jupyter-matlab-proxy 0.18.0

MATLAB Integration for Jupyter

MATLAB Integration for Jupyter

Run MATLAB® code in Jupyter® environments such as Jupyter notebooks, JupyterLab, and JupyterHub.

Table of Contents

• MATLAB Integration for Jupyter
  • Table of Contents
  • Features of MATLAB Integration for Jupyter
  • Requirements
  • Install
    • Install from PyPI
    • Build from Source
    • Using VS Code
    • Using JupyterHub and The Littlest JupyterHub
    • Using Simulink
    • Troubleshooting
  • Get Started
  • Run MATLAB Code in a Jupyter Notebook
    • Notes
  • Open MATLAB in a Browser
  • Edit MATLAB Files in JupyterLab
  • Limitations

Features of MATLAB Integration for Jupyter

You can use this package to run MATLAB code in Jupyter notebooks and JupyterLab.

From your Jupyter notebook or JupyterLab, you can also open the MATLAB development environment in your browser to access more MATLAB features.

Requirements

• Supported operating systems:

  • Linux®
  • MacOS
  • Windows® (supported from v0.6.0).
  • Windows Subsystem for Linux (WSL 2) Installation Guide.

• Python versions: 3.10 | 3.11 | 3.12 | 3.13

• MATLAB R2020b or later, installed and on the system PATH.

  # Confirm MATLAB is on the PATH
  which matlab
  

  Note: You only need MATLAB installed if you want to execute MATLAB code. You can open Jupyter notebooks containing MATLAB code without having MATLAB installed.

• System dependencies required to run MATLAB:

  • The MATLAB Dependencies repository contains base-dependencies.txt files that list the libraries required to run each release of MATLAB on a given operating system. To see how to use these files, refer to the Dockerfiles in the same folder.

• Linux based systems also require X Virtual Frame Buffer (Xvfb), which you can install with:

  # On a Debian/Ubuntu based system:
  $ sudo apt install xvfb
  
  # On a RHEL based system:
  $ yum search Xvfb
  xorg-x11-server-Xvfb.x86_64 : A X Windows System virtual framebuffer X server.
  $ sudo yum install xorg-x11-server-Xvfb
  

Install

Install this Python package from the Python Package Index (PyPI) or build it from the source.

Install from PyPI

python -m pip install jupyter-matlab-proxy
install-matlab-kernelspec

For more information on install-matlab-kernelspec, see Jupyter Kernelspec Installation Utility.

Installing this package will not install MATLAB. To execute MATLAB code in Jupyter, you must have MATLAB installed separately.

Build from Source

Alternatively, you can install this package by building it from the source. This requires Node.js® version 18 or higher. To install Node.js, see Node.js Downloads.

git clone https://github.com/mathworks/jupyter-matlab-proxy.git
cd jupyter-matlab-proxy
python -m pip install .
install-matlab-kernelspec

Using VS Code

You can use this package to run MATLAB in Jupyter notebooks using VS Code. For instructions, see Run MATLAB in Jupyter Notebooks Using VS Code.

Using JupyterHub and The Littlest JupyterHub

To use MATLAB with JupyterHub, install the jupyter-matlab-proxy Python package in the Jupyter environment launched by your JupyterHub platform. For example, if your JupyterHub platform launches Docker containers, install this package in the Docker image used to launch those containers, using the instructions for Using MATLAB Integration for Jupyter in a Docker Container.

To use MATLAB with The Littlest JupyterHub (TLJH), see MATLAB Integration for Jupyter on The Littlest JupyterHub. You might use this if you want to set up JupyterHub on a single server for a small number of users, such as students in a class.

Using Simulink

This package lets you use Simulink® programmatically by entering commands in a Jupyter notebook. To view a model or use other Simulink features that require the Simulink UI, you can use a VNC to connect your Jupyter environment to a Linux desktop where you have MATLAB and Simulink installed. For instructions, see MATLAB Jupyter VNC Solution.

Troubleshooting

To troubleshoot package installation issues, see Troubleshooting.

Get Started

This section shows you how to:

1. Run MATLAB Code in a Jupyter Notebook
2. Open MATLAB in a Browser
3. Edit MATLAB files in JupyterLab

Install Jupyter Notebook or JupyterLab:

# For Jupyter Notebook
python -m pip install notebook

# For JupyterLab 4
python -m pip install jupyterlab

Note: you can use this package to execute MATLAB code in both JupyterLab 3 and 4, but syntax highlighting is only supported on JupyterLab 4.

Open your Jupyter environment by starting Jupyter Notebook or JupyterLab.

# For Jupyter Notebook
jupyter notebook

# For JupyterLab
jupyter lab

If you are prompted for a token, click the link shown in your terminal to access your Jupyter environment.

After installing this package, you see new MATLAB options in your Jupyter environments.

Classic Notebook Interface	JupyterLab

Run MATLAB Code in a Jupyter Notebook

To open a Jupyter notebook where you can run MATLAB code, click MATLAB Kernel in your notebook or JupyterLab.

Classic Notebook Interface	JupyterLab

This opens a Jupyter notebook that supports MATLAB.

Notes

• Licensing: When you execute MATLAB code in a notebook for the first time, enter your MATLAB license information in the dialog box that appears. For details, see Licensing. The MATLAB session can take a few minutes to start.

• Sharing MATLAB across notebooks: By default, multiple notebooks running on a Jupyter server share the underlying MATLAB process, so executing code in one notebook affects the workspace in others. To use a dedicated MATLAB for your kernel instead, use the magic %%matlab new_session. For details, see Magic Commands for MATLAB Kernel. To learn more about the kernel architecture, see MATLAB Kernel for Jupyter.

• MATLAB Kernel: The MATLAB kernel supports tab completion and rich outputs:

  • Inline static plot images
  • LaTeX representation for symbolic expressions
  • Tables formatted using HTML instead of ASCII, in MATLAB R2024a and later:

    Before R2024a	After R2024a

  For a technical overview of the MATLAB kernel, see MATLAB Kernel for Jupyter.

• Local functions: With MATLAB R2022b and later, you can define a local function at the end of the cell where you want to call it:

  

• Magic Commands: You can use predefined magic commands in a Jupyter notebook with the MATLAB kernel, and you can also implement your own. To see a list of predefined magic commands, run %%lsmagic. For details about using magic commands, see Magic Commands for MATLAB Kernel.

Open MATLAB in a Browser

To access more MATLAB features, you can open the MATLAB development environment in your browser. Click the Open MATLAB button in your notebook or JupyterLab.

Classic Notebook Interface	JupyterLab

Notebooks in JupyterLab also have a Open MATLAB button on the toolbar:

Clicking Open MATLAB opens the MATLAB development environment in a new browser tab.

When you use the package for the first time, enter your MATLAB license information in the dialog box that appears. See Licensing for details.

For technical details about this MATLAB development environment, see MATLAB in a Browser.

Edit MATLAB Files in JupyterLab

You can also edit MATLAB .m files in JupyterLab. Click the MATLAB File button.

This opens an untitled .m file where you can write MATLAB code with syntax highlighting.

• Currently, this package allows you to edit MATLAB .m files but not to execute them.
• To open a new MATLAB .m file, you can also use the JupyterLab command palette. Press CTRL+SHIFT+C, then type New MATLAB File and press Enter.

Limitations

• This package has limitations. For example, it does not support certain MATLAB commands. For details, see Limitations.

• To discuss a technical issue or submit an enhancement request, create a GitHub issue, or send an email to [e-mail].

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Copyright 2021-2025 The MathWorks, Inc.

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