SageMaker Studio Python Library

import os
from sagemaker_studio import ClientConfig, Domain, Project

# --- Configure ClientConfig if not in SageMaker Studio JupyterLab ---
# In a SageMaker Studio JupyterLab environment, credentials are automatically pulled.
# Otherwise, provide AWS credentials and region.
# Replace 'us-east-1' and 'your-aws-profile' as needed.
# For demonstration, we use os.environ.get for robustness.
aws_region = os.environ.get('AWS_REGION', 'us-east-1')
aws_profile = os.environ.get('AWS_PROFILE', 'default')

# Instantiate ClientConfig (optional, if running outside of Studio or with specific profile)
try:
    client_config = ClientConfig(region_name=aws_region, profile_name=aws_profile)
except Exception as e:
    print(f"Could not initialize ClientConfig, proceeding assuming environment provides credentials: {e}")
    client_config = None # Or handle more robustly

# --- Interact with a SageMaker Domain and Project ---
# To interact with a Domain or Project, you typically need its ID.
# Replace 'your-domain-id' and 'your-project-id' with actual values.
# If running in Studio, these might be discoverable from the environment.
domain_id = os.environ.get('SAGEMAKER_DOMAIN_ID', 'd-xxxxxxxxxxxx') # Placeholder
project_id = os.environ.get('SAGEMAKER_PROJECT_ID', 'p-yyyyyyyyyyyy') # Placeholder

print(f"Attempting to interact with Domain ID: {domain_id}")
print(f"Attempting to interact with Project ID: {project_id}")

if client_config:
    # Initialize Domain with client_config
    domain = Domain(id=domain_id, client_config=client_config)
    project = Project(id=project_id, domain_id=domain_id, client_config=client_config)
else:
    # Initialize Domain without client_config (assumes environment provides)
    domain = Domain(id=domain_id)
    project = Project(id=project_id, domain_id=domain_id)

# Accessing some properties (these calls might fail if IDs are invalid or permissions are insufficient)
try:
    print(f"Domain ID: {domain.id}")
    print(f"Project Name: {project.name}")
    print(f"Project S3 Path: {project.s3_path}")
except Exception as e:
    print(f"Error accessing domain/project properties: {e}")
    print("Please ensure the provided Domain/Project IDs are valid and your AWS credentials/permissions are correctly configured.")

# Example of using a utility module (requires an actual connection and query context)
# from sagemaker_studio import sqlutils
# try:
#     result = sqlutils.sql("SELECT 1", connection_name="your-connection-name")
#     print(f"SQL Query Result: {result}")
# except Exception as e:
#     print(f"Error executing SQL query: {e}")