Luiz Lopes theprivileges

## workflow.yml
# This workflow will build and push a new container image to Amazon ECR, and then deploy a new task definition to Amazon ECS.
#
# To use this workflow, assume you have your infrastructure already provisioned, if not, you will need to complete the following set-up steps:
#
# 1. Create an ECR repository to store your images.
#    For example: `aws ecr create-repository --repository-name my-ecr-repo --region us-east-1`.
#    Replace the value of the `ECR_REPOSITORY` environment variable in the workflow below with your repository's name.
#    Replace the value of the `AWS_REGION` environment variable in the workflow below with your repository's region.
#
# 2. Create an ECS task definition, an ECS cluster, and an ECS service.

## clamav.md

      
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                theprivileges
                / clamav.md
            
            
              Created
              September 20, 2021 21:10
            
              
                How to install and run ClamAV on Mac
              
          
    install homebrew

/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
install clamav

brew install clamav

  
## clean-branches.sh
git branch -vv | grep 'origin/.*: gone]' | awk '{print $1}' | xargs git branch -D

## username_generator.sh
date | md5sum | cut -c 1-10 | pbcopy

## getRandomDate.js
/**
 * Give a start and end Date object, returns a string representation of a random Date between the start and end dates.
 *
 * @param {object} start — Date object specifing the start date.
 * @param {object} end — Date object specifiing the end date.
 * @example
 * // may return "Wed Jan 30 2019 18:26:45 GMT-0700 (Mountain Standard Time)"
 * getRandomDate(new Date(2019, 0, 1), new Date())
 * @example
 * // mary return "Wed Jun 12 2002 08:53:15 GMT-0600 (Mountain Daylight Time)"

## createThumbnail.js
'use strict';
// dependencies
const async = require('async');
const AWS = require('aws-sdk');
const gm = require('gm').subClass({
    imageMagick: true
}); // Enable ImageMagick integration.
const fs = require('fs');
const path = require('path');

## immutableSplice.js
function immutableSplice(arr, start, deleteCount, ...items) {
  return [ ...arr.slice(0, start), ...items, ...arr.slice(start + deleteCount) ]
}

## searchInArray.js
const labels = [
    { id: 1, name:"string 1", value:"this", other: "that" },
    { id: 2, name:"string 2", value:"this", other: "that" },
    { id: 3, name:"string 2", value:"this", other: "that" },
];

const selected = [1,3];

const searchInArray = (array, prop, value) => array.filter(element => element[prop] === value);

## index.html
<!DOCTYPE html>
<html>
<head>
  <meta charset="utf-8">
  <meta name="viewport" content="width=device-width">
  <title>JSON Data Example</title>
</head>
<body>
  <div id="main"></div>
<script type="application/json" id="data">

## Microsoft Edge Testing on VirtualBox.md

      
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                theprivileges
                / Microsoft Edge Testing on VirtualBox.md
            
            
              Created
              May 23, 2018 15:15
            
              
                A simple guide on how to use VirtualBox and Virtual Machine images from modern.ie so you can test your project on MSEdge.
              
          
    The following are the steps for downloading and running MSEdge on VirtualBox.
Step 1 — Download Virtual Box

Head to https://www.virtualbox.org/wiki/Downloads, and download the appropriate platform package.
Step 2 — Download Virtual Machine

Microsoft's modern.ie has kindly provided us with images from IE8 to MSEdge.  You can download these images at https://developer.microsoft.com/en-us/microsoft-edge/tools/vms/.

Select the MSEdge option under Virtual Machine.
Select VirtualBox under Platform.
	# This workflow will build and push a new container image to Amazon ECR, and then deploy a new task definition to Amazon ECS.
	#
	# To use this workflow, assume you have your infrastructure already provisioned, if not, you will need to complete the following set-up steps:
	#
	# 1. Create an ECR repository to store your images.
	# For example: `aws ecr create-repository --repository-name my-ecr-repo --region us-east-1`.
	# Replace the value of the `ECR_REPOSITORY` environment variable in the workflow below with your repository's name.
	# Replace the value of the `AWS_REGION` environment variable in the workflow below with your repository's region.
	#
	# 2. Create an ECS task definition, an ECS cluster, and an ECS service.
	/**
	* Give a start and end Date object, returns a string representation of a random Date between the start and end dates.
	*
	* @param {object} start — Date object specifing the start date.
	* @param {object} end — Date object specifiing the end date.
	* @example
	* // may return "Wed Jan 30 2019 18:26:45 GMT-0700 (Mountain Standard Time)"
	* getRandomDate(new Date(2019, 0, 1), new Date())
	* @example
	* // mary return "Wed Jun 12 2002 08:53:15 GMT-0600 (Mountain Daylight Time)"
	'use strict';
	// dependencies
	const async = require('async');
	const AWS = require('aws-sdk');
	const gm = require('gm').subClass({
	imageMagick: true
	}); // Enable ImageMagick integration.
	const fs = require('fs');
	const path = require('path');
	function immutableSplice(arr, start, deleteCount, ...items) {
	return [ ...arr.slice(0, start), ...items, ...arr.slice(start + deleteCount) ]
	}
	const labels = [
	{ id: 1, name:"string 1", value:"this", other: "that" },
	{ id: 2, name:"string 2", value:"this", other: "that" },
	{ id: 3, name:"string 2", value:"this", other: "that" },
	];

	const selected = [1,3];

	const searchInArray = (array, prop, value) => array.filter(element => element[prop] === value);
	<!DOCTYPE html>
	<html>
	<head>
	<meta charset="utf-8">
	<meta name="viewport" content="width=device-width">
	<title>JSON Data Example</title>
	</head>
	<body>
	<div id="main"></div>
	<script type="application/json" id="data">