junegunn

# GIT heart FZF
# -------------

is_in_git_repo() {
  git rev-parse HEAD > /dev/null 2>&1
}

fzf-down() {
  fzf --height 50% --min-height 20 --border --bind ctrl-/:toggle-preview "$@"
}

audreyfeldroy

• Update HISTORY.md
• Commit the changes:

git add HISTORY.md
git commit -m "Changelog for upcoming release 0.1.1."

• Update version number (can also be minor or major)

bumpversion patch

cuppster

#!/usr/bin/env python
# -*- coding: utf-8 -*-

import sys, re
import itertools
from functools import wraps
from pyquery import PyQuery as pq

class scrape:
  

Nurdok

Python Number Conversion Chart

From	To	Expression

mrjoes

1. pip install -r reqs.pip
2. server.py
3. open client.html in browser
4. redis-cli publish push '123456'
5. check browser console

evildmp

This document has now been incorporated into the uWSGI documentation:

http://uwsgi-docs.readthedocs.org/en/latest/tutorials/Django_and_nginx.html

Set up Django, nginx and uwsgi

Steps with explanations to set up a server using:

erikh

#!/usr/bin/env sh

##
# This is script with usefull tips taken from:
#   https://github.com/mathiasbynens/dotfiles/blob/master/.osx
#
# install it:
#   curl -sL https://raw.github.com/gist/2108403/hack.sh | sh
#

hrldcpr

One-line Tree in Python

Using Python's built-in defaultdict we can easily define a tree data structure:

def tree(): return defaultdict(tree)

That's it!

rapimo

-- ~/Library/Application\ Support/iTerm/Scripts/setup_rails.scpt
-- Thanks to http://www.worldgoneweb.com/2011/iterm2-advanced-features/#comment-20560
-- http://www.iterm2.com/#/section/documentation/scripting
tell application "iTerm" 
        activate
	set myterm to (make new terminal)
	set cd_to_my_project_path to ("cd ~/Projekte/my_awesome_project")
--	you can altenativly tell the first terminal		
        tell the first terminal			
		launch session "Panes"		        

entaroadun

Movies Recommendation:

• MovieLens - Movie Recommendation Data Sets http://www.grouplens.org/node/73
• Yahoo! - Movie, Music, and Images Ratings Data Sets http://webscope.sandbox.yahoo.com/catalog.php?datatype=r
• Jester - Movie Ratings Data Sets (Collaborative Filtering Dataset) http://www.ieor.berkeley.edu/~goldberg/jester-data/
• Cornell University - Movie-review data for use in sentiment-analysis experiments http://www.cs.cornell.edu/people/pabo/movie-review-data/

Music Recommendation:

• Last.fm - Music Recommendation Data Sets http://www.dtic.upf.edu/~ocelma/MusicRecommendationDataset/index.html