https://github.com/pavel-kirienko/jupyter-pyuavcan-demo

A Jupyter notebook showcasing how to use PyUAVCAN for interactive network analysis
https://github.com/pavel-kirienko/jupyter-pyuavcan-demo

Last synced: about 2 months ago
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A Jupyter notebook showcasing how to use PyUAVCAN for interactive network analysis

• Host: GitHub
• URL: https://github.com/pavel-kirienko/jupyter-pyuavcan-demo
• Owner: pavel-kirienko
• License: unlicense
• Created: 2019-11-10T18:04:50.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2021-02-22T11:56:52.000Z (over 4 years ago)
• Last Synced: 2025-02-10T21:19:35.502Z (4 months ago)
• Language: Jupyter Notebook
• Size: 11.7 KB
• Stars: 2
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Jupyter PyUAVCAN demo

[![Forum](https://img.shields.io/discourse/https/forum.uavcan.org/users.svg)](https://forum.uavcan.org)

A Jupyter notebook showcasing how to use PyUAVCAN for interactive network analysis.

Usage instructions:

1. [Install PyUAVCAN](https://pyuavcan.readthedocs.io).

2. [Install Jupyter](https://jupyter.org).

3. Open the notebook: `jupyter notebook pyuavcan.ipynb`.

As a better alternative to the web browser, consider using [JetBrains PyCharm](https://www.jetbrains.com/pycharm/).

It is a wonderful IDE (rumor has it that it's better than VSCode) and it has a solid support for Jupyter notebooks

out of the box.

If you have a clever snippet to share, add it to the notebook and send a pull request at once!