Open Selkubi opened 2 months ago
Current status: The lambda function Magno sent works with the S3Access tests but the setup does not work when data is actually uploaded to the S3 bucket.
The function no.1 now works by itself with the tests but the access error is persistent. Magno is looking into that.
Status Update: The function is working up until the "+,+,+_octant" column. Here there need to be a naming convention agreement. The original csv files comes with "+,+,+_octant". But, when I convert the the example_dataset xlsx file @akalikadien sent to a csv, this double quote is deleted and delimiter is switched to ";" (this is spesific to my pc maybe?) But then, I can take in the column names without any problems.
So the question is should I proceed with the "+,+,+_octant" column name and "," as the delimiter or just switch to +,+,+_octant as column name and ";" as the delimiter?
Some notes on what to consider after the handover of the function
I have completed the conversion of the first lambda function (attached as txt since .py is not accepted). For now it passes a test event of "clean_Rh_ligand_NBD_DFT_descriptors_v9.csv" file upload. aws_S3_to_dynamodb_function.txt
The function must be triggered when S3 bucket receives new data. And should do the following;
The metadata will be processed the same way once the experiment id is emailed to the user. The user must put the experiment id into the metadata file so that the metadata and the experiment can be matched when they are in DynamoDB