Mount Dataset to Azure Machine Learning Compute Instance

mount_dataset.py

import os
import pandas as pd
from azureml.core import Workspace, Dataset

# Connect to Workspace and reference Dataset
ws = Workspace.from_config()
dataset = ws.datasets["german-credit-train-tutorial"]

# Create mountcontext and mount the dataset
mount_ctx = dataset.mount()  
mount_ctx.start()  

# Get the mount point
dataset_mount_folder = mount_ctx.mount_point
print(dataset_mount_folder)

# List the files in the mount point
files = os.listdir(dataset_mount_folder)
print(files)

# Read some data
df = pd.read_csv(os.path.join(dataset_mount_folder, 'german_credit_data.csv'))

# Do some more stuff with the data....

# Unmount the dataset from the instance
mount_ctx.stop()