Mael laem

sudo docker exec -i -t RUNNING_DOCKER_NAME bash

sudo openssl req -x509 -nodes -newkey rsa:2048 -keyout /etc/cozy/server.key -out /etc/cozy/server.crt -days 365 -subj '/CN=DOMAIN_NAME'

	//JSX code

	<HBar
	// data is an array of {v: 18, label: "Joseph"} objects
	data={randomData()}
	/>


	//CSS

	//JSX code

	<HBar
	data={randomData(9, 10000, true)}
	width="230"
	height="300"
	focus="3" // focus on the 3rd bar
	textPosition="dynamic" // insert texts in bars if possible
	axis="false"
	sort="descending"

	//JSX code

	<HBar
	data={randomData()}
	width="230"
	height="300"
	axis="false"
	sort="descending"
	formatter={formatter}
	//lighten for 150ms an element that appeared or that was reordered. Requires barColor

	#!/bin/bash
	#
	# Fork of https://gist.github.com/senko/1154509#file-onchange-sh

	if [ -z "$1" ]; then
	echo "Specify an rsync dest as first argument"
	exit -1;
	fi

	EVENTS="CREATE,CLOSE_WRITE,DELETE,MODIFY,MOVED_FROM,MOVED_TO"

	https://news.ycombinator.com/item?id=9808021

	No, reducers are about reducing things. Transducers are about creating reducers that can be used on arbitrary collection-like things.

	Reducers come from the observation that many higher order operations on collections can be built on reduce. You just supply the right reducing function and you get the equivalent to 'map' or 'filter'. This is useful because when you start chaining these higher order functions you can gain performance be replacing the multiple function calls with a single reducer based function.

	To take the example from the main docs:

	(fold + (filter even? (map inc [1 1 1 2])))

	import math
	from scipy.optimize import fsolve

	def calculate_net_from(brut):
	print brut[0]
	scenario = tax_benefit_system.new_scenario()
	scenario.init_single_entity(
	period = "2015-11",
	parent1 = dict(
	age = 30,

	(defmacro forever [& body]
	`(while true ~@body))