start new:
tmux
start new with session name:
tmux new -s myname
#!/bin/bash | |
if [ "$1" = "-h" -o "$1" = "--help" -o -z "$1" ]; then cat <<EOF | |
appify v3.0.1 for Mac OS X - http://mths.be/appify | |
Creates the simplest possible Mac app from a shell script. | |
Appify takes a shell script as its first argument: | |
`basename "$0"` my-script.sh |
# To install the Python client library: | |
# pip install -U selenium | |
# Import the Selenium 2 namespace (aka "webdriver") | |
from selenium import webdriver | |
# iPhone | |
driver = webdriver.Remote(browser_name="iphone", command_executor='http://172.24.101.36:3001/hub') | |
# Android |
import unittest, os, os.path, sys, urllib | |
import tornado.database | |
import tornado.options | |
from tornado.options import options | |
from tornado.testing import AsyncHTTPTestCase | |
# add application root to sys.path | |
APP_ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), '..')) | |
sys.path.append(os.path.join(APP_ROOT, '..')) |
#!/bin/bash | |
# source: http://www.haskell.org/pipermail/haskell-cafe/2011-March/090170.html | |
sudo rm -rf /Library/Frameworks/GHC.framework | |
sudo rm -rf /Library/Frameworks/HaskellPlatform.framework | |
sudo rm -rf /Library/Haskell | |
rm -rf ~/.cabal | |
rm -rf ~/.ghc | |
rm -rf ~/Library/Haskell |
adb shell am | |
usage: am [subcommand] [options] | |
usage: am start [-D] [-W] [-P <FILE>] [--start-profiler <FILE>] | |
[--R COUNT] [-S] [--opengl-trace] <INTENT> | |
am startservice <INTENT> | |
am force-stop <PACKAGE> | |
am kill <PACKAGE> | |
am kill-all | |
am broadcast <INTENT> | |
am instrument [-r] [-e <NAME> <VALUE>] [-p <FILE>] [-w] |
(by @andrestaltz)
If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.
Cython has two major benefits:
Cython gains most of it's benefit from statically typing arguments. However, statically typing is not required, in fact, regular python code is valid cython (but don't expect much of a speed up). By incrementally adding more type information, the code can speed up by several factors. This gist just provides a very basic usage of cython.
A personal diary of DataFrame munging over the years.
Convert Series datatype to numeric (will error if column has non-numeric values)
(h/t @makmanalp)