Forum Discussion
Retrieve column descriptions from semantic models
I'm trying to write a kind of "data glossary" report, where I went to detail all of the column and column descriptions from various reports. I'm trying to use the SemPy library to do this, but can't ...
This works for me:
import sempy.fabric as fabric display(fabric.list_columns("DatasetName"))Well, I don't actually have column descriptions in my test dataset... But if I had, I think they would show here:
Hi Anonymous,
I'd like to suggest you try to use Semantic functions to list all of the workspace items: (it will include the id, name, description, type and workspace id)
import sempy.fabric as fabric
# Get the items of this workspace
workspace_items=fabric.list_items()
# Filter by type to get DataPipeline list
#itemList= workspace_items[workspace_items.Type == "DataPipeline"]
display(workspace_items)
Semantic functions - Microsoft Fabric | Microsoft Learn
Regards,
Xiaoxin Sheng
Thanks OR the response, but that hasn't answered my question. I already have a list of workspaces and semantic models. I can also get the columns that are in the semantic models, but what I'm struggling tog et is the column d3escriptions. Do you know how I can get these?