One possible workaround is to download the delta lake files to a tmp-dir and read the files using python-delta-rs with something like this:
from azure.storage.blob import BlobServiceClient
import tempfile
from deltalake import DeltaTable
def get_blobs_for_folder(container_client, blob_storage_folder_path):
blob_iter = container_client.list_blobs(name_starts_with=blob_storage_folder_path)
blob_names = []
for blob in blob_iter:
if "." in blob.name:
# To just get files and not directories, there might be a better way to do this
blob_names.append(blob.name)
return blob_names
def download_blob_files(container_client, blob_names, local_folder):
for blob_name in blob_names:
local_filename = os.path.join(local_folder, blob_name)
local_file_dir = os.path.dirname(local_filename)
if not os.path.exists(local_file_dir):
os.makedirs(local_file_dir)
with open(local_filename, 'wb') as f:
f.write(container_client.download_blob(blob_name).readall())
def read_delta_lake_file_to_df(blob_storage_path, access_key):
blob_storage_url = "https://your-blob-storage"
blob_service_client = BlobServiceClient(blob_storage_url, credential=access_key)
container_client = blob_service_client.get_container_client("your-container-name")
blob_names = get_blobs_for_folder(container_client, blob_storage_path)
with tempfile.TemporaryDirectory() as tmp_dirpath:
download_blob_files(container_client, blob_names, tmp_dirpath)
local_filename = os.path.join(tmp_dirpath, blob_storage_path)
dt = DeltaTable(local_filename)
df = dt.to_pyarrow_table().to_pandas()
return df