jexp

export NEO4J_HOME=${NEO4J_HOME-~/Downloads/neo4j-community-3.0.1}

if [ ! -f data-csv.zip ]; then
  curl -OL https://cloudfront-files-1.publicintegrity.org/offshoreleaks/data-csv.zip
fi
	
export DATA=${PWD}/import

rm -rf $DATA

chiaochi

Year,Picture,Studio,Box Office,Box Office MM,Noms,Wins,Realease Date,ProdBudget,Running Time,Genre,MPAA
2014,Birdman,FoxS,"$42,085,397","$42,000,000",9,4,10/17/14,"$18,000,000",119,Comedy / Drama,R
2013,12 Years a Slave,FoxS,"$56,671,993","$57,000,000",9,3,10/18/13,"$20,000,000",133,Drama,R
2012,Argo,WB,"$136,025,503","$136,000,000",7,3,10/12/12,"$44,500,000",120,Drama / Thriller,R
2011,The Artist,Wein.,"$44,671,682","$45,000,000",10,5,11/25/11,"$15,000,000",100,Comedy / Drama,PG-13
2010,The King's Speech,Wein.,"$135,453,143","$135,000,000",12,4,11/26/10,"$15,000,000",118,Drama,R
2009,The Hurt Locker,Sum.,"$17,017,811","$17,000,000",9,6,6/26/09,"$15,000,000",130,War,R
2008,Slumdog Millionaire,FoxS,"$141,319,928","$141,000,000",10,8,11/12/08,"$15,000,000",120,Drama,R
2007,No Country for Old Men,Mira.,"$74,283,625","$74,000,000",8,4,11/9/07,"$25,000,000",122,Drama,R
2006,The Departed,WB,"$132,384,315","$132,000,000",5,4,10/6/06,"$90,000,000",150,Drama,R

dvcama

CREATE PROCEDURE dump_graphs 
  ( IN  dir               VARCHAR  :=  '{WRITE HERE YOUR EXPORT PATH (allowed dir in virtuoso.ini)}'   , 
    IN  file_length_limit INTEGER  :=  10000000000
  )
  {
    DECLARE inx INT;
    inx := 1;
    SET ISOLATION = 'uncommitted';
    FOR ( SELECT * 
            FROM ( SPARQL DEFINE input:storage ""

darekkay

<?php

/* 
Backup script for trakt.tv (API v2).

Live demo: https://darekkay.com/blog/trakt-tv-backup/
*/

// create a Trakt app to get a client API key: http://docs.trakt.apiary.io/#introduction/create-an-app
$apikey = "CLIENT_API_KEY";

dfkoz

#!/usr/bin/env ruby
require 'nokogiri'
require 'open-uri'
require 'net/http'

open('results.txt', 'wb') do |file|
  (1 .. 94000).step(50).to_a.each do |start|

      dir_url = 'http://www.imdb.com/search/title?at=0&sort=num_votes,desc&start=%s&title_type=tv_series' % start.to_s
      puts dir_url  

ALenfant

def path_cost(graph, path, weights=None):
    pathcost = 0
    for i in range(len(path)):
        if i > 0:
            edge=graph.es.find(_source=path[i-1], _target=path[i])
            if weights != None:
                pathcost += edge[weights]
            else:
                #just count the number of edges
                pathcost += 1

cheme

Misgoals of this misperiment

The first goal to describe a little what would be call misperimenting with graphDB, RDF, and all fun stuff, without being to formal, and (I am very sorry for that) some misenglish everywhere.

And of course if it could help or inspire anyone for more useful tests it should be great (in did this a few month ago but have not time to pursue).

A graphDB for everything

There are not so many graphDB implementations, it is quiet odd considering the hype of NoSql idea and current social graph applications.

jprante

curl -XDELETE 'localhost:9200/jsonld'

curl -XPOST 'localhost:9200/jsonld'

curl -XPUT 'localhost:9200/jsonld/doc/1' -d '
{
  "@context":
  {
    "dc": "http://purl.org/dc/elements/1.1/",

tmcw

import glob, json

# this script loves this script
# https://gist.github.com/3350235

points = []
vids = set()
places = glob.glob("checkins/*.json")

for p in places:

tmcw

import requests, os, glob, json, sys, webbrowser

you = 'self'
data = 'checkins'

try: os.mkdir(data)
except Exception: pass

cid = 'YOUR_CLIENT_ID'