A little wrapper around `uv` to launch ephemeral Jupyter notebooks.
Project description
juv
A little wrapper around uv to launch ephemeral Jupyter notebooks.
uvx juv
# juv [uvx flags] <command>[@version] <path>
#
# Commands:
# lab Launch JupyterLab
# notebook Launch Jupyter Notebook (classic)
#
# Arguments:
# path Path to the Python script or notebook file
#
# Examples:
# uvx juv lab script.py
# uvx juv notebook@7.2.2 script.ipynb
# uvx juv notebook existing_notebook.ipynb
# uvx juv --with pandas,matplotlib lab new_notebook.ipynb
juv has two main commands:
juv lablaunches a Jupyter Lab sessionjuv notebooklaunches a classic notebook session
Both commands accept a single argument: the path to the notebook or script to launch. A script will be converted to a notebook before launching.
uvx juv lab script.py # creates script.ipynb
Any flags that are passed prior to the command (e.g., uvx juv --with=polars lab) will be forwarded to uvx as-is. This allows you to specify additional
dependencies, a different interpreter, etc.
what
PEP 723 (inline script metadata) allows
specifying dependencies as comments within Python scripts, enabling
self-contained, reproducible execution. This feature could significantly
improve reproducibility in the data science ecosystem, since many analyses are
shared as standalone code (not packages). However, a lot of data science code
lives in notebooks (.ipynb files), not Python scripts (.py files).
juv bridges this gap by:
- Extending PEP 723-style metadata support from
uvto Jupyter notebooks - Launching Jupyter sessions with the specified dependencies
It's a simple Python script that parses the notebook and starts a Jupyter
session with the specified dependencies (piggybacking on uv's existing
functionality).
alternatives
juv is opinionated and might not suit your preferences. That's ok! uv is
super extensible, and I recommend reading the
documentation to learn about its primitives.
For example, you can achieve a similar workflow using the --with-requirements
flag:
uvx --with-requirements=requirements.txt --from=jupyter-core --with=jupyterlab jupyter lab notebook.ipynb
While slightly more verbose, and breaking self-containment, this approach works well.
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