Tutorial: https://www.youtube.com/watch?v=hIqMrPTeGTc
Paste the below code in your browser console (F12 > Console):
(()=>{
markAllVideosAsNotBeingInteresting({
iterations: 1
});
})();
## System76 Scheduler | |
# URL: https://github.com/pop-os/system76-scheduler | |
# LICENSE(PKGBUILD): MIT | |
pkgname=system76-scheduler | |
pkgver="0.1.0" | |
pkgrel=1 | |
pkgdesc="Auto-configure CFS for improved desktop responsiveness when on AC (based on Zen CFS settings)" | |
arch=('any') | |
url="https://github.com/pop-os/system76-scheduler" | |
license=('MPL') |
Tutorial: https://www.youtube.com/watch?v=hIqMrPTeGTc
Paste the below code in your browser console (F12 > Console):
(()=>{
markAllVideosAsNotBeingInteresting({
iterations: 1
});
})();
Syncthing: https://syncthing.net/
Syncthing is a free, open-source peer-to-peer file synchronization application available for Windows, Mac, Linux, Android, Solaris, Darwin, and BSD. It can sync files between devices on a local network, or between remote devices over the Internet. Data security and data safety are built into the design of the software.
This is written using Linux Mint 21.2 x86_64 using kernel 5.15.0-89-generic.
I couldn't find good directions for doing this, so here we go.
# OBJECTIVE: Install Arch Linux with encrypted root and swap filesystems with full Bcache SSD/HDD support | |
# and boot from UEFI. | |
# RATIONALE: As most users realize, you have to pay for marginal speed improvements in all circuits which compute. | |
# This holds true for CPUs, GPUs, DRAM, SRAM, Drives, including memory cards and USB sticks. If you want speed, you | |
# must be willing to pay the price premium that a faster device commands versus a slower alternative. | |
# SSDs are incredibly fast, but expensive to produce, and therefore, only offer limited storage space. | |
# HDDs, by comparison, are ridiculously slow, but offer immense storage space per dollar expended. |
#!python3 | |
''' | |
This is a demo of how you can use the CoreML framework (via objc_util) to classify images in Pythonista. It downloads the trained 'MobileNet' CoreML model from the Internet, and uses it to classify images that are either taken with the camera, or picked from the photo library. | |
''' | |
import requests | |
import os | |
import io | |
import photos | |
import dialogs |