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Multi user nix installation

Each section should be run as the user or as root, pay attention to which one!

Install nix single user

As $USER

curl https://nixos.org/nix/install | sh
@mikeball
mikeball / core.clj
Last active June 3, 2020 13:22
Postgres listen/notify in Clojure using http://impossibl.github.io/pgjdbc-ng/
; Postgres listen/notify in Clojure using http://impossibl.github.io/pgjdbc-ng/
; in project.clj dependencies
; [com.impossibl.pgjdbc-ng/pgjdbc-ng "0.5"]
(ns pglisten.core
(:import [com.impossibl.postgres.jdbc PGDataSource]
[com.impossibl.postgres.api.jdbc PGNotificationListener]))
@alexedwards
alexedwards / gist:4d20c505f389597c3360
Last active January 25, 2016 02:07
Illustration of using httprouter and stack
package main
import (
"fmt"
"github.com/alexedwards/stack"
"github.com/julienschmidt/httprouter"
"net/http"
)
func main() {
@bendc
bendc / functional-utils.js
Last active September 15, 2023 12:12
A set of pure ES2015 functions aimed to make functional JavaScript more idiomatic.
// array utils
// =================================================================================================
const combine = (...arrays) => [].concat(...arrays);
const compact = arr => arr.filter(Boolean);
const contains = (() => Array.prototype.includes
? (arr, value) => arr.includes(value)
: (arr, value) => arr.some(el => el === value)
@tkafka
tkafka / LICENSE.txt
Last active May 17, 2024 02:08
Drop-in replacement for ReactCSSTransitionGroup that uses velocity.js instead of CSS transforms. Add your own transitions to `transitions` hash.
The MIT License (MIT)
Copyright (c) 2014 Tomas Kafka
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
@dpwiz
dpwiz / Hedis.hs
Last active August 29, 2015 14:01
Scotty application skeleton
module Hedis
(
-- * Application classes
HasRedis(..)
-- * App-wrapped redis runner
, redis
-- * Re-export other stuff from "Database.Redis"
, module R
) where
@thomasfr
thomasfr / Git push deployment in 7 easy steps.md
Last active July 3, 2024 02:22
7 easy steps to automated git push deployments. With small and configurable bash only post-receive hook
@lelandbatey
lelandbatey / whiteboardCleaner.md
Last active June 16, 2024 13:44
Whiteboard Picture Cleaner - Shell one-liner/script to clean up and beautify photos of whiteboards!

Description

This simple script will take a picture of a whiteboard and use parts of the ImageMagick library with sane defaults to clean it up tremendously.

The script is here:

#!/bin/bash
convert "$1" -morphology Convolve DoG:15,100,0 -negate -normalize -blur 0x1 -channel RBG -level 60%,91%,0.1 "$2"

Results

@jfromaniello
jfromaniello / gist:8418116
Last active September 19, 2023 23:38
Example of authenticating websockets with JWTs.
var WebSocketServer = require('ws').Server;
var wss = new WebSocketServer({port: 8080});
var jwt = require('jsonwebtoken');
/**
The way I like to work with 'ws' is to convert everything to an event if possible.
**/
function toEvent (message) {
try {
@debasishg
debasishg / gist:8172796
Last active July 5, 2024 11:53
A collection of links for streaming algorithms and data structures

General Background and Overview

  1. Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
  2. Models and Issues in Data Stream Systems
  3. Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
  4. Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
  5. [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t