azureml-dataprep-native

# Install azureml-dataprep-native to make its native components available. # Users typically interact with the higher-level azureml.dataprep or # azureml.core.Dataset APIs, which leverage this package internally. # No direct user-facing imports are typically made from azureml-dataprep-native. # To use data prep functionality, install azureml-dataprep: # pip install azureml-dataprep # Example of how functionality (implicitly powered by this library) is accessed: import pandas as pd from azureml.dataprep import read_csv, Dataflow import os # Create a dummy CSV file csv_content = "id,name\n1,Alice\n2,Bob\n3,Charlie" with open("sample.csv", "w") as f: f.write(csv_content) # Read data using azureml.dataprep (which uses azureml-dataprep-native internally) # This code will only run if azureml-dataprep is also installed. # To run this code, ensure you have: pip install azureml-dataprep try: dataflow: Dataflow = read_csv("sample.csv") print("Dataflow created successfully (backed by azureml-dataprep-native).") # Further operations would typically follow, e.g., dataflow.to_pandas_dataframe() # For demonstration, let's just show the schema print(dataflow.get_profile().schema_summary) except ImportError: print("azureml-dataprep not installed. Please install it to use data prep features:") print("pip install azureml-dataprep") except Exception as e: print(f"An error occurred during data prep operation: {e}") finally: # Clean up the dummy file if os.path.exists("sample.csv"): os.remove("sample.csv") print("\nazureml-dataprep-native is primarily an underlying dependency.")