The kernel appears to have died. It will restart automatically.
The Jupyter kernel process crashed — usually out of memory or a native library crash.
Exact message you may see
The kernel appears to have diedKernel Restarting
Seen on:
Python
Meaning
Large DataFrames/models exceeding RAM, segfaults in C extensions (TensorFlow, PyTorch builds), or incompatible library versions kill the kernel without a Python traceback.
Common causes
- Out of memory
- Native extension crash / incompatible binary
- CPU instruction set unsupported by a library build
⚡ Quick fix
- Watch memory and reduce data size
- Run the cell as a script to see the real error
- Reinstall/upgrade the crashing library in the same environment
Detailed fix by platform
Python
python -X faulthandler script.pyshows where a native crash happens
How to diagnose
- Memory — Does RAM spike before the crash?
- Isolation — Which import/cell triggers it?
🔧 Still not fixed?
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Last updated 10 Oct 2026