Jupyter中R内核崩溃无法自动重启求助（Mac OSX环境）

Hey there, sorry to hear your R kernel in Jupyter’s throwing that "died and can’t restart" error—let’s troubleshoot this step by step to get it back up and running.

1. Refresh Anaconda & Re-register the R Kernel #

First, let’s make sure your conda environment and IRkernel are intact:

• Open Terminal, and activate your conda environment (skip if using the base environment):

  conda activate your_environment_name
  

• Update conda to ensure all packages are up to date:

  conda update conda
  

• Reinstall the IRkernel package to fix any corrupted files:

  conda install -c r r-irkernel --force-reinstall
  

• Then, re-register the R kernel with Jupyter: Open an R session (either via Anaconda Navigator or run R in Terminal), and run this command:

  IRkernel::installspec()
  

Close all Jupyter windows and restart it to test.

2. Check for R Version & System Dependency Issues #

Mac OS updates or version mismatches often cause kernel crashes:

• Verify your current R version in Terminal:

  R --version
  

• Compare it to the R version in your conda environment:

  conda list r-base
  

If there’s a mismatch or you suspect a version conflict, install a stable, compatible R version (e.g., 4.2.0 is widely tested):

conda install -c r r-base=4.2.0

• Also, ensure you have Xcode Command Line Tools installed (many R packages depend on this):

  xcode-select --install
  

Follow the prompts to install if it’s missing.

3. Clear Jupyter Cache & Corrupted Kernel Configs #

Sometimes stale kernel files cause issues:

• Close all Jupyter instances first.
• List all installed kernels to find the R kernel path:

  jupyter kernelspec list
  

You’ll see a line like /Users/your_username/Library/Jupyter/kernels/ir—copy that path.

• Delete the corrupted kernel directory:

  rm -rf /Users/your_username/Library/Jupyter/kernels/ir
  

• Re-register the kernel again (same as step 1: open R and run IRkernel::installspec(user = TRUE)).

4. Test in a Clean Conda Environment #

If your main environment has conflicting packages, test with a fresh one:

• Create a new environment with minimal dependencies:

  conda create -n test_r_env r-base r-irkernel jupyter
  

• Activate the new environment:

  conda activate test_r_env
  

• Launch Jupyter and create a new R notebook. If this works, your original environment has package conflicts—you can either rebuild it or migrate your work to the new environment.

5. Dig into Crash Logs for Exact Errors #

If none of the above works, check the kernel crash logs to pinpoint the issue:

• Find Jupyter’s data directory:

  jupyter --paths
  

Look for the data path (e.g., ~/Library/Jupyter/data).

• Navigate to the runtime folder inside that directory—you’ll find files named like kernel-xxxx.json. Open these files to see specific error messages (e.g., a missing R package or library conflict). Share these details if you need further help!

内容的提问来源于stack exchange，提问作者Abdullah