Jupyter Server: Not Started, No Kernel in VS Code? Here's How to Fix It
Are you trying to use Jupyter Notebooks in VS Code but encountering the dreaded "Jupyter Server: Not Started, No Kernel" error? This frustrating issue can stem from various factors, preventing you from enjoying the interactive environment you're aiming for.
Let's break down the problem and explore common solutions to get your Jupyter Notebook environment up and running smoothly within VS Code.
Understanding the Problem
When you see the "Jupyter Server: Not Started, No Kernel" message, it means VS Code can't establish a connection to a running Jupyter server, leaving you unable to execute code in your notebooks. Think of it as trying to use a remote computer without properly establishing a connection.
Replicating the Scenario
Let's say you've installed the Jupyter extension in VS Code, created a new notebook file, and are ready to start coding. But when you try to run a cell, you're met with the "Jupyter Server: Not Started, No Kernel" message.
Here's a snippet showing the error in VS Code:
Jupyter Server: Not Started, No Kernel
[Error] No Jupyter Server is currently running.
Debugging and Solutions
1. Verify Jupyter Installation
- Check if Jupyter is installed: Open a terminal (cmd or PowerShell on Windows, Terminal on MacOS/Linux) and type
jupyter --version. You should see the version number. If not, you'll need to install it. - Installation: Use
pip install jupyterto install Jupyter.
2. Start the Jupyter Server
- Manual Start: From your terminal, navigate to the directory containing your notebooks and run
jupyter notebook. This will launch a browser window with a Jupyter Notebook dashboard. - VS Code Integration: If you're using the Jupyter extension in VS Code, it often handles server management. Look for a "Jupyter: Start Server" option in the command palette (Ctrl+Shift+P).
3. Kernel Selection
- Check Available Kernels: Ensure that your desired kernel is listed in the VS Code notebook. You can usually see available kernels in the top right corner of your notebook.
- Install Needed Kernels: If you need a specific kernel (like Python 3.8), make sure it's installed in your environment. Use the
pip install ipykernelcommand followed bypython -m ipykernel install --user --name "your_kernel_name"to add it to Jupyter's list.
4. Port Conflicts
- Check Port: The default port for Jupyter is 8888. If it's already in use by another application, you might face issues. Try manually changing the port in the terminal when starting the server (e.g.,
jupyter notebook --port=8889). - Identify Conflicting Programs: Use tools like
netstat -a -b(Windows) orlsof -i :8888(Linux/Mac) to see what processes are using the port.
5. Firewall Issues
- Allow Access: Check your firewall settings to ensure it's not blocking Jupyter's communication.
6. Environment Variables
- Jupyter Path: Ensure that your
PATHenvironment variable includes the directory where Jupyter is installed. - Kernels in Virtual Environments: If you're using a virtual environment, make sure the kernel is activated within it.
7. Restart VS Code
Sometimes, a simple restart can resolve issues.
8. VS Code Extension Issues
- Reinstall Jupyter Extension: Try reinstalling the Jupyter extension from the VS Code extensions marketplace.
- Other Extensions: Sometimes, other installed extensions can conflict with Jupyter. Try temporarily disabling them to see if it solves the problem.
Example: A Specific Case
Let's say you're working on a project with a specific Python version (e.g., 3.9) and need to create a kernel for it. Here's what you'd do:
- Activate your Python 3.9 environment:
source .venv/bin/activate(Linux/Mac),.\venv\Scripts\activate(Windows) - Install the
ipykernelpackage:pip install ipykernel - Create the kernel:
python -m ipykernel install --user --name "my_python39_kernel" - Select the new kernel in your notebook: The kernel should now appear as an option in the top right corner of your notebook.
Additional Value: Troubleshooting Tips
- Clear Cache: Sometimes, clearing VS Code's cache can help. You can find instructions on VS Code's documentation.
- Log Files: Check the VS Code log files for more detailed error messages.
Conclusion
Getting Jupyter Notebooks working in VS Code requires a bit of setup and attention to detail. By following the steps and troubleshooting tips above, you can overcome the "Jupyter Server: Not Started, No Kernel" error and unlock the interactive power of Jupyter Notebooks within your VS Code environment.
