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# this script has been tested and worked in a freshly installed Ubuntu 16.04 and 16.10
# it assumes that you are running airflow in a private netowrk and no need to be worry about outside access
# if that's not the case, the lines for PostgreSQL and Redis in this script need to be updated accordingly
# run as root
sudo su

# initial system updates and installs
apt-get update && apt-get upgrade -y && apt-get autoremove && apt-get autoclean

apt-get -y install build-essential binutils gcc make git htop nethogs tmux

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https://airflow.readthedocs.io/en/latest/start.html

sudo apt-get install python3-pip

sudo apt-get install postgresql postgresql-contrib

sudo -u postgres createuser --interactive

name: airflow
superuser: yes

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# install
mkdir ~/airflow
cd ~/airflow
pip install airflow
# Have a look here if you need additional packages: https://airflow.incubator.apache.org/installation.html

# setup mysql backend as given here. The default SQLite is not adequate for some workloads.
# http://site.clairvoyantsoft.com/installing-and-configuring-apache-airflow/
 
# start services

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# Given a text string, remove all non-alphanumeric
# characters (using Unicode definition of alphanumeric).

def stripNonAlphaNum(text):
    import re
    return re.compile(r'\W+', re.UNICODE).split(text)

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Live streaming mpeg-dash video using ffmpeg and dash.js

Use ffmpeg to connect to an ip cctv camera and create video files on the fly that can be viewed in an mpeg-dash compatible browser using dash.js and an html5 video element.

Prerequisites

A linux server, such as Ubuntu

Apache web server installed, running, and reachable via its ip address

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import os
import airflow
from airflow import models, settings
from airflow.contrib.auth.backends.password_auth import PasswordUser


def create_admin_user(uname, pwd, email):
  user = PasswordUser(models.User())
  user.username = uname
  user.email = email

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ffmpeg -i input.mp3 -acodec pcm_s16le -ac 1 -ar 16000 output.wav

# To convert all mp3 files in a directory in Linux:

for f in *.mp3; do ffmpeg -i "$f" -acodec pcm_s16le -ac 1 -ar 16000 "${f%.mp3}.wav"; done

# Or Windows:

for /r %i in (*) do ffmpeg -i %i -acodec pcm_s16le -ac 1 -ar 16000 %i.wav

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ON MASTER

$ yum install mariadb-server
$ systemctl restart mariadb
$ systemctl enable mariadb
$ mysql_secure_installation

On /etc/my.cnf, add

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Develop a Flask Application using MariaDB, Redis and Celery on Ubuntu 14.04

@credit Yan Zhu (https://github.com/nina-zhu)

Introduction

Before you start this guide, you should run through the "How To Serve Flask Applications with uWSGI and Nginx on Ubuntu 14.04" guide. This is necessary in order to set up virtualenv, uWSGI and Nginx. In that guide, we developed a very simple flask application having just 1 file "firstflask.py" with only 9 lines of code, it is a sample for showing you the general steps. In this guide, we will create a complete user session listing application, with login, logout functionality. We will use MariaDB to store the users records, and use Redis to store the session data and background tasks.

Let's get started.

Set Up the MariaDB Server

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docker run --privileged -it -v /var/run/docker.sock:/var/run/docker.sock jongallant/ubuntu-docker-client 
docker run --net=host --ipc=host --uts=host --pid=host -it --security-opt=seccomp=unconfined --privileged --rm -v /:/host alpine /bin/sh
chroot /host