Here is a workaround to access data from OneLake in Azure ML.

It uses Python and Notebooks to read data from OneLake.

  1. Create a compute instance alt text

  2. From Notebooks create a new .py file or .ipynb. Use the following code: https://learn.microsoft.com/en-us/fabric/onelake/onelake-access-python#sample alt text

  3. You can get “myWorkspace” and “myLakeHose” from the Lakehouse properties URL. The URL is formatted as follows: https://onelake.dfs.fabric.microsoft.com/myWorkspace/myLakehouse/Files alt text alt text                                  

  4. To run the code in Notebooks, open a terminal and attach it to your compute. alt text

  5. In the command line. install Azure storage and Azure identity packages:$pip install azure-storage-file-datalake azure-identity

  6. Navigate to the location of your Python file: For example: $cd ~/cloudfiles/code/Users/admin

  7. The code uses Default credentials of the logged in user from the command line. Login using using: $az login --identity

  8. Make sure the logged in user has access to the files in the Fabric Lakehouse

  9. Run the Python file to list the files in the OneLake/Files directory: $python ./onelake.py

  10. If it succeeds, you should see the files listed: alt text