Call one notebook from another with parameters

[VickyDev18]

I have this simple notebook to load data from an xlsx file in a lakehouse to a delta table in the Lakehouse. 

How can I make this reusable/parameterized so I call it from another notebook and pass parameters and how exactly would I call it from another notebook?

import pandas as pd

source_path = "/lakehouse/default/"
source_file_name = "Files/Test.xlsx"
sheet_name = "Test"
destination_table = "test"

# Read Excel data into a Pandas DataFrame
df = pd.read_excel(source_path + source_file_name, sheet_name=sheet_name)

# Convert Pandas DataFrame to Spark DataFrame
df_spark = spark.createDataFrame(df)

# Save Spark DataFrame as a Delta table
df_spark.write.mode("overwrite").format("delta").saveAsTable(destination_table)

I am aware of how to call a parameterized notebook from a pipeline How to Pass Parameters from Pipelines to Notebooks in Microsoft Fabric! - YouTube. 

However, I want to know if we can call the notebook from another notebook. 

[HimanshuS-msft]

Hello @VickyDev18 , 

Its me again. Have you tried using this 

from notebookutils import mssparkutils

mssparkutils.notebook.runMultiple(["aaa"])

[Anonymous · Accepted solution]

Hi @VickyDev18 
Thanks for using Fabric Community.
You can call one notebook from another notebook using %run command. I have created a repro of the same but instead I used a CSV file. I have attached the screenshots of the code.

Functions is my child notebook where I am defining a function to create a table inside lakehouse using the data inside a CSV file.

I am calling this notebook from another notebook:

The table got created in the lakehouse.

Hope this helps. Please let me know if you have any further questions.

[VickyDev18]

I had tried this method but for some reason it wasn't working. However, now that I tried it again, it worked! 

Only simplified approach I tried was to just call the function directly without the 2nd function. 

So overall the approach was:-

1. Create a Notebook called Functions with code below. 

import pandas as pd

def load_excel(source_path, source_file_name, sheet_name, destination_table):

    # Read Excel data into a Pandas DataFrame
    df = pd.read_excel(source_path + source_file_name, sheet_name=sheet_name)

    # Convert Pandas DataFrame to Spark DataFrame
    df_spark = spark.createDataFrame(df)

    # Save Spark DataFrame as a Delta table
    df_spark.write.mode("overwrite").format("delta").saveAsTable(destination_table)

2. Create a new Notebook and call the function above using the code below

%run Functions

#load_excel(source_path, source_file_name, sheet_name, destination_table)
load_excel("/lakehouse/default/Files/", "Test.xlsx", "Test", "test")

[Anonymous]

Hi @VickyDev18 
Thanks for sharing your approach here. Glad that your query got resolved. Please continue using Fabric Community for any help regarding your queries.

[Anonymous]

Hi @VickyDev18 
We haven’t heard from you on the last response and was just checking back to see if you have a resolution yet. Otherwise, will respond back with the more details and we will try to help.
Thanks