MrNice

Ansible

Understanding Ansible

Ansible is a powerful, simple, and easy to use tool for managing computers. It is most often used to update programs and configuration on dozens of servers at once, but the abstractions are the same whether you're managing one computer or a hundred. Ansible can even do "fun" things like change the desktop photo or backup personal files to the cloud. It can take a while to learn how to use Ansible because it has an extensive terminology, but once you understand the why and the how of Ansible, its power is readily apparent.

Ansible's power comes from its simplicity. Under the hood, Ansible is just a domain specific language (DSL) for a task runner for a secure shell (ssh). You write ansible yaml (.yml) files which describe the tasks which must run to turn plain old / virtualized / cloud computers into production ready server-beasts. These tasks, in turn, have easy to understand names like "copy", "file", "command", "ping", or "lineinfile". Each of these turns into shell comma

chiragjn

The reStructuredText_ Cheat Sheet: Syntax Reminders

Info:	See <http://docutils.sf.net/rst.html> for introductory docs.
Author:	David Goodger <[email protected]>
Date:	2013-02-20
Revision:	7612
Description:	This is a "docinfo block", or bibliographic field list

Note

If you are reading this as HTML, please read

peterhurford

Using py.test is great and the support for test fixtures is pretty awesome. However, in order to share your fixtures across your entire module, py.test suggests you define all your fixtures within one single conftest.py file. This is impractical if you have a large quantity of fixtures -- for better organization and readibility, you would much rather define your fixtures across multiple, well-named files. But how do you do that? ...No one on the internet seemed to know.

Turns out, however, you can define fixtures in individual files like this:

tests/fixtures/add.py

import pytest

@pytest.fixture

dwilkie

Build docker image

$ cd /path/to/Dockerfile
$ sudo docker build .

View running processes

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

wy193777

"""
This is free and unencumbered software released into the public domain.

Anyone is free to copy, modify, publish, use, compile, sell, or
distribute this software, either in source code form or as a compiled
binary, for any purpose, commercial or non-commercial, and by any
means.

In jurisdictions that recognize copyright laws, the author or authors
of this software dedicate any and all copyright interest in the

mrry

# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,

AlexArcPy

import json
import ogr

driver = ogr.GetDriverByName('ESRI Shapefile')
shp_path = r'C:\GIS\Temp\Counties.shp'
data_source = driver.Open(shp_path, 0)

fc = {
    'type': 'FeatureCollection',
    'features': []

alexellis

This guide has moved to a GitHub repository to enable collaboration and community input via pull-requests.

https://github.com/alexellis/k8s-on-raspbian

Alex

ruxi

# install latest nvidia driver


sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt-get update

# then go to device manager and dl newest driver 
# nvidia-390 for linux >4.13.32 | there is a bug with <nvidia-390 & >linux 4.13.25