alejandrobernardis

#!/bin/bash

# generate new personal ed25519 ssh key
ssh-keygen -o -a 100 -t ed25519 -f ~/.ssh/id_ed25519 -C "rob thijssen <rthijssen@gmail.com>"

# generate new host cert authority (host_ca) ed25519 ssh key
# used for signing host keys and creating host certs
ssh-keygen -t ed25519 -f manta_host_ca -C manta.network

eval "$(ssh-agent -s)"

alejandrobernardis

#!/bin/bash

#Harbor on Ubuntu 18.04

#Prompt for the user to ask if the install should use the IP Address or Fully Qualified Domain Name of the Harbor Server
PS3='Would you like to install Harbor based on IP or FQDN? '
select option in IP FQDN
do
    case $option in
        IP)

alejandrobernardis

"""
The most simple DNS client written for Python with asyncio:

* Only A record is support (no CNAME, no AAAA, no MX, etc.)
* Almost no error handling
* Doesn't  support fragmented UDP packets (is it possible?)

"""
import asyncio
import logging

alejandrobernardis

"""Demo of streaming requests with Tornado.

This script features a client using AsyncHTTPClient's body_producer
feature to slowly produce a large request body, and two server
handlers to receive this body (one is a proxy that forwards to the
other, also using body_producer).

It also demonstrates flow control: if --client_delay is smaller than
--server_delay, the client will eventually be suspended to allow the
server to catch up. You can see this in the logs, as the "client

alejandrobernardis

#!/usr/bin/env python
"""This is a demonstration of sharing file descriptors across processes.

It uses Tornado (need a recent post-2.0 version from github) and the
multiprocessing module (from python 2.6+).  To run it, start one copy
of fdserver.py and one or more copies of testserver.py (in different
terminals, or backgrounded, etc).  Fetch http://localhost:8000 and
you'll see the requests getting answered by different processes (it's
normal for several requests to go to the same process under light
load, but under heavier load it tends to even out).

alejandrobernardis

import macropy.activate
import test

alejandrobernardis

"""Demo of streaming requests with Tornado.

This script features a client using AsyncHTTPClient's body_producer
feature to slowly produce a large request body, and two server
handlers to receive this body (one is a proxy that forwards to the
other, also using body_producer).

It also demonstrates flow control: if --client_delay is smaller than
--server_delay, the client will eventually be suspended to allow the
server to catch up. You can see this in the logs, as the "client

alejandrobernardis

Asynchronous programming with Tornado

Asynchronous programming can be tricky for beginners, therefore I think it's useful to iron some basic concepts to avoid common pitfalls.

For an explanation about generic asynchronous programming, I recommend you one of the [many][2] [resources][3] [online][4].

I will focus on solely on asynchronous programming in [Tornado][1]. From Tornado's homepage:

alejandrobernardis

import concurrent.futures


class ProcessManager(object):

    def __init__(self):
        self.pool = concurrent.futures.ProcessPoolExecutor()
        self.futures = {}

    def submit(self, f, *args, **kwargs):

alejandrobernardis

from tornado import stack_context as old, new_stack as new


def exc(type, value, tb):
    return True


def non_exc(type, value, tv):
    pass