3D models are being stored in a Google Drive folder, 3D models. We want to feed those into a model training pipeline. Tooling is in Python so we want a Python solution.
For contexts besides just JupyterLab, there is pydrive, licensed under Apache. "PyDrive is a wrapper library of google-api-python-client that simplifies many common Google Drive API tasks." The documentation starts at Welcome to PyDrive’s documentation!. There seem to be many developers yet only 58 commits; that seems odd.
There is also gdrive_python but that's the effort of just a solo developer with only 43 commits.
3D models are being stored in a Google Drive folder, 3D models. We want to feed those into a model training pipeline. Tooling is in Python so we want a Python solution.
I've done this on Colab before: External data: Local Files, Drive, Sheets, and Cloud Storage: Google Drive. It is really easy. Scot raised a good point though: that solution may only work on Colab. We need to test that. There are other Python based solutions if that does not work for us.
For JupyterLab (used in Hypnowerk), there is jupyterlab-google-drive is a JupyterLab extension, licensed under BSD with over 500 commits. There is a how to article, Integrate JupyterLab with Google Drive.
For contexts besides just JupyterLab, there is pydrive, licensed under Apache. "PyDrive is a wrapper library of google-api-python-client that simplifies many common Google Drive API tasks." The documentation starts at Welcome to PyDrive’s documentation!. There seem to be many developers yet only 58 commits; that seems odd.
There is also gdrive_python but that's the effort of just a solo developer with only 43 commits.