剛嘗試了怎麼樣在區域網路中使用 WebRTC 來進行 VOIP,意外發現其實滿簡單的。分享一下我的步驟
P.S 這是提供給外部網路不通的環境下,如果外部網路通暢,那麼可以直接用現有服務,如 https://talky.io/ 即可
git clone https://github.com/andyet/signalmaster
剛嘗試了怎麼樣在區域網路中使用 WebRTC 來進行 VOIP,意外發現其實滿簡單的。分享一下我的步驟
P.S 這是提供給外部網路不通的環境下,如果外部網路通暢,那麼可以直接用現有服務,如 https://talky.io/ 即可
git clone https://github.com/andyet/signalmaster
#!/usr/bin/env python | |
# -*- coding: utf-8 -*- | |
import mechanize | |
from colorama import init | |
from colorama import Fore, Back, Style | |
init() | |
def main(): |
function load_efi_video { | |
set gfxmode=auto | |
insmod efi_gop | |
insmod efi_uga | |
insmod gfxterm | |
terminal_output gfxterm | |
} | |
function load_video { | |
set gfxmode=auto |
#!/usr/bin/env python3 | |
# | |
# Copyright 2015 Canonical Ltd. | |
# | |
# Authors: | |
# Daniel Manrique <[email protected]> | |
# | |
# develop-in-lxc is free software: you can redistribute it and/or modify | |
# it under the terms of the GNU General Public License version 3, as | |
# published by the Free Software Foundation. |
lxc.cgroup.devices.allow = c 10:236 rwm
lxc.cgroup.devices.allow = b 252:* rwm
https://wiki.deimos.fr/LXC_:_Install_and_configure_the_Linux_Containers#LXC_control_device_mapper
Curtin has a test suite named vmtest
. It has loads of configs for
installation that put curtin through a battery. As of this writing
it runs 192 installations on amd64 covering all supported ubuntu releases.
It runs nightly under jenkins. See example results in the
curtin-vmtest-devel-amd64 job.
If you're interested just a general use of curtin without starting a VM, see another article 'Curtin Development on uvt-kvm'.
Memo Date: 2018-07-18 MAAS version: 2.3
Curtin’s assumption is that a fairly rich Linux (Ubuntu) environment is booted.
But if your image is not Linux (Ubuntu) based, you could customize the image via:
I hereby claim:
To claim this, I am signing this object:
# Failed trial of airflow subdag with timezone aware | |
from datetime import datetime, timedelta | |
import pendulum | |
from airflow import DAG | |
from airflow.operators.python_operator import PythonOperator | |
from airflow.operators.subdag_operator import SubDagOperator | |
from datetime import datetime, timedelta | |
import pendulum | |
from airflow import DAG | |
from airflow.operators.python_operator import PythonOperator | |
default_args = {"owner": "airflow"} |