fabric-analytics-notebook-plugin

import pyspark.sql.functions as F # This package is an internal plugin for the Fabric Notebook environment. # Direct import of 'fabric_analytics_notebook_plugin' is not typically done by users. # Instead, users interact with the Fabric environment and built-in utilities like notebookutils. # Example of typical analytics operation in a Fabric Python Notebook # Read data from a Lakehouse table (replace 'YourLakehouse' and 'YourTable' with actual names) # Assume 'spark' object is pre-initialized in Fabric notebooks # You might need to attach a Lakehouse to your notebook first. # Example: Reading a Delta table from the default Lakehouse try: df = spark.read.format("delta").load("Files/YourTable") print(f"DataFrame schema: {df.schema.simpleString()}") df.show(5) # Example using built-in Fabric notebook utilities (formerly mssparkutils) # from notebookutils import mssparkutils # Older syntax, still compatible for now from notebookutils import notebook, fs # List files in the default Lakehouse's 'Files' section print("\nListing files in 'Files/' directory:") files = fs.ls("Files/") for file_info in files: print(f" - {file_info.name} (size: {file_info.size} bytes)") except Exception as e: print(f"Error during quickstart execution: {e}") print("Please ensure you are running this in a Microsoft Fabric Notebook") print("and have a Lakehouse attached with a 'YourTable' Delta table and some files.")