Package Health Score

66 / 100

security
No known security issues
popularity
Limited
maintenance
Sustainable
community
Sustainable

Popularity

Limited

GitHub Stars: 215
Forks: 33
Contributors: 10

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package jupyter-matlab-proxy, we found that it has been starred 215 times.

Security

No known security issues

Security and license risk for latest version

Release Date: Feb 7, 2024
Direct Vulnerabilities: 0
C
0
H
0
M
0
L
Indirect Vulnerabilities: 0
C
0
H
0
M
0
L
License Risk: 0
H
0
M
0
L

All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

MATHWORKS CLOUD REFERENCE ARCHITECTURE LICENSE The files in this GitHub repository refer to commercial software products and services, virtual machine images, and related materials of The MathWorks, Inc. (“MathWorks Programs”). MathWorks Programs are separately licensed under the MathWorks Software License Agreement, available in the desktop installation of the MathWorks Programs or in the virtual machine image. The files in this GitHub repository may also refer to third-party software licensed under separate terms provided by such third parties. The following license terms apply only to the files in this GitHub repository, including files in this folder and its subfolders, and do not apply to MathWorks Programs. References to “software” and “code” in the following license terms refer to the files in this GitHub repository. Copyright (c) 2020, The MathWorks, Inc. All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. In all cases, the software is, and all modifications and derivatives of the software shall be, licensed to you solely for use in conjunction with MathWorks products and service offerings. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Security Policy

Yes

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Maintenance

Sustainable

Commit Frequency

Open Issues: 22
Open PR: 0
Last Release: 3 months ago
Last Commit: 1 month ago

Further analysis of the maintenance status of jupyter-matlab-proxy based on released PyPI versions cadence, the repository activity, and other data points determined that its maintenance is Sustainable.

We found that jupyter-matlab-proxy demonstrates a positive version release cadence with at least one new version released in the past 3 months.

As a healthy sign for on-going project maintenance, we found that the GitHub repository had at least 1 pull request or issue interacted with by the community.

Community

Sustainable

Readme: Yes
Contributing.md: No
Code of Conduct: No
Contributors: 10
Funding: No

This project has seen only 10 or less contributors.

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Package

Python Versions Compatibility: >=3.8

Age: 3 years
Latest Release: 3 months ago
Dependencies: 4 Direct
Versions: 21
Maintainers: 1
Wheels: OS Independent

Readme

MATLAB Integration for Jupyter

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

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).
Python versions: 3.8 | 3.9 | 3.10 | 3.11
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

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 16 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 .

Integration with 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.

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:

Install Jupyter Notebook or JupyterLab:

# For Jupyter Notebook
python -m pip install notebook

# For JupyterLab 3
python -m pip install 'jupyterlab&gt;=3.0.0,&lt;4.0.0a0'

Note: the package allows you to execute MATLAB code in both JupyterLab 3 and JupyterLab 4, but syntax highlighting and auto indentation are currently only supported on JupyterLab 3. To upgrade to JupyterLab 4, run python -m pip install --upgrade jupyterlab.

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.

When you execute MATLAB code in a notebook for the first time, enter your MATLAB license information in the dialog box that appears. See Licensing for details. The MATLAB session can take a few minutes to start.
Multiple notebooks running on a Jupyter server share the underlying MATLAB process, so executing code in one notebook affects the workspace in others. If you work in several notebooks simultaneously, be aware that they share a workspace.
With MATLAB R2022b and later, you can define a local function at the end of the cell where you want to call it:

For technical details about how the MATLAB kernel works, see MATLAB Kernel for Jupyter.

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 and auto indentation.

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 jupyter-support@mathworks.com.

jupyter-matlab-proxy dependencies

ipykernel jupyter-server-proxy psutil requests

FAQs

What is jupyter-matlab-proxy?

MATLAB Integration for Jupyter. Visit Snyk Advisor to see a full health score report for jupyter-matlab-proxy, including popularity, security, maintenance & community analysis.

Is jupyter-matlab-proxy popular?

The python package jupyter-matlab-proxy receives a total of 547 weekly downloads. As such, jupyter-matlab-proxy popularity was classified as limited. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is jupyter-matlab-proxy well maintained?

We found indications that jupyter-matlab-proxy maintenance is sustainable demonstrating some project activity. We saw a total of 10 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is jupyter-matlab-proxy safe to use?

The python package jupyter-matlab-proxy was scanned for known vulnerabilities and missing license, and no issues were found. Thus the package was deemed as safe to use. See the full health analysis review.

Last updated on 3 May-2024, at 18:11 (UTC).

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