zwave-js-ui VS pyenv

The software I want to compile is open source. On the GitHub page below the author provides a copy of the source code as well as the compiled exe file. https://github.com/zwave-js/zwave-js-ui/releases

It's a bit convoluted. That's the ZWave-JS-UI for HA addon release notes. The note indicates an update to ZWaveJS-UI to v8.8.6. Those release notes say ZWaveJS-Server updates to v1.26. Finally, the ZWaveJS-Server release notes indicate the actual ZWaveJS package is updated to 10.10.0.

If that doesn't work then I would try connecting it to another piece of software like the Z-WaveJSUI software. It's the same thing as the addon that you would find in home assistant but it is standalone self contained windows program that's about 50mb in size. Download the latest version from here then extract the files and run the exe file. Now just type in 127.0.0.1:8091 in your browser to pull up the management webpage. Then you can go to settings and try to connect your USB. I believe you can update the firmware in this software as well but I'm not 100% certain.

Once you have all the hardware you’ll want to setup home assistant. Configure your zwave devices. I used zwavejs2mqtt (but without mqtt) I know very confusing… https://github.com/zwave-js/zwavejs2mqtt

However, looking at the githubs for these packages: * sonarr: https://github.com/Sonarr/Sonarr/ * pihole: https://github.com/pi-hole/pi-hole * zwavejs2mqtt: https://github.com/zwave-js/zwavejs2mqtt

I recently deployed a small fleet of Dell thin clients around my house to run zwavejs2mqtt[1] via docker. I decided to use Alpine because the machines have 2GB of ram and 8GB of eMMC storage and I figured Alpine would minimize resource usage. They're working great so far!

[1]: https://github.com/zwave-js/zwavejs2mqtt

/u/Warm_Command7954 is right. You need to map /usr/src/app/store to a folder outside of the container or you will lose your configs on every update. This might help.

This is an upcoming feature that is in development. https://github.com/zwave-js/zwavejs2mqtt/pull/2205

If you have a requirement for multiple, specific Python versions, why not just use pyenv?

https://github.com/pyenv/pyenv

For more information visit: pyenv repository

Note that virtual environments assume you are using the same global version of Python. Often, this is not the case and additional tools like pyenv can be used alongside virtual environments when you need to switch between versions of Python itself on your local machine.

Python version manager pyenv

First of all, install the Python virtual environment from these links: 1 and 2. I developed my GPT-based API in Python version 3.8.18. Pick any Python versions >= 3.7.

Note: Most modern systems will probably have a system environment that meets this requirement, but if yours does not or if you prefer not to install anything in your system environment (even if it's just PDM) check out asdf or pyenv to help install and manage additional Python environments.

When dealing with software development, reproducibility is key. This is why we encourage you to use Python virtual environments to set up an isolated environment for your project. Virtual environments allow the isolation of dependencies, which plays a crucial role to avoid breaking compatibility between different projects. We cannot cover all the details about virtual environments in this post, but we encourage you to learn more about venv, pyenv or conda for a better understanding on how to create and manage virtual environments.

For Python, with your use case I would avoid system packages, no matter the distro. It sounds like it would be worth setting up pyenv and working exclusively with virtual environments.

For OSX there is homebrew or pyenv (pyenv is another solution on Linux). As pyenv compiles from source it will require setting up XCode (the Apple IDE) tools to support this which can be pretty bulky. Windows users have chocolatey but the issue there is it works off the binaries. That means it won't have the latest security release available since those are source only. Conda is also another solution which can be picked up by Visual Studio Code as available versions of Python making development easier. In the end it might be best to consider using WSL on Windows for installing a Linux version and using that instead.