terrancesnyder

// Show how to handle Ctrl+C in Node.js

var zmq = require('zmq')
  , socket = zmq.createSocket('rep');

socket.on('message', function(buf) {
  // echo request back
  socket.send(buf);
});

BretFisher

sudo: required #is required to use docker service in travis

language: php #can be any language, just php for example

services:
  - docker # required, but travis uses older version of docker :(

install:
  - echo "install nothing!" # put your normal pre-testing installs here

cosmincatalin

#!/bin/bash

# These variables can be overwritten using the arguments below
VERSION="1.1.463"
# drwho is listed as user in YARN's Resource Manager UI.
USER="drwho"
# Depending on where the EMR cluster lives, you might have to change this to avoid security issues.
# To change the default password (and user), use the arguments bellow.
# If the cluster is not visible on the Internet, you can just leave the defaults for convenience.
PASS="tardis"

cosmincatalin

AWS EMR bootstrap to install R packages from CRAN

This bootstrap is useful if you want to deploy SparkR applications that run arbitrary code on the EMR cluster's workers. The R code will need to have its dependencies already installed on each of the workers, and will fail otherwise. This is the case if you use functions such as gapply or dapply.

How to use the bootstrap

1. You will first have to download the gist to a file and then upload it to S3 in a bucket of your choice.
2. Using the AWS EMR Console create a cluster and choose advanced options.
3. In Step 3 you can configure your bootstraps. Choose to Configure and add a Custom action

roylee0704

docker logs nginx 2>&1 | grep "127." 

# ref: http://stackoverflow.com/questions/34724980/finding-a-string-in-docker-logs-of-container

nicor88

#!/usr/bin/env bash
set -x -e

JUPYTER_PASSWORD=${1:-"myJupyterPassword"}
NOTEBOOK_DIR=${2:-"s3://myS3Bucket/notebooks/"}

# home backup
if [ ! -d /mnt/home_backup ]; then
  sudo mkdir /mnt/home_backup
  sudo cp -a /home/* /mnt/home_backup

milesrichardson

const AWS = require('aws-sdk');
const fs = require('fs')

const s3download = (bucketName, keyName, localDest) => {

    if (typeof localDest == 'undefined') {
        localDest = keyName;
    }

    let params = {

jancurn

const Apify = require('apify');

Apify.main(async () => {
    const requestQueue = await Apify.openRequestQueue();
    await requestQueue.addRequest(new Apify.Request({ url: 'https://www.iana.org/' }));
    const pseudoUrls = [new Apify.PseudoUrl('https://www.iana.org/[.*]')];

    const crawler = new Apify.PuppeteerCrawler({
        requestQueue,
        handlePageFunction: async ({ request, page }) => {

kppullin

Overview

The steps below bootstrap an instance of airflow, configured to use the kubernetes airflow executor, working within a minikube cluster.

This guide works with the airflow 1.10 release, however will likely break or have unnecessary extra steps in future releases (based on recent changes to the k8s related files in the airflow source).

Prerequisites

• Docker installed
• Minikube installed and started

arnaud9

from airflow import DAG
from airflow.operators import DummyOperator, PythonOperator

default_args = {
    'owner': 'arnaud',
    'start_date': datetime(2019, 1, 1),
    'retry_delay': timedelta(minutes=5)
}
# Using the context manager alllows you not to duplicate the dag parameter in each operator
with DAG('S3_dag_test', default_args=default_args, schedule_interval='@once') as dag: