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@rgaidot
rgaidot / TextWithCR.js
Last active August 28, 2019 18:49
Text with carriage returns without dangerouslySetInnerHTML #react
import React, { Fragment } from 'react';
import PropTypes from 'prop-types';
const TextWithCR = ({ text }) => {
const lines = text.split('\n');
return (
<Fragment>
{lines.map(line => (
<Fragment key={line}>
@rgaidot
rgaidot / useStateFetch.js
Last active June 11, 2019 11:46
useStateFetch
import { useState, useEffect } from 'react';
const render = data => match =>
data.pending ? match.pending()
: data.error ? match.error(data.error)
: data.data ? match.data(data.data)
: null;
export const useStateFetch = url => {
const [data, setData] = useState({ pending: true });
@rgaidot
rgaidot / compose-install.service
Created January 28, 2017 13:11
Docker Compose on CoreOS
[Unit]
Description=Docker Compose on CoreOS
After=docker.service
Requires=docker.service
[Service]
Type=oneshot
RemainAfterExit=yes
TimeoutStartSec=0
apiVersion: batch/v1beta1
kind: CronJob
metadata:
annotations:
name: ecr-cred-helper
namespace: default
spec:
concurrencyPolicy: Allow
failedJobsHistoryLimit: 1
jobTemplate:
@rgaidot
rgaidot / the-basics-of-JavaScript-with-arrays.js
Created July 17, 2018 18:56
The basics of JavaScript with Arrays
// Code Challenge #11: JavaScript Functional Programming
// https://scotch.io/bar-talk/code-challenge-11-javascript-functional-programming
// ARRAY 1
const texasss = [{
name: 'Mike',
age: 23,
gender: 'm',
us: false,
@rgaidot
rgaidot / gist:792451
Created January 23, 2011 21:24
Entity Extraction using NLTK
import nltk
text = """Barack Hussein Obama II (born August 4, 1961) is the 44th and current President of the United States. He is the first African American to hold the office. Obama previously served as a United States Senator from Illinois, from January 2005 until he resigned after his election to the presidency in November 2008."""
sentences = nltk.sent_tokenize(text)
tokenized_sentences = [nltk.word_tokenize(sentence) for sentence in sentences]
tagged_sentences = [nltk.pos_tag(sentence) for sentence in tokenized_sentences]
chunked_sentences = nltk.batch_ne_chunk(tagged_sentences, binary=True)
def extract_entity_names(t):
@rgaidot
rgaidot / build_rancheros_for_rpi.sh
Created May 24, 2016 08:52
Build RancherOS for Raspberry Pi
#!/bin/zsh
git clone https://github.com/rancher/os.git
cd os/scripts/images/rpi-hypriot
docker build -f Dockerfile.dapper --pull -t rancheros/rpi .
docker run -ti --privileged -v `pwd`/scripts/build.sh:/source/scripts/build.sh -v `pwd`/dist:/source/dist rancheros/rpi
echo ---
echo Done!
echo Now you can unzip rancheros-rpi2.zip in os/scripts/images/rpi-hypriot/dist
@rgaidot
rgaidot / gist:72e34ca92f62382e7b9c18afc06b5762
Created June 16, 2017 08:24 — forked from rxaviers/gist:7360908
Complete list of github markdown emoji markup

People

:bowtie: :bowtie: 😄 :smile: 😆 :laughing:
😊 :blush: 😃 :smiley: ☺️ :relaxed:
😏 :smirk: 😍 :heart_eyes: 😘 :kissing_heart:
😚 :kissing_closed_eyes: 😳 :flushed: 😌 :relieved:
😆 :satisfied: 😁 :grin: 😉 :wink:
😜 :stuck_out_tongue_winking_eye: 😝 :stuck_out_tongue_closed_eyes: 😀 :grinning:
😗 :kissing: 😙 :kissing_smiling_eyes: 😛 :stuck_out_tongue:

There are three easy to make mistakes in go. I present them here in the way they are often found in the wild, not in the way that is easiest to understand.

All three of these mistakes have been made in Kubernetes code, getting past code review at least once each that I know of.

  1. Loop variables are scoped outside the loop.

What do these lines do? Make predictions and then scroll down.

func print(pi *int) { fmt.Println(*pi) }
@rgaidot
rgaidot / gitflow-breakdown.md
Created September 12, 2016 16:24 — forked from JamesMGreene/gitflow-breakdown.md
A comparison of using `git flow` commands versus raw `git` commands.

Initialize

gitflow git
git flow init git init
git commit --allow-empty -m "Initial commit"
git checkout -b develop master

Connect to the remote repository