IBM
[Bug] fix dependencies so notebooks run well on Google Colab
Search before asking
- [x] I searched the issues and found no similar issues.
Component
Other
What happened + What you expected to happen
Using v 1.1.0
pip install data-prep-toolkit-transforms[all]==1.1.0 conflicts with Google colab libraries...
see error below.
Let's update our dependencies.
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
google-colab 1.0.0 requires ipykernel==6.17.1, but you have ipykernel 6.29.4 which is incompatible.
google-colab 1.0.0 requires ipython==7.34.0, but you have ipython 8.25.0 which is incompatible.
google-colab 1.0.0 requires tornado==6.4.2, but you have tornado 6.4.1 which is incompatible.
flask 3.1.0 requires blinker>=1.9, but you have blinker 1.8.2 which is incompatible.
notebook 6.5.7 requires jupyter-client<8,>=5.3.4, but you have jupyter-client 8.6.2 which is incompatible.
google-genai 1.7.0 requires anyio<5.0.0,>=4.8.0, but you have anyio 4.4.0 which is incompatible.
google-genai 1.7.0 requires httpx<1.0.0,>=0.28.1, but you have httpx 0.27.0 which is incompatible.
moviepy 1.0.3 requires decorator<5.0,>=4.0.2, but you have decorator 5.1.1 which is incompatible.
torchaudio 2.6.0+cu124 requires torch==2.6.0, but you have torch 2.5.1 which is incompatible.
Reproduction script
Running this notebook on google colab : https://github.com/data-prep-kit/data-prep-kit/blob/dev/examples/notebooks/pdf-processing-1/pdf_processing_1_python.ipynb
Anything else
No response
OS
Other
Python
3.11
Are you willing to submit a PR?
- [ ] Yes I am willing to submit a PR!
@sujee I searched for all of these dependency problems you show above and the culprit for almost all of them (except jupyter- client and torch) is the code_profiler transforms. See the amazing: https://github.com/data-prep-kit/data-prep-kit/blob/dev/transforms/code/code_profiler/requirements.txt.
Since you are using only language and universal transforms (and not the code modules), I think if you
pip install data-prep-toolkit-transforms[language]==1.1.0 this issue could be fixed for your example.
