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Intro

The plan is to create a pair of executables (ngrok and ngrokd) that are connected with a self-signed SSL cert. Since the client and server executables are paired, you won't be able to use any other ngrok to connect to this ngrokd, and vice versa.

DNS

Add two DNS records: one for the base domain and one for the wildcard domain. For example, if your base domain is domain.com, you'll need a record for that and for *.domain.com.

Different Operating Systems

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How to setup Let's Encrypt for Nginx on Ubuntu 16.04 (including IPv6, HTTP/2 and A+ SLL rating)

There are two main modes to run the Let's Encrypt client (called Certbot):

• Standalone: replaces the webserver to respond to ACME challenges
• Webroot: needs your webserver to serve challenges from a known folder.

Webroot is better because it doesn't need to replace Nginx (to bind to port 80).

In the following, we're setting up mydomain.com. HTML is served from /var/www/mydomain, and challenges are served from /var/www/letsencrypt.

PatWie

# -*- coding: utf-8 -*-
# File: base.py
# Author: Patrick Wieschollek <[email protected]>

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function


import numpy as np

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#!/bin/bash
# Patrick Wieschollek

# =============================================================
# UPDATE SOURCE
# =============================================================
git checkout -- .
git pull origin master

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import tensorflow as tf
from tensorflow.python.ops import data_flow_ops
import time
from contextlib import contextmanager


@contextmanager
def benchmark(name="unnamed context"):
    elapsed = time.time()
    yield

PatWie

import numpy
import zmq

def send_array(socket, A, flags=0, copy=True, track=False):
    """send a numpy array with metadata"""
    md = dict(
        dtype = str(A.dtype),
        shape = A.shape,
    )
    socket.send_json(md, flags|zmq.SNDMORE)

PatWie

# zmqimage.py -- classes to send, receive and display cv2 images via zmq
#     based on serialization in pyzmq docs and pyzmq/examples/serialization

'''
PURPOSE:
    These classes allow a headless (no display) computer running OpenCV code
    to display OpenCV images on another computer with a display.
    For example, a headless Raspberry Pi with no display can run OpenCV code
    and can display OpenCV images on a Mac with a display.
USAGE:

PatWie

import tensorflow as tf


# save
dummy = tf.Variable(tf.truncated_normal(shape=[10]), name='dummy')
with tf.Session() as sess:
  saver = tf.train.Saver()
  sess.run(tf.global_variables_initializer())
  expected = sess.run(tf.reduce_sum(dummy))
  saver.save(sess, 'model')

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'''
These functions take a dictionary of dependencies in the following way:

depdict = { 'a' : [ 'b', 'c', 'd'],
            'b' : [ 'c', 'd'],
            'e' : [ 'f', 'g']
            }

PatWie

Here is a list of scopes to use in Sublime Text 2 snippets - 

ActionScript: source.actionscript.2
AppleScript: source.applescript
ASP: source.asp
Batch FIle: source.dosbatch
C#: source.cs
C++: source.c++
Clojure: source.clojure
CoffeeScript: source.coffee