Jupyter Kernel ↔ Environment Synchronization

Pain point

Packages import in a terminal session but fail in a notebook because the notebook is running a different

interpreter than expected.

Repro/diagnostic steps

1. In the notebook, run: `import sys; print(sys.executable); print(sys.prefix)`
2. Compare to the activated environment's `which python` / `python -c "import sys; print(sys.executable)"`.
3. List kernels: `jupyter kernelspec list`.

Root causes (common)

• Jupyter server launched from base/another env.
• Environment exists but ipykernel is not installed/registered.
• Kernelspec points to a moved/deleted interpreter path.

Fix workflow

1. Install kernel support inside the target env: `conda install ipykernel` (or pip in venv).
2. Register kernelspec with a clear name/display-name.
3. Restart Jupyter and explicitly select the intended kernel.
4. Add a "sanity cell" to notebooks that prints sys.executable at runtime.

Expected result

• sys.executable in notebook matches the target environment interpreter.
• Imports behave consistently across shell and notebook.

References

• https://stackoverflow.com/questions/39604271/conda-environments-not-showing-up-in-jupyter-notebook
• https://stackoverflow.com/questions/62329185/modulenotfounderror-in-jupyter-notebook-when-importing-a-module-after-conda-inst
• https://jupyter-client.readthedocs.io/en/5.1.0/api/kernelspec.html