Question
You manage an Azure Machine Learning workspace named workspace1 by using the Python SDK v2. You create a General Purpose v2 Azure storage account named mlstorage1. The storage account includes a publicly accessible container named mlcontainer1. The container stores 10 blobs with files in the CSV format.
You must develop Python SDK v2 code to create a data asset referencing all blobs in the container named mlcontainer1.
You need to complete the Python SDK v2 code.
How should you complete the code? To answer, select the appropriate options in the answer area.
```python
sample_dataset = Data(
path=[Dropdown 1]://mlstorage1.blob.core.windows.net/mlcontainer1,
type=AssetTypes.[Dropdown 2],
description="sample_dataset",
name="sample_dataset",
version='1.0'
)
```
Explanation
Dropdown 1: wasbs is the documented URI scheme for Azure Blob Storage paths on the blob.core.windows.net endpoint. abfss is for ADLS Gen2 paths on the dfs.core.windows.net endpoint, and azureml is used for datastore and asset references, not a direct storage account URL.
Dropdown 2: the data asset must reference all 10 blobs in the container, so it points at a folder and uses URI_FOLDER, the type documented for reading a folder of CSV files into pandas or Spark. URI_FILE references a single file, and the table type requires an MLTable blueprint, which the scenario does not have.
