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Jupyterlite is a Python/ Jupyterlab distribution that runs entirely in the browser. The various Python packages have been ported to WebAssembly (WASM), a binary format that is executable in browsers. For optimized libraries (numpy, pandas, etc.), performance is equivalent to native performance. For pure Python (loops, etc.), execution is 3 to 10 times slower. What this means, however, is that you can prepare Python programs and Jupyter notebooks that are fully executable in a browser, with zero installation! And it works independently of the system, even on tablets, phones, etc. For example, you can find here: https://perso.esiee.fr/~bercherj/JliteNotes/lab/ an example of a practical assignment distributed in this way, incorporating labquiz.

11.1Deploy to Jupyterlite - 🧑‍🏫🏫

Preparation and deployment under Jupyterlite are not exactly immediate (there are documents to follow and adaptations to make), so I suggest a shortcut, which is as follows:

  1. Download the archive of a deployed version, available here
    https://drive.google.com/file/d/14BnzVmPO6I8uOMEmNC6BTMsjXL3RLrQL/view?usp=sharing
    and unzip it on your disk,

  2. Place the files you want to make available in _output/files

  3. Run the program update_jupyterlite_contents.py available in the extras directory by typing python update_jupyterlite_contents.py. Install dependencies if necessary.

👉🏼 This will update the lists and characteristics of the files in the distribution

  1. init) Upload all of the contents of _output to your web account, typically (or for instance...) to login/public_html, in a directory such as MyJlite, and you will obtain a distribution that is accessible and executable at https://www.esiee.fr/~login/MyJlite. If you don’t know how to do this, ask your nearest local IT guru.

  2. update) If you only need to perform an update, simply copy the contents of _output/files and _output/api to login/public_html/MyJlite/files and login/public_html/MyJlite/api. For subsequent updates, add or modify files, you only need to perform steps 2, 3, and 5.maj); this will save you from having to upload the 70 MB in step 4.init).