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progrium/bashstyle

Bash is the JavaScript of systems programming. Although in some cases it's better to use a systems language like C or Go, Bash is an ideal systems language for smaller POSIX-oriented or command line tasks. Here's three quick reasons why:

• It's everywhere. Like JavaScript for the web, Bash is already there ready for systems programming.
• It's neutral. Unlike Ruby, Python, JavaScript, or PHP, Bash offends equally across all communities. ;)
• It's made to be glue. Write complex parts in C or Go (or whatever!), and glue them together with Bash.

This document is how I write Bash and how I'd like collaborators to write Bash with me in my open source projects. It's based on a lot of experience and time collecting best practices. Most of them come from these two articles, but here integrated, slightly modified, and focusing on the most bang for buck items. Plus some ne

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#!/usr/bin/awk -f
#
# call_graph.awk
#
# Usage:
#   ./call_graph.awk my_program.lua | dot -Tpng > call_graph.png
#
# This is a script that generates a visual call graph for a Lua file.
# This script only shows calls made to functions defined within the
# input Lua file; that is, it excludes calls such as standard library

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Contents

• Articles
• Algorithms
• Coding
• Guides
• Language-specific
  • JavaScript
• Python

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git log --graph --pretty=format:'%Cred%h%Creset -%C(yellow)%d%Creset %s %Cgreen(%cr) %C(bold blue)<%an>%Creset' --abbrev-commit

git config --global alias.lol "log --graph --pretty=format:'%Cred%h%Creset -%C(yellow)%d%Creset %s %Cgreen(%cr) %C(bold blue)<%an>%Creset' --abbrev-commit"

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1. *General Background and Overview*
  * [Probabilistic Data Structures for Web Analytics and Data Mining](http://highlyscalable.wordpress.com/2012/05/01/probabilistic-structures-web-analytics-data-mining/) : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
  * [Models and Issues in Data Stream Systems](http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.106.9846)
  * [Philippe Flajolet’s contribution to streaming algorithms](https://speakerdeck.com/timonk/philippe-flajolets-contribution-to-streaming-algorithms) : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
  * [Approximate Frequency Counts over Data Streams](http://www.vldb.org/conf/2002/S10P03.pdf) by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
  * [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep

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using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Data.SqlClient;
using System.Reflection.Emit;
using System.Collections.Concurrent;
using System.Data;
using System.Reflection;

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.terraform/
*.pem
*.tf
*.tfstate
*.yaml
*.backup
istio-*/
cert-manager-*/
*.swp
env

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curl -fsSL https://get.docker.com | sh
sudo gpasswd -a $USER docker
newgrp docker


# NOTE: you may remove the lines below, if you prefer to use rootful docker, not rootless
sudo systemctl disable --now docker
sudo apt-get install -y uidmap
dockerd-rootless-setuptool.sh install

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fzf --preview '([[ -f {} ]] && (bat --style=numbers --color=always {} || cat {})) || ([[ -d {} ]] && (tree -C {} | less)) || echo {} 2> /dev/null | head -200'

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  public static String point(int x, int y) {
    return String.format("%sx%s", x, y);
  }
                         
  public static int contiguousRegions(int[][] matrix) {
    var seen = new HashSet<String>();
    var count = 0;
    
    for (int i = 0; i < matrix.length; ++i) {
      for (int k = 0; k < matrix[0].length; ++ k) {