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Linux is a family of open source Unix-like operating systems based on the Linux kernel, an operating system kernel first released on September 17, 1991 by Linus Torvalds. Linux is typically packaged in a Linux distribution (or distro for short).

Distributions include the Linux kernel and supporting system software and libraries, many of which are provided by the GNU Project. Many Linux distributions use the word "Linux" in their name, but the Free Software Foundation uses the name GNU/Linux to emphasize the importance of GNU software, causing some controversy.

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Make a Linux App (makealinux.app)

submitted 1 year ago by [email protected] to c/[email protected]

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Make a Linux app. Stop making distributions.

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[–] [email protected] 7 points 1 year ago (1 children)

The term to look up is Monaco. That's the secret sauce part of VS Code that made it faster but I don't know enough about it to describe it well

[–] [email protected] 5 points 1 year ago

Just looked it up a bit: https://microsoft.github.io/monaco-editor/

AFAIU, monaco is just about the editor part. So if an electron application doesn't need an editor, this won't really help to improve performance.

Having gone through learning and developing with electron myself, this (and the referenced links) was a very helpful resource: https://www.electronjs.org/docs/latest/tutorial/performance

In essence: "measure, measure, measure".

Then optimize what actually needs optimizing. There's no easy, generic answer on how to get a given electron app to "appear performant". I say "appear", because even vscode leverages various strategies to appear more performant than it might actually be in certain scenarios. I'm not saying this to bash vscode, but because techniques like "lazy loading" are simply a tool in the toolbox called "performance tuning".

BTW: Not even using C++ will guarantee a performant application in the end, if the application topic itself is complex enough (e.g. video editors, DAWs, etc.) and one doesn't pay attention to performance during development.

All it takes is to let a bunch of somewhat CPU intensive procedures pile up in an application and at some point it will feel sluggish in certain scenarios. Only way out of that is to measure where the actual bottlenecks are and then think about how one could get away with doing less (or doing less while a bunch of other things are going on and then do it when there's more of an "idle" time), then make resp. changes to the codebase.