| #!/usr/bin/env python | |
| # -*- coding:utf-8 -*- | |
| import sys | |
| reload(sys) | |
| sys.setdefaultencoding('utf-8') | |
| from ws4py.client.threadedclient import WebSocketClient | |
| import binascii | |
| class WSClient(WebSocketClient): | |
| def __init__(self, url, text, filename): | 
| { | |
| "title": "SpaceFN", | |
| "rules": [ | |
| { | |
| "description": "SpaceFN: Space enables SpaceFN mode (see: https://geekhack.org/index.php?topic=51069.0 & https://spacelauncherapp.com)", | |
| "manipulators": [ | |
| { | |
| "type": "basic", | |
| "from": { | |
| "key_code": "spacebar" | 
| #!/bin/bash | |
| # Monitor the movie download folder and organize it. | |
| # Author: Seven Yu <[email protected]> | |
| # Version: 1.0 | |
| if [[ -z $1 ]]; then | |
| echo "⚠️ You must input a path" | |
| exit 1 | |
| fi | 
This cheatsheet shows how to install and configure multipath tools on Proxmox PVE Cluster where multiple nodes share single storage with multipath configuration, for example SAN storage connected to each of the nodes by two independent paths.
This cheatsheet has been tested on Proxmox 5.x.
I do not prepend sudo command to any of commands listed here, but keep in mind that nearly all commands requires su privileges, so use sudo if your account happen to not have root access.
MOVE TO HERE
首先确定已经安装完成 docker,如果没有安装可以使用以下脚本快速安装并配置:
Important: I'm writing this when the last version of macOS (and the one I have installed) is Mojave. There is already a script which installs Mojave in a virtual machine here https://github.com/img2tab/okiomov. But if you are curios how to do everything manually to install High Sierra, then this guide may be useful.
After reading a few articles I ended up with these steps:
- On macOS, download the High Sierra installer (even if you have Mojave installed): https://itunes.apple.com/us/app/macos-high-sierra/id1246284741?ls=1&mt=12
- If the High Sierra Installer starts, quit it.
- Open "Disk Utility".
- Click on "File" > "New Image" > "Blank image...". Or just press cmd+N.
| #!/usr/bin/python3.7 | |
| import asyncio | |
| import ipaddress | |
| import re | |
| import sys | |
| MAX_NUMBER_WORKERS = 200 | 
This guide will show you how to use Intel graphics for rendering display and NVIDIA graphics for CUDA computing on Ubuntu 18.04 / 20.04 desktop.
I made this work on an ordinary gaming PC with two graphics devices, an Intel UHD Graphics 630 plus an NVIDIA GeForce GTX 1080 Ti.
Both of them can be shown via lspci | grep VGA.
00:02.0 VGA compatible controller: Intel Corporation Device 3e92
01:00.0 VGA compatible controller: NVIDIA Corporation GP102 [GeForce GTX 1080 Ti] (rev a1)