mmizutani

Table of Contents

• References
• Other cheatsheets
• multiple gcloud config configurations
  • switch gcloud context with gcloud config
• auth
• info
• projects
• zones

EverythingSmartHome

{{ states.binary_sensor
   | selectattr('attributes.device_class', 'in', ['door','window'])
   | selectattr('state', 'equalto', 'on')
   | list | count }}

ebanDev

--[[
FolderCover patch for KOReader (v3.0)
========================================

Features:
- Automatically detects cover images in directories
- Supports multiple image formats (jpg, jpeg, png, webp, gif)
- Configurable folder name and file count display with positioning options
- Rounded corners and proper image cropping
- Settings integration with BookInfoManager

skfarhat

--------------------------------------------
Version: 1.45.1
Commit: 5763d909d5f12fe19f215cbfdd29a91c0fa9208a
Date: 2020-05-14T08:33:47.663Z
Electron: 7.2.4
Chrome: 78.0.3904.130
Node.js: 12.8.1
V8: 7.8.279.23-electron.0
OS: Darwin x64 18.5.0
-------------------------------------------

Pulimet

Hi All!

I've recently launched a tool that wraps many of the commands here with a user interface. This desktop application is currently available for macOS. There's a roadmap outlining planned features for the near future.
Feel free to request any features you'd like to see, and I'll prioritize them accordingly.
One of the most important aspects of this application is that every command executed behind the scenes is displayed in a special log section. This allows you to see exactly what’s happening and learn from it.

Here's the link to the repository:  https://github.com/Pulimet/ADBugger

App Description:
ADBugger is a desktop tool designed for debugging and QA of Android devices and emulators. It simplifies testing, debugging, and performance analysis by offering device management, automated testing, log analysis, and remote control capabilities. This ensures smooth app performance across various setups.

pusherman

<select name="state" id="state">
  <option value="" selected="selected">Select a State</option>
  <option value="AL">Alabama</option>
  <option value="AK">Alaska</option>
  <option value="AZ">Arizona</option>
  <option value="AR">Arkansas</option>
  <option value="CA">California</option>
  <option value="CO">Colorado</option>
  <option value="CT">Connecticut</option>
  <option value="DE">Delaware</option>

santaklouse

#!/usr/bin/env bash

# checck if pidof exists
PIDOF="$(which pidof)"
# and if not - install it
(test "${PIDOF}" && test -f "${PIDOF}") || brew install pidof

# find app in default paths
CO_PWD=~/Applications/CrossOver.app/Contents/MacOS
test -d "${CO_PWD}" || CO_PWD=/Applications/CrossOver.app/Contents/MacOS

dmalinovsky

local ReaderPageMap = require("apps/reader/modules/readerpagemap")
local postInit_orig = ReaderPageMap._postInit

ReaderPageMap._postInit = function(self)
    self.ui.document:buildSyntheticPageMapIfNoneDocumentProvided(1818)

    -- Run original code
    postInit_orig(self)
end

sumitsahoo

# Remove delay
defaults write com.apple.dock autohide -bool true && defaults write com.apple.dock autohide-delay -float 0 && defaults write com.apple.dock autohide-time-modifier -float 0 && killall Dock

# Faster animation
# defaults write com.apple.dock autohide -bool true && defaults write com.apple.dock autohide-delay -float 0 && defaults write com.apple.dock autohide-time-modifier -float 0.65 && killall Dock

# Revert back
# defaults delete com.apple.dock autohide && defaults delete com.apple.dock autohide-delay && defaults delete com.apple.dock autohide-time-modifier && killall Dock

ericmjl

UPDATE: I have baked the ideas in this file inside a Python CLI tool called pyds-cli. Please find it here: https://github.com/ericmjl/pyds-cli

How to organize your Python data science project

Having done a number of data projects over the years, and having seen a number of them up on GitHub, I've come to see that there's a wide range in terms of how "readable" a project is. I'd like to share some practices that I have come to adopt in my projects, which I hope will bring some organization to your projects.

Disclaimer: I'm hoping nobody takes this to be "the definitive guide" to organizing a data project; rather, I hope you, the reader, find useful tips that you can adapt to your own projects.

Disclaimer 2: What I’m writing below is primarily geared towards Python language users. Some ideas may be transferable to other languages; others may not be so. Please feel free to remix whatever you see here!