Discover rickfarmer/tether Open Source project

Stars
36
Rank 735,472 (Top 15 %)
Language
C
License
GNU General Publi...
Created over 10 years ago
Updated over 10 years ago

rickfarmer

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Internet tether proxy for iOS and Android. Internet connection sharing for iPhone, iPad, and Android. Share your phones internet connection with other devices including your PC or Mac. This is a simplified, cross-platform implementation of a wi-fi tethering web proxy for sharing internet connections from your iOS or Android devices.

android-vm

Automated provisioning and configuration of an Ubuntu VM containing the Android development environment, including Android ADT Bundle with SDK, Eclipse & the Android NDK using the Vagrant DevOps tool with Chef and shell-scripts.

Shell

103

data-science-vm

A Big Data Analytics VM for doing Data Science. It provides a huge kickstart to those working with the Big Data Analytics side of Data Science. Essentially, this project automates the creation of the Big Data Scientist's toolbox on a virtual machine (VM). In a few minutes one can begin working with a fully configured data science lab instead of performing the complex installations and configuration required for a functioning development environment. The Data Scientist's VM includes R, Git, Python, Cloudera, Hadoop, YARN, MRv2, Mahout, MongoDB, Spark, Neo4j, etc. pre-installed. The Data Scientist's Toolbox VM is automatically built for you on a single CentOS VM using the Vagrant DevOps tool with Chef and shell-scripts for VMware Fusion.

Ruby

bin

OS X dotfiles for custom shell configuration

Ruby

big-data-wordcount

A simplified starter project for Big Data Analytics/Big Data Science with Hadoop Yarn. Integrated with Spring Boot and Spring for Hadoop to provide a unified configuration model and access to easy to use APIs for using HDFS, MapReduce, Pig, and Hive with built-in local deployment. Yes, you heard right -- there is no need to have a Hadoop cluster running to test your code! This project will spin up Hadoop on demand for you locally and then spin it back down after running your MapReduce code.