Notebook (.ipynb)

Open and run Jupyter notebooks inside IVYX Studio. Edit cells, run your Python code, and watch output appear live — then save back to a standard .ipynb file.

What you can do

• Open .ipynb files as a list of code and Markdown cells, each with its own syntax-highlighted editor.
• Run a cell, run all cells, interrupt a running cell, or restart the kernel.
• Watch output stream in live as a cell runs — stdout and stderr, plus rich results: pandas tables (HTML), matplotlib images (PNG), SVG, JSON, Markdown, and colored tracebacks.
• Copy any output from the button in its top right corner. What lands on the clipboard matches the output: text and tracebacks as plain text, a pandas table as a real table (plus tab separated columns for plain text pastes), a matplotlib figure as an image you can paste straight into a document, an SVG as an image or as source. A cell toolbar button copies all of a cell's output at once.
• Choose which kernel a notebook uses from a Select Kernel picker; the choice is remembered per notebook.
• See the notebook's current variables in a side panel.
• Use Jupyter keyboard shortcuts: Shift+Enter (run and move on), Ctrl/Cmd+Enter (run in place), A / B (insert a cell above / below), DD (delete), M / Y (switch a cell to Markdown / code), and arrows or J / K to move between cells.
• Save with Ctrl/Cmd+S, keeping both your code and its outputs.
• Add the notebook to your pipeline from the toolbar: its code cells become a Python script and that script becomes a stage of whichever pipeline engine your workspace uses.

Requirements

A kernel must be available in the Kernels sidebar, pointing at a running Jupyter Server (for example, start one with jupyter server --port 8889). Your Python code runs through that kernel.

Getting started

Open any .ipynb file from the explorer, pick a kernel from the toolbar, and run a cell. When the notebook is doing something you want to keep, press the pipeline button in the toolbar to turn it into a stage you can rerun.