Metadata in PDF files can be stored in at least two places:
- the Info Dictionary, a limited set of key/value pairs
- XMP packets, which contain RDF statements expressed as XML
# Bash function gen_random_filename | |
# Description: Generates random file names | |
# Requires shuf (brew install coreutils) | |
# Requires a list of adjectives and nouns (1 per line) | |
gen_random_filename() { | |
local adjs=~/words/adjectives.txt | |
local nouns=~/words/nouns.txt | |
local adj noun title starts_with_1 starts_with_2 counter |
// Traverses an arbitrary struct and translates all stings it encounters | |
// | |
// I haven't seen an example for reflection traversing an arbitrary struct, so | |
// I want to share this with you. If you encounter any bugs or want to see | |
// another example please comment. | |
// | |
// The MIT License (MIT) | |
// | |
// Copyright (c) 2014 Heye Vöcking | |
// |
#!/bin/sh | |
echo Install all AppStore Apps at first! | |
# no solution to automate AppStore installs | |
read -p "Press any key to continue... " -n1 -s | |
echo '\n' | |
echo Install and Set San Francisco as System Font | |
ruby -e "$(curl -fsSL https://raw.github.com/wellsriley/YosemiteSanFranciscoFont/master/install)" | |
echo Install Homebrew, Postgres, wget and cask | |
ruby -e "$(curl -fsSL https://raw.github.com/Homebrew/homebrew/go/install)" |
import javax.crypto.Cipher; | |
class Test { | |
public static void main(String[] args) { | |
try { | |
System.out.println("Hello World!"); | |
int maxKeyLen = Cipher.getMaxAllowedKeyLength("AES"); | |
System.out.println(maxKeyLen); | |
} catch (Exception e){ | |
System.out.println("Sad world :("); |
/* | |
* I add this to html files generated with pandoc. | |
*/ | |
html { | |
font-size: 100%; | |
overflow-y: scroll; | |
-webkit-text-size-adjust: 100%; | |
-ms-text-size-adjust: 100%; | |
} |
package main | |
import ( | |
"database/sql" | |
"errors" | |
"fmt" | |
_ "github.com/bmizerany/pq" | |
"os" | |
"regexp" | |
"strings" |
# FILE: Classifying Breast Cancer as Benign or Malignant | |
# AUTHOR: Timothy P. Jurka | |
library(RTextTools); | |
# GET THE BREAST CANCER DATA FROM http://archive.ics.uci.edu/ml/machine-learning-databases/breast-cancer-wisconsin/wdbc.names | |
data <- read.csv("http://archive.ics.uci.edu/ml/machine-learning-databases/breast-cancer-wisconsin/breast-cancer-wisconsin.data",header=FALSE) | |
data <- data[-1] | |
# ADD TEXTUAL DESCRIPTORS FOR EACH MASS CHARACTERISTIC FOR THE DOCUMENT-TERM MATRIX |
package gocard | |
import ( | |
"fmt" | |
"io" | |
"crypto/md5" | |
"crypto/sha1" | |
"crypto/sha256" | |
"crypto/sha512" | |
) |
L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns
L2 cache reference ........................... 7 ns
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns
Compress 1K bytes with Zippy ............. 3,000 ns = 3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns = 20 µs
SSD random read ........................ 150,000 ns = 150 µs
Read 1 MB sequentially from memory ..... 250,000 ns = 250 µs