Python 3.11 notebook slow startup when using builtin import

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.