thomasdarimont

import json
import logging

from flask import Flask, g
from flask_oidc import OpenIDConnect
import requests

logging.basicConfig(level=logging.DEBUG)

app = Flask(__name__)

orenitamar

# Below are the dependencies required for installing the common combination of numpy, scipy, pandas and matplotlib 
# in an Alpine based Docker image.
FROM alpine:3.4
RUN echo "http://dl-8.alpinelinux.org/alpine/edge/community" >> /etc/apk/repositories
RUN apk --no-cache --update-cache add gcc gfortran python python-dev py-pip build-base wget freetype-dev libpng-dev openblas-dev
RUN ln -s /usr/include/locale.h /usr/include/xlocale.h
RUN pip install numpy scipy pandas matplotlib

lilongen

Question:
. How to run Ansible without specifying the inventory but the host directly?
. Run a playbook or command with arbitrary host not in the inventory hosts list?
. run ansible with arbitrary host/ip without inventory?

Answer:
Surprisingly, the trick is to append a ,
The host parameter preceding the , can be either a hostname or an IPv4/v6 address.

ansible all -i example.com,

dimitardanailov

server {
  listen 80 default deferred;

  server_name myapp.com;

  root /var/www/project-folder/;

  # Nginx and Angularjs with html mode 5 - https://gist.github.com/cjus/b46a243ba610661a7efb
  index index.html;

quimbs

var findFundamentalFreq = function(buffer, sampleRate) {
	// We use Autocorrelation to find the fundamental frequency.
	
	// In order to correlate the signal with itself (hence the name of the algorithm), we will check two points 'k' frames away. 
	// The autocorrelation index will be the average of these products. At the same time, we normalize the values.
	// Source: http://www.phy.mty.edu/~suits/autocorrelation.html
	// Assuming the sample rate is 48000Hz, a 'k' equal to 1000 would correspond to a 48Hz signal (48000/1000 = 48), 
	// while a 'k' equal to 8 would correspond to a 6000Hz one, which is enough to cover most (if not all) 
	// the notes we have in the notes.json file.
	var n = 1024, bestR = 0, bestK = -1;

feklee

Introduction

Collection of solutions for streaming via DASH, Dynamic Adaptive Streaming over HTTP, as of November 2014.

Recommended client: Chrome 38

Tool used for encoding live streams: FFmpeg