Python 3.11 notebook slow startup when using builtin import

[P_work]

Python 3.11 notebook is slow to startup when using builtin import.  If builtin py file imports are not used, the notebook is orders of magnitude faster startup. Are there no workarounds to handle this? Most of these type of notebooks will be called in pipelines, so not sure if possible to 'warm' or always cold start?

[deborshi_nag]

Hello @P_work 

Use Fabric Environments item to install and govern Python libraries (including your own custom modules) for notebooks. This process gives you repeatability, version control, and attach-at-once behavior across notebooks/Spark job definitions. Keep %pip inline installs for ad‑hoc or exploratory work, not for anything you want to be reliable or reusable.

Use the following rules for custom libraries -

1. Team‑wide, repeatable libraries for notebooks/Jobs

Create a Fabric Environment, add libraries (PyPI/conda, private feed, or custom wheels), and attach it (or set as Workspace default).

2. Quick experiments in a single notebook session

Use %pip install ... in a cell.

3. Your own modules (internal utilities)

Package as a Wheel (.whl) and add it as a custom library in the Environment.

Please refer to the following Microsoft doc reference

Manage Apache Spark libraries - Microsoft Fabric | Microsoft Learn

Hope this helps - please appreciate leaving a Kudos or accepting as a Solution!

[P_work]

I have implented custom environments add found the startup times to be excessively long as well. This is a known issue from what I have seen in the community and will not alleviate long session startups. When anything other than the default environment is used, especially from pipelines, startup times will be orders of magnitude longer.

[v-hjannapu]

Hi @P_work   ,
Thank you for reaching out to the Microsoft Community Forum.If you have tried all the everything and the issue still persists, I suggest you to raise a Microsoft Support ticket,as this would need to be resolved on their end.

Below is the link to help create Microsoft Support ticket:
How to create a Fabric and Power BI Support ticket - Power BI | Microsoft Learn

Regards,
Community support team.

[v-hjannapu]

Hi @P_work ,
Could you please confirm if the issue has been resolved after raising a support case? If a solution has been found, it would be greatly appreciated if you could share your insights with the community. This would be helpful for other members who may encounter similar issues.

Thank you for your understanding and assistance.

[v-hjannapu]

Hi @P_work,

Thank you  for reaching out to the Microsoft fabric community forum.

When a notebook is triggered from a pipeline, it always starts with a fresh session. During startup, Python has to set up the environment and load all imported files. If the notebook is using built-in or shared .py imports, this step takes more time, so the notebook startup feels slow. When those imports are removed, startup becomes faster.

Currently, there is no option to keep the notebook warm or reuse the same session when running from pipelines. Cold start will happen every time.

As a workaround, try to keep only required imports at the top and move other imports inside functions. Also, keep shared utility files as small and simple as possible to reduce startup delay.

Once the notebook starts, execution speed should be normal. The delay is mainly during initialization.

Hope this clarifies the issue.
Regards,
Community Support Team.

[v-hjannapu]

Hi @P_work,
I hope the information provided above assists you in resolving the issue. If you have any additional questions or concerns, please do not hesitate to contact us. We are here to support you and will be happy to help with any further assistance you may need.

Regards,
Community Support Team.