I can never find a great guide on this stuff, so these are more like notes to myself.
The goal here is to have a virtualbox running more or less headless. An ssh client is used separately to actually use the machine. I've found it to be fantastic for a quick dev setup.
Assumes you have a vbox setup with Ubuntu server (this will work for 16.04) ready to go.
| #!/usr/bin/python | |
| import serial | |
| import signal | |
| import sys | |
| import time | |
| def BinaryModeEnter(connection): | |
| connection.flushInput() | |
| for x in range(0, 20): # Try at most 20 times |
| /* | |
| AnalogReadSerial | |
| Reads an analog input on pin 0, prints the result to the serial monitor. | |
| Attach the center pin of a potentiometer to pin A0, and the outside pins to +5V and ground. | |
| This example code is in the public domain. | |
| Upload this to the Arduino using the Arduino IDE! | |
| */ |
| /* | |
| * This sketch sends ads1115 current sensor data via HTTP POST request to thingspeak server. | |
| * It needs the following libraries to work (besides the esp8266 standard libraries supplied with the IDE): | |
| * | |
| * - https://github.com/adafruit/Adafruit_ADS1X15 | |
| * | |
| * designed to run directly on esp8266-01 module, to where it can be uploaded using this marvelous piece of software: | |
| * | |
| * https://github.com/esp8266/Arduino | |
| * |
| #!/bin/sh -e | |
| # | |
| # NOTE: Since Docker 1.10 (February 4, 2016), it has been possible to configure the | |
| # Docker daemon using a JSON config file. On Linux, this file is normally located at | |
| # /etc/docker/daemon.json. You should use this JSON config method if you are running | |
| # a version of Docker that is at least 1.10! | |
| # Here is an example configuration that sets the docker0 bridge IP to 192.168.254.1/24: | |
| # { | |
| # "bip": "192.168.254.1/24" | |
| # } |
| ##### ##### ##### ##### ##### ##### ##### ##### ##### ##### ##### ##### ##### ##### ##### ##### ##### | |
| ### Shell script to download Oracle JDK / JRE / Java binaries from Oracle website using terminal / command / shell prompt using wget. | |
| ### You can download all the binaries one-shot by just giving the BASE_URL. | |
| ### Script might be useful if you need Oracle JDK on Amazon EC2 env. | |
| ### Script is updated for every JDK release. | |
| ### Features:- | |
| # 1. Resumes a broken / interrupted [previous] download, if any. | |
| # 2. Renames the file to a proper name with including platform info. |
| # Create a log format called 'logstash_json' that emits, in json, the parts of an http | |
| # request I care about. For more details on the features of the 'LogFormat' | |
| # directive, see the apache docs: | |
| # http://httpd.apache.org/docs/2.2/mod/mod_log_config.html#formats | |
| # http://cookbook.logstash.net/recipes/apache-json-logs/ | |
| LogFormat "{ \"@timestamp\": \"%{%Y-%m-%dT%H:%M:%S%z}t\", \"@message\": \"%m %H %U%q %s\", \"@fields\": { \"client\": \"%a\", \"duration_usec\": %D, \"status\": %s, \"request\": \"%U%q\", \"method\": \"%m\", \"protocol\": \"%H\", \"referrer\": \"%{Referer}i\", \"user-agent\": \"%{User-agent}i\" } }" logstash_json | |
| # Apache 2.4 adds sub-second precision logging | |
| # http://httpd.apache.org/docs/2.4/mod/mod_log_config.html#formats | |
| # LogFormat "{ \"@timestamp\": \"%{%Y-%m-%dT%H:%M:%S}t.%{msec_frac}t%{%z}t\", \"@message\": \"%m %H %U%q %s\", \"@fields\": { \"client\": \"%a\", \"duration_usec\": %D, \"status\": %s, \"request\": \"%U%q\", \"method\": \"%m\", \"protocol\": \"%H\", \"referrer\": \"%{Refer |
Eric Bidelman has documented some of the common workflows possible with headless Chrome over in https://developers.google.com/web/updates/2017/04/headless-chrome.
If you're looking at this in 2016 and beyond, I strongly recommend investigating real headless Chrome: https://chromium.googlesource.com/chromium/src/+/lkgr/headless/README.md
Windows and Mac users might find using Justin Ribeiro's Docker setup useful here while full support for these platforms is being worked out.
| #! /usr/bin/python | |
| """Implementation of the arrow abstraction for functions. | |
| Abstracting functions with Arrows has advantages. Arrows make it very easy to | |
| compose functions (by simply 'multiplying' them with the `*` operator). The | |
| order in which the arrows are written match the order of the computations, | |
| making long pipelines easy to work with. Arrows also provide mechanisms for | |
| creating and merging branches, which helps when a value needs to be consumed by | |
| several functions, or when a function needs values from several sources. Arrows | |
| can also support conditional application, selecting which of two functions f and |
| """Simple but robust implementation of generator/coroutine-based | |
| pipelines in Python. The pipelines may be run either sequentially | |
| (single-threaded) or in parallel (one thread per pipeline stage). | |
| This implementation supports pipeline bubbles (indications that the | |
| processing for a certain item should abort). To use them, yield the | |
| BUBBLE constant from any stage coroutine except the last. | |
| In the parallel case, the implementation transparently handles thread | |
| shutdown when the processing is complete and when a stage raises an |