Set NotebookId dynamically in notebook activity of data pipeline irrespective of Fabric workspace

I believe most of you have come to the situation where a notebook needs to be run from the current workspace. It can easily be done selecting the the current workspace (e.g. DevWorkspace)  and the notebook (e.g. Notebook1) as shown below:

This works perfectly but the issue pops up when the pipeline is deployed to another workspace (e.g ProdWorkspace). There is no Fabric deployment rule available a data pipeline to overwrite workspace from "DevWorkspace" to "ProdWorkspace" at the time of writing this post. 

Setting Fabric workspace dynamically in pipeline activity is easier with the availibility of system variable

@pipeline().DataFactory . 

 

 

There is no inbuilt function available to set NotebookId dynamically. We could set fixed NotebookId of Notebook1 in DevWorkspace but the NotebookId for the same Notebook would be different in ProdWorkspace.

Until there is a proper solution from Microsoft to tackle this issue, we need to build our own solution to set NotebookId dynamically irrespective of the workspace the pipeline runs in. 

 

I am going to explain in 3 steps how I have achieved this so that deployment to different workspace goes smooth. 

Background:

- Created Workspace DevWorkspace and ProdWorkpace 

- Created Lakehouse LH_BRONZE, LH_SILVER and LH_GOLD (Medallian architecture)

- Created Notebook1 and Notebook2 which need to be run dynamically in DevWorkspace and ProdWorkspace

 

 

Step 1: Create a notebook with name Notebook_config under DevWorkspace and written PySpark code to list all the fabric items in the "DevWorkspace" and store the information as a delta table "WorkspaceItems" in the bronze lakehouse.

 

Cell1# set default lakehouse to LH_BRONZE. This must be first cell in the notebook.

%%configure -f
{ 
    "defaultLakehouse": {
        "name": "LH_BRONZE",
    }
}​

Cell2# list workspace items and insert into delta table

import pandas as pd
import sempy.fabric as fabric
from pyspark.sql.functions import *
from delta.tables import *

client = fabric.FabricRestClient()

workspaceId = fabric.get_workspace_id()

response = client.get(f"/v1/workspaces/{workspaceId}/items")

pd_df = pd.json_normalize(response.json()['value'])

spark.sql("SET spark.databricks.delta.schema.autoMerge.enabled = true") 

df_source = spark.createDataFrame(pd_df)

target_table_path = f"Tables/WorkspaceItems"

if DeltaTable.isDeltaTable(spark, f"{target_table_path}"):
    print("The Table already exists so merging data...")
    targetDeltaTable = DeltaTable.forPath(spark, target_table_path)
    (targetDeltaTable.alias("t")
        .merge(df_source.alias("s"), "s.id = t.id")
        .whenMatchedUpdateAll()
        .whenNotMatchedInsertAll()
        .whenNotMatchedBySourceDelete()
        .execute()
    )     
else:
    print("Creating new table and inserting data...")
    df_source.write.format("delta").mode("append").save(f"{target_table_path}")

After the successful run of Notebook_config, Delta table WorkspaceItems is created and loaded with all the fabric items including NotebookIds of Notebook1 and Noteboook2 from the DevWorkspace as shown below:

Step 2: Create a Data pipeline with name p_set_variables which will return NotebookIds of Notebook1 and Notebook2 using pipeline activities Lookup, Filter and set variables as shown below:

        Fig: p_set_variables data pipeline with return variables

        Fig: Lookup setting

        Fig: Filter Notebook1 setting

        Fig: Filter Notebook2 setting

         Fig: Set variable settings as Pipeline return value

Step 3: Create a Data pipeline with name p_demo_pipeline1 where Notebook1 and Notebook2 need to be run. You need to add Invoke pipeline (legacy) and invoke the data pipeline p_set_variable (step 2) which returns the NotebookIds of Notebook1 and Notebook2 as Pipeline return values. 

        Fig: Invoking p_set_variables 

        Fig: Setting run Notebook1 dynamically using Workspace Id and Notebook Id. 

        Fig: Setting run Notebook2 dynamically using Workspace Id and Notebook Id.