Rodolfo Ferro RodolfoFerro

To forward X11 from inside a docker container to a host running macOS

Install XQuartz: https://www.xquartz.org/
Launch XQuartz. Under the XQuartz menu, select Preferences
Go to the security tab and ensure "Allow connections from network clients" is checked.
Run xhost + ${hostname} to allow connections to the macOS host *
Setup a HOSTNAME env var export HOSTNAME=`hostname`*
Add the following to your docker-compose:

 environment:

refer to: https://stackoverflow.com/questions/39371772/how-to-install-anaconda-on-raspberry-pi-3-model-b

{USER}: pi

Install Miniconda 3:

wget http://repo.continuum.io/miniconda/Miniconda3-latest-Linux-armv7l.sh
sudo md5sum Miniconda3-latest-Linux-armv7l.sh # (optional) check md5
sudo /bin/bash Miniconda3-latest-Linux-armv7l.sh # -&gt; change default directory to /home/pi/miniconda3

What is this gist?

Explanation of a fullstack deployment of wagtail in a dockerized environment with Nginx, Elasticsearch, Postgres and Memcached

Required Skills:

docker
docker-compose
get a local wagtail site running

Obfuscating Python

Obfuscation isn't difficult in most programming languages. It's why we have "good practices" because it is so easy to hide what you mean in badly written code.

Obfuscation tends to be even easier in dynamic languages because of how forgiving they tend to be - and because they tend to give you direct access to the environment so that you can manipulate it.

Today, for fun, I'm going to obfuscate this code:

def _(n):

if n <= 0:

First steps with the Luigi workflow manager

As an introduction into Luigi, I am following this tutorial with some modifications, e.g. installation using conda.

The problems and solutions described in the examples below have led to the development of sciluigi,

	# Objective
	# Use non-linear curve fitting to estimate the relaxation rate of an exponential
	# decaying signal.

	# Steps
	# 1. Simulate data (instead of collecting data)
	# 2. Define the objective function for the least squares algorithm
	# 3. Perform curve fitting
	# 4. Compare results

	#!/usr/bin/env python3
	#ps3 wireless controller interface by Robin Newman July 2017
	#converts controller inputs to OSC messages
	#which can be output to Sonic Pi 3, running on the local computer, or on an external machine
	#rtested with ps3 "afterglow" wireless controller, dongle in Pi usb socket
	#needs sudo apt-get install joystick after sudo apt-get update
	#also needs sudo pip3 install python-osc
	#Version 2. Modified to ensure clean exit on Ubuntu

	import subprocess,pygame,sys

	#Program to drive Sonic Pi 3 visualiser written in "processing"
	#by Robin Newman, September 2017
	#see article at https://rbnrpi.wordpress.com
	#set up OSC address of processing sketch
	use_osc '127.0.0.1',5000
	#select shapes to show
	osc "/viz/shapes","e" #"s" "e" "r" Star,Ellipse, Rectangle or combination
	sleep 0.1

	live_loop :c do

	# @Author: xiewenqian <int>
	# @Date: 2016-11-28T20:35:09+08:00
	# @Email: [email protected]
	# @Last modified by: int
	# @Last modified time: 2016-12-01T19:32:48+08:00


	import pandas as pd
	from pymongo import MongoClient

	#!/bin/bash

	airflow run add_gcp_connection add_gcp_connection_python 2001-01-01