jun9

Install raspbian, set up your users however you would like, so long as you have sudo access on the user you are running this with. You probably want to resize the image so it fills the SD card as well.

Copy this entire gist to your raspberry pi
Do chmod +x step1.sh step2.sh iptables.sh in the gist folder (so that
Run step1.sh a) This script does a few things - it first updates your raspberry pi, then it installs a few needed utilities, then it upgrades the firmware on your raspberry pi

Determine the package name of the app, e.g. "com.example.someapp". Skip this step if you already know the package name.

adb shell pm list packages

Look through the list of package names and try to find a match between the app in question and the package name. This is usually easy, but note that the package name can be completely unrelated to the app name. If you can't recognize the app from the list of package names, try finding the app in Google Play using a browser. The URL for an app in Google Play contains the package name.

Get the full path name of the APK file for the desired package.

Each of these commands will run an ad hoc http static server in your current (or specified) directory, available at http://localhost:8000. Use this power wisely.

Discussion on reddit.

Python 2.x

$ python -m SimpleHTTPServer 8000

% Title % Name % Date

My first slide

List

	Byobu is a suite of enhancements to tmux, as a command line
	tool providing live system status, dynamic window management,
	and some convenient keybindings:

	F1 * Used by X11 *
	Shift-F1 Display this help
	F2 Create a new window
	Shift-F2 Create a horizontal split
	Ctrl-F2 Create a vertical split
	Ctrl-Shift-F2 Create a new session

	data_sets <- c("mtcars")

	shinyServer(function(input, output) {

	# Drop-down selection box for which data set
	output$choose_dataset <- renderUI({
	selectInput("dataset", "Data set", as.list(data_sets))
	})

	# select a car

	from sklearn.datasets import load_iris
	from sklearn.ensemble import RandomForestClassifier
	import pandas as pd
	import numpy as np

	iris = load_iris()
	df = pd.DataFrame(iris.data, columns=iris.feature_names)
	df['is_train'] = np.random.uniform(0, 1, len(df)) <= .75
	df['species'] = pd.Factor(iris.target, iris.target_names)
	df.head()

	Byobu Commands
	==============

	byobu Screen manager


	Level 0 Commands (Quick Start)
	------------------------------

	<F2> Create a new window

	<html>
	<head>
	<script src="http://ajax.googleapis.com/ajax/libs/jquery/1.9.0/jquery.min.js" type="text/javascript"></script>
	<script src="http://www.skulpt.org/js/skulpt.min.js" type="text/javascript"></script>
	<script src="http://www.skulpt.org/js/skulpt-stdlib.js" type="text/javascript"></script>

	</head>

	<body>