jupyter

Start a Jupyter notebook server in the current directory

$ jupyter notebook

$ jupyter notebook [example.ipynb]

$ jupyter nbconvert --to [html|markdown|pdf|script] [example.ipynb]

$ jupyter notebook --port [port]

$ jupyter notebook list

$ jupyter notebook stop

$ jupyter lab

jupyter <subcommand> [options]

notebook
    Launches the Jupyter Notebook application.

lab
    Launches the JupyterLab application.

console
    Launches the Jupyter Console application.

qtconsole
    Launches the Qt Console application.

kernelspec
    Manages Jupyter kernelspecs. (list, install, uninstall)

kernelspec list
    Lists available kernelspecs.

kernelspec install <path>
    Installs a kernel specification.

kernelspec uninstall <name>
    Uninstalls a kernel specification.

trust <notebook>
    Trusts a notebook, allowing JavaScript execution.

server
    Command group to manage Jupyter Server configurations.

--config-dir
    The Jupyter config directory.
Default: ~/.jupyter

--data-dir
    The Jupyter data directory.
Default: ~/.local/share/jupyter

--runtime-dir
    The Jupyter runtime directory.
Default: /run/user/1000/jupyter

--paths
    Print all of the Jupyter paths and exit.

The `jupyter` command is the main entry point for the Jupyter ecosystem, a suite of tools for interactive computing and data science. It facilitates running interactive computing environments, primarily Jupyter Notebooks and JupyterLab, accessible through a web browser. It allows users to create and share documents that contain live code, equations, visualizations, and narrative text. Jupyter supports multiple programming languages via kernels, including Python, R, Julia, and more. The command provides functionalities for managing kernels, extensions, configurations, and launching different Jupyter applications. Users can execute code cells, view results inline, and export notebooks in various formats (e.g., HTML, PDF). Jupyter is widely used in research, education, and data analysis for its ability to combine code, documentation, and results in a single, shareable document. It streamlines the workflow for iterative data exploration, analysis, and visualization.

The `jupyter` command relies on a properly configured Python environment with the necessary Jupyter packages installed.
Firewall settings and browser configurations may impact accessibility.

Jupyter executes code provided by the user.
Ensure that notebooks from untrusted sources are opened with caution, as malicious code could be embedded within them. Use the 'trust' subcommand to explicitly trust notebooks.

Jupyter evolved from the IPython project in 2014. The name 'Jupyter' is a reference to the core supported programming languages: Julia, Python, and R.
It was designed to be a language-agnostic tool for interactive computing, building upon IPython's interactive shell capabilities.
Over time, it has become a central tool in the data science community, with widespread adoption in research, education, and industry. JupyterLab was introduced as a next-generation web-based interface.

python(1), ipython(1), jupyter-notebook(1), jupyter-lab(1)