One solution for you problem would be to use docker to develop and deploy your project.
You can define all your dependencies, create your project and build a docker image with them. With this image, you can be sure that anyone who is using it, will have the same infrastructure like yours.
It shouldn't take you a lot of time to learn docker and it will help you in the future.
An analytic task has been given to me to solve it by python and return back the result to the technical staff. I was asked to prepare the result in a jupyter notebook and such that the resulting code would be fully runnable and documented.
Honestly, I just started using jupyter notebook and generally found it pretty useful and convenient in generating reports integrated with codes and figures. But I had to go into some level of difficulty when I wanted to use specific packages like graphviz and dtreeviz, which was beyond doing a simple pip install xxx.
So, how should I make sure that my code is runnable when I do not know what packages are available at the destination Jupyter notebook of the next guy who wants to run it or when they want to run it using a Jupiter Lab? especially regarding these particular packages!
How to make sure my jupyter notebook is runnable on any other computer or on any jupyter Lab?