Kernel Toolbar

Every notebook has a kernel — the runtime that executes your code. The kernel toolbar at the top of each notebook lets you select, control, and monitor the kernel.

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The kernel picker

Click the kernel button (shows the current kernel name) to open the picker.

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Kernel information

The button displays:

• Status indicator: Colored dot showing kernel state
• Display name: Language and environment (e.g., “Python 3.11 | /usr/local/bin/python”)

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Selecting a kernel

The picker groups available kernels by language:

• Python: All Python installations and virtual environments
• R: R installations
• Julia: Julia installations

Each entry shows the language version and environment path. Click to switch kernels.

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Active kernels

If a kernel is already running, it appears separately under Active — you can attach to an existing kernel session instead of starting a new one.

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Status indicators

The kernel status dot changes color: When code is running, a spinner appears in the toolbar.

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Toolbar actions

The toolbar provides buttons for common kernel operations:

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Execution control

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Kernel management

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Combined actions

Some actions combine restart with execution:

• Restart and run all: Fresh kernel, then run everything
• Restart and run up to current: Fresh kernel, then run to current cell
• Restart and clear: Fresh kernel, clear all outputs

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Execution indicator

When cells are running:

• A spinner appears in the toolbar
• Click the spinner to scroll to the executing cell
• The spinner persists until execution completes

This helps you track long-running computations — click to jump back to where the action is.

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Default kernel

Set your preferred default kernel in Settings > General:

1. Go to Settings
2. Under Default Python Environment, select your preferred Python
3. New notebooks use this kernel automatically

Qualia validates that the selected kernel exists. If it’s missing (e.g., a virtual environment was deleted), you’ll see a warning.

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Responsive layout

When the window is narrow, toolbar actions collapse into a More menu (⋮). All the same actions are available — just fewer visible buttons.

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Keyboard shortcuts

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Troubleshooting

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Kernel not starting

• Check that the Python/R/Julia installation exists
• Verify virtual environments are activated correctly
• Look at the error message in the status area

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Kernel keeps dying

• Memory issues can crash kernels — check your system resources
• Some packages have installation problems — try in a fresh environment
• The kernel log may have more details

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Wrong environment

• Verify the kernel picker shows the expected path
• Check that packages are installed in that environment
• The environment shown in the picker should match where you installed dependencies