Please post the most simple example loading a .csv into a table

[campopianoa]

To get a CSV file into a datatable (where each row in the CSV becomes a row in the datatable), I use Pandas. This is one way to do it (server-side only).

Please see this post which reads a CSV media file into a Pandas dataframe:

Return a media file (CSV) using uplink

I think you’re already doing the right thing! Pulling a CSV file out of a database and then loading it into Pandas in four lines of Python isn’t bad going. If you really want to, you can trim a couple of lines by using BytesIO rather than StringIO. I’d do something like: my_media=app_tables.my_table.get(...)['media_column'] df = pd.read_csv(io.BytesIO(media.get_bytes()), ...) I think two lines is plenty concise

Please see this post that shows how to add rows to the datatable based on a Pandas dataframe:

Add_row to data table

Absolutely to this part of the question. You can do: my_dict={'my_column_1': 'my_value_1', 'my_column_2': 'my_value_2'} app_tables.my_table.add_row(**my_dict) This is assuming you have those columns in your data table (or you have “auto-create missing columns when adding rows checked”). If you have a single dictionary with lists as values, perhaps you could convert to a list of dictionaries and then add rows using the code above in a loop. For example, if you have Pandas: import pandas a…

So, if your CSV is stored as a media object in a datatable, you should be able to use the first post to put it into a Pandas dataframe, The second post shows how to convert the dataframe to a list of dicts and how to use that list to populate a datatable.

I think this is what you are asking for but please clarify if I’ve got it wrong.