Notebook Viewer

Omnilib's Notebook Viewer lets you work with Jupyter notebooks (.ipynb files). View notebooks, edit cells, and execute code using real Python kernels with full keyboard navigation.

Overview

The Notebook Viewer provides:

• Cell display — View code and markdown cells
• Code execution — Run cells with Jupyter kernels
• Rich output — Display text, HTML, images, and errors
• Kernel management — Select kernels and conda environments
• Full keyboard navigation — Run, add, and convert cells without the mouse
• Tags — Apply tags per notebook from the ribbon

Getting Started

Opening a Notebook

Click any .ipynb file in the sidebar. The notebook opens showing all cells in order.

Understanding Cells

Viewing Notebooks

Code Cells

Code cells show:

• Source code — Syntax-highlighted Python
• Execution count — [1], [2], etc.
• Output — What the code produces

Markdown Cells

Markdown cells render headings, lists, tables, links, images, and mathematical formulas. Double-click to edit.

Executing Code

Keyboard Shortcuts for Execution

Running All Cells

Click Run All in the toolbar, or press Cmd+Shift+Enter (Windows: Ctrl+Shift+Enter).

Execution States

The kernel state indicator appears in the toolbar.

Cell Output

Text Output

Standard print output and text results display below the cell.

HTML Output

Rich HTML renders inline — DataFrames as formatted tables, interactive widgets, and custom HTML.

Images

Matplotlib figures, PIL images, and SVG graphics render directly in the notebook.

Errors

Error messages display with the error type, message, and full traceback with line numbers.

Editing Cells

Adding Cells

Or click Add Cell in the toolbar and select Code or Markdown.

Converting Cell Types

With a cell selected (not in edit mode):

Moving Cells

Select a cell and use Cmd+Shift+Up (Windows: Ctrl+Shift+Up) or Cmd+Shift+Down (Windows: Ctrl+Shift+Down) to reorder.

Deleting Cells

Select a cell and press Delete.

Full Keyboard Navigation

The notebook uses a two-mode system: Command mode (cell selected, not editing) and Edit mode (cursor inside a cell).

Press Escape to enter command mode. Press Enter to enter edit mode on the selected cell.

Command Mode Shortcuts

Tags

Click the Tags button in the notebook toolbar ribbon to manage tags for the current notebook. Tags are stored in the notebook metadata and can be used to categorize notebooks across a project.

Kernel Management

Selecting a Kernel

Click the kernel selector in the toolbar:

System Kernels — Python kernels installed on your system, detected automatically.

Conda Environments — Environments from Conda or Miniconda. If the environment does not have ipykernel installed, Omnilib prompts you to install it with one click.

Conda Environment Selection

Select a conda environment from the kernel dropdown. Omnilib detects environments from your standard conda installation paths. If ipykernel is not installed in the selected environment, a prompt appears:

1. Click Install ipykernel.
2. Wait for installation to complete.
3. The environment becomes available as a kernel.

Kernel Actions

Toolbar Actions

Working with Data

import pandas as pd

df = pd.read_csv("data.csv")
df.head()  # Displays as a formatted table

import matplotlib.pyplot as plt

plt.plot([1, 2, 3, 4])
plt.ylabel('Values')
plt.show()  # Displays inline

Desktop-Only Features

Full kernel execution requires the Omnilib desktop app. The web version can view notebooks (read-only) and see existing outputs, but cannot execute code or start kernels.

Troubleshooting

Kernel Not Starting

• Ensure Python and Jupyter are installed.
• Check that the selected kernel is valid.
• Try restarting Omnilib.

Execution Stuck

• Click Interrupt to stop.
• If unresponsive, restart the kernel.

Missing Packages

1. Open a terminal.
2. Activate the relevant environment.
3. Run pip install package-name.
4. Restart the kernel.

Output Not Showing

• Check that the cell ran (look for an execution count).
• Ensure the code produces output.
• Try running the cell again.

Related

• Code Editor
• Terminal
• Git Source Control