Notebook, files and terminal

Cells and the shared document

A notebook is made of Python code cells and text cells. Edits sync between participants. A cell's output appears below it: text, tables, plots or a Python error. What you can do depends on the room rules and the position of the cell's lock.

The run buttons also work on devices without a keyboard. To continue a notebook you prepared earlier, upload the .ipynb to the room's files and open it: it becomes the room's notebook. Code, text and embedded images carry over; saved outputs do not. You can download the notebook file from the Files panel, but it contains only the cells' code and text, without outputs.

A room can have several notebooks: each one is an .ipynb file in the Files panel, and “New notebook” creates another. All notebooks in a room share one kernel. Version history and restore cover only the room's main notebook, whose name is shown in the History panel; edits in other notebooks do not appear there.

One kernel per room

All cells in a room share the same Python memory. Run the setup once, then use its values in later cells:

# Teacher's setup
numbers = [2, 4, 6]

# A later cell in the same room
sum(numbers) / len(numbers)

The order in which cells ran matters more than where they sit in the notebook. If a variable is not defined, run the cell that creates it. Running a cell again may write data a second time or modify an object that has already been modified.

Restarting the kernel wipes the variables for everyone. The notebook text and files are kept. After a restart, run the setup cells again. Reloading the page is not the same as restarting Python.

Working with files

The Files panel shows a folder tree. You can upload a file from your computer, open it and download it. The room rules decide who can create and edit files; only the teacher can rename them, move them to another folder or delete them. A single file can be up to 50 MB, and all files in a room together up to 1 GB; the server owner changes these limits with the MAX_UPLOAD_MB and MAX_SESSION_MB variables. Text files can be edited together.

Python sees this room's working files. Use relative paths so the notebook stays portable:

from pathlib import Path

Path("results").mkdir(exist_ok=True)
Path("results/answer.txt").write_text("42\n", encoding="utf-8")

A downloaded .ipynb is not a backup of every file on the server. Before working on your own, also download the data, images and anything else the code depends on.

Shared terminal

The terminal runs commands in the room's environment and shows a shared output history. The “Run code” rule applies to it too. The command python analysis.py starts a separate Python process: notebook variables do not carry over to it, but the room's files are still shared. The “Run” button in the editor of a .py or .sh file saves your latest edits and runs the file in the same terminal.

In production, the room's root file system is read-only, and the room has no network access by default except DNS. Installing packages from the internet during class may not work. Add the libraries in advance with an environment release.

What survives a stop

The notebook, files and saved materials are stored on disk. Python memory and processes live only as long as the kernel. A server update or a consistent backup stops the kernels, and their memory is lost. If a room has had nobody in it and nothing running for two hours, the server stops its kernel on its own: the variables are lost, the notebook and files stay. Deleting the server's disk destroys the files too, unless you have an off-server backup.