and was curious to see if I could do one large push of Conditions for all unit ops at once, rather than having to do separate pushes for each unit? I have done this for multiple Signals in the past, but cannot find documentation for a way to do it with multiple Conditions. Below is a concatenated version of the code I am currently running using the for loops: for index in range(len(state)): ... capsule_bounds = pd.DataFrame({'Capsule Start': start_list, 'Capsule End': end_list, 'Batch ID': batch_id_list}) spy.push(data=capsule_bounds, metadata=pd.DataFrame([{ 'Name': 'Unit '+[index]+' Condition', 'Type': 'Condition', 'Maximum Duration': max_dur}]), replace={'Start': start_time, 'End': end_time}, workbook=workbook_id)