Python Notebook does not respect pipeline input parameter

[afataconsulting]

Hi,

I'm encountering an issue when running a Python notebook through a Fabric pipeline. When I run the notebook manually in the workspace, everything works fine: it correctly loads the Excel file from SharePoint using the sheet name I provide.

However, when I run the same notebook via a pipeline, the execution fails with this error:

ValueError: Worksheet named 'Sheet1' not found

This shows that the sheet parameter is not correctly passed to the notebook inside the pipeline context — it seems to default to "Sheet1", even though "Sheet2" is clearly defined in the pipeline input parameters (see attached screenshots).

Expected behavior:
The notebook in the pipeline should honor the runtime parameter and use "Sheet2" as provided, instead of defaulting to "Sheet1".

Environment:
- Microsoft Fabric (Trial version)
- Python 3.11 notebook 
- Excel file hosted on SharePoint

[BhaveshPatel]

 For that, You should use Dataflow Gen 2 rather than Fabric Data Factory.

Here is a quick view

Easy to implement and all is available:

[afataconsulting]

Hi @AmiGarala and thank you for your quick response.
Placing the configured cell at the very top fixed my issue, there was also a misnamed parameter. Thanks again.

[AmiGarala]

1. Check Notebook Parameter Cell Format
Your notebook must have a parameter cell defined like this at the top:

# Parameters
sheet_name = "Sheet1" # default value
Fabric uses this cell to inject pipeline parameters. If this is missing or misnamed, the pipeline cannot override it.

Make sure:

The variable name (sheet_name) matches exactly with the name used in the pipeline.

The cell is tagged with "parameters" (Fabric auto-detects this if you're using the right format).

2. Ensure the Pipeline Is Passing the Parameter
In your pipeline:

Go to the notebook activity block.

Click on the "Settings" pane.

Confirm:

Input parameter name is sheet_name (case-sensitive match).

Value is set to Sheet2.

Optional sanity check: Add a debug cell to your notebook to log it:
print(f"Using sheet name: {sheet_name}")

3. Double-Check Parameter Mapping in JSON Behind the Scenes (Optional)
If you're comfortable editing JSON:

Open the pipeline JSON (if accessible via export or dev mode).

Look for something like:

"notebookActivity": {
"parameters": {
"sheet_name": "Sheet2"
}
}

4. Avoid Hardcoded Values in Notebook
Sometimes developers accidentally override the parameter later in the notebook:

sheet_name = "Sheet1" #  This will override pipeline input
Make sure this line appears only in the parameter cell and not anywhere else.