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# Jupyter

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Jupyter is a project which produces browser-based interactive environments for programming, mathematics, and data science. It supports a number of languages via plugins ("kernels"), such as Python, Ruby, Haskell, R, Scala, Julia and Kotlin.

JupyterLab is "Jupyter’s Next-Generation Notebook Interface", while Jupyter Notebook is the original. See the Jupyter website for a comparison.

## Installation

- For JupyterLab, install the jupyterlab package.
- For Jupyter Notebook, install the jupyter-notebook package.

To install third-party Jupyter Notebook extensions for the current user, use the `--user` option while executing `jupyter nbextension install`. To do the same for installation of JupyterLab extensions, set the following environment variable:

    JUPYTERLAB_DIR=$HOME/.local/share/jupyter/lab

and verify it by running `jupyter lab paths`. Then onwards follow usual installation instructions.

## Running

To start JupyterLab run:

    $ jupyter lab

To start Jupyter Notebook run:

    $ jupyter notebook

Navigate to the URL given on the standard output if a web browser does not automatically open.

To start JupyterLab without launching browser and listening on port `9999` run

    $ jupyter lab --no-browser --port 9999

To change the default behavior, edit the configuration file:

    ~/.jupyter/jupyter_lab_config.py

    c = get_config()
    c.ExtensionApp.open_browser = False
    c.ServerApp.port = 9999

See `jupyter lab --help-all` for an overview of all options or run `jupyter lab --generate-config` to generate a default configuration file.

## Kernels

### C++

Install the cling-jupyter-gitAUR package.

### Haskell

Install the ihaskell package. Then run `ihaskell install`.

### Julia

Install the julia package and run `julia` to get a REPL prompt. Then run:

    using Pkg
    Pkg.add("IJulia")

See the Julia manual for more details on package management.

### Python

Python 3 kernel is used by default via python-ipykernel.

### Perl

Install the iperlAUR package and run `iperl`. Then press `Ctrl+d`. Now if you run jupyter you will see perl there.

### R

Install the r-irkernelAUR package. Then in an R console run:

    require(IRkernel)
    IRkernel::installspec()

Alternatively you could follow the installation instructions in IR Kernel.

### Rust

Install the evcxr_jupyterAUR package.

### SageMath

Install the sagemath package.

### Octave

Install the jupyter-octave_kernelAUR package.

### Maxima

Install the maxima-jupyter-gitAUR package.

### Cadabra

Install the cadabra2AUR package.

### Kotlin

Install the python-kotlin-jupyter-kernelAUR package.

## Interactive widgets in JupyterLab

The factual accuracy of this article or section is disputed.

Reason: The linked issue is specific to python-matplotlib, the title of this section is overly general. The linked comment says to use `%matplotlib ipympl`, while the following instruction here contains `%matplotlib widget`. It would be much better to link to a proper documentation on matplotlib's magic commands. (Discuss in Talk:Jupyter)

In order to enable interactive widgets in Jupyter Lab install python-ipympl and jupyterlab-widgets according to this github issue. Afterwards, in your notebook use:

    %matplotlib widget

Don't forget to restart you JupyterLab instance after installing extensions.

It also might be helpful to RMB->Clear Outputs of All Cells after your extension manipulations

## See also

- Official website
- JupyterHub

Category:

- Science

Hidden category:

- Pages or sections flagged with Template:Accuracy