Microsoft Fabric in PythonSend data to Fabric, read it back, send and receive events, and read the results of notebooks and pipelines, all from Python services.
Start here if this is your first Fabric connection - create it and read rows from a lakehouse table in a service.
TutorialTutorial Create the connection and read rows from a lakehouse table in a Python service. Writing to Fabric Append new rows, replace small tables whole, load files that are already in the lakehouse and write files to it. Reading from Fabric Pass values into queries and read totals for reports. Events Send events to an eventstream, run a service for each event Fabric raises and read recent events from an eventhouse. Notebooks and pipelines Run a notebook and read what it wrote, run a pipeline and refresh a report, and let Fabric read your own systems. Tables write_table, load_table, list_tables and wait_for_operation, with every parameter. Queries query and refresh_sql_endpoint on the SQL analytics endpoint, query_events on an eventhouse, run_spark, open_spark_session and close_spark_session on Spark. Events The Kafka and REST connections for an eventstream endpoint, every field of each. Files onelake_list, onelake_read, onelake_write and onelake_delete, and the two forms a file path takes. Jobs run_job, wait_for_job, get_job and cancel_job, the job types for notebooks, pipelines and report refreshes, and the statuses. Connection The Dashboard fields, how tokens are obtained and refreshed, invoke for endpoints without a method of their own, and ping. Workspaces list_workspaces, get_workspace, list_items and get_item, plus shortcuts and capacities.