markwatson

<?php if ( ! defined('BASEPATH')) exit('No direct script access allowed'); 
ob_start();
/**
* Template Library
*
* @package Template
* @category Libraries
* @author Mark Watson
* @link http://markedup.org
*

markwatson

<?php

// error logging function that saves arrays, objects - anything.
// easier to type then always typing "error_log(print_r($var,1));
function e($var, $mess=null)
{
  error_log($mess.': '.print_r($var,1));
}

markwatson

<?php
/**
* The global model! All hail potentate MY_Controller!
* It provides some great default queries...
*/
class MY_Model extends Model
{
	var $default_table;
	
	function get_all()

markwatson

<?php
/**
* Intelligent News Parser Library
*
* @package Parse_news
* @category Libraries
* @author Mark Watson
* @link http://markwatson.us
*
* A simple library that parses the html from news articles to pull out metadata. 

markwatson

The first is to use the object oriented way:
$config = array(
           'indent'         => true,
           'output-xml'   => true,
           'wrap'           => 200);

// Tidy
$tidy = new tidy;
$tidy->parseString($xml, $config, 'utf8');
$tidy->cleanRepair();

markwatson

#include <stdio.h>

double my_ceil(double x) {
    double y = (double) ((long long) x);
    if (x - y == 0) {
        return x;
    } else {
        if (x > 0) {
            return y + 1;
        } else {

markwatson

class AdjacencyMatrix[T: Manifest](size: Int) {
  // initialize it
  // (It's in column vector format)
  val matrix = Array.ofDim[T](size, size)

  // helper functions
  // takes a list of 3-tuples in the form: (from, to, weight)
  def setConnections(connections: List[(Int, Int, T)]) = {
    for (x <- connections) {
      // make matrix[to][from] = weight

markwatson

import mechanize
from BeautifulSoup import BeautifulSoup

class Dmoz(object):
    def __init__(self):
        self.br = mechanize.Browser()

    def get_page_urls(self, term):
        result = self.br.open("http://www.dmoz.org/search?q="+term)
        result_html = result.read()

markwatson

def super_split(string, delim):
    segment = ''
    for c in string:
        if c in delim:
            yield segment
            segment = ''
        else:
            segment += c
    yield segment

markwatson

# Tested on Windows 7 and Python 2.7

# the code
def lagrangian_interpolate(samples):
    """
    Takes some samples as a list of tuples and returns a function that's
    a lagrangian interpolation of all the samples.
    """
    X = 0 # the tuple index of the X variable in the samples
    Y = 1 # the tuple index of the Y variable in the samples