Watermark fails to recognize all project used libraries

[gloriamacia]

I find Colab pre-installed libraries convenient as well as AWS Sagemaker pre-defined kernels but this convenience becomes very annoying when gathering the requirements.txt file as I end up with many libraries I have not actually used in my project. I know I could create a virtual at the very beginning but I am wondering if there is a way to avoid it.

I have recently discovered watermark which partially solves this issue. Nevertheless, for this solution to be a perfect fit it still has two issues that I will exemplify below and that you can easily reproduce in Colab.

!pip install fastai --upgrade
!pip install voila
!jupyter serverextension enable voila --sys-prefix
!pip install watermark
from fastai.vision.all import *
from fastai.vision.widgets import *
%load_ext watermark
%watermark --iversion  

Neither fastai nor voila appear in the output as I am not running import fastai and loading voila as an extension.

%watermark -p fastai

This would return the correct output for e.g. fastai but I would like to be able to generate automatically without having to manually check for the missing packages.

[rasbt]

Thanks for the feedback!

I agree that this is currently an issue. I looked into this a few months ago but couldn't find an obvious way to make it work, yet. Would be great if someone has some ideas for how to address this

[d-kleine]

the issue with the packages (fastai) has been fixed with #94 , the other issue (voila) is the extensions, that seem to be not (yet) covered by watermark

[rasbt]

Thanks for the note. It looks like the voila call is a terminal shell call outside Python, so that would be out of scope for watermark. But Python packages should be all supported now :)