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#! /usr/bin/env python

import secure
import pexpect

# the file containing the list of servers to log into
input_file = "script_list"

# The login creds
user = secure.USER 

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import frontmatter
from frontmatter import Post as FMPost

def frontmatter_to_file(file, data={}, content=""):

    p = FMPost(content=content, **data)
    with open(file, "w") as f:
        f.write(frontmatter.dumps(p))

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{
    "python.pythonPath": "/Users/Mardix/.virtualenvs/${workspaceRootFolderName}/bin/python"
}

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# Allow to create pages for testing purposes

from datetime import datetime
import random
import string
import shutil
import os


def generateWord():

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# coding=UTF-8
from __future__ import division
import re

# This is a naive text summarization algorithm
# Created by Shlomi Babluki
# April, 2013


class SummaryTool(object):

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// _responsive_mixin.scss

$font : "Lato", sans-serif;

// Text Colors
$text-color: #111;
$text-light-color: #B9B9B9;
$text-lighter-color: #fff;
$text-dark-color: #1E1E1E;
$text-darker-color: #111;

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

# You need PIL <http://www.pythonware.com/products/pil/> to run this script
# Download unifont.ttf from <http://unifoundry.com/unifont.html> (or use
# any TTF you have)
# Copyright 2011 Álvaro Justen [alvarojusten at gmail dot com]
# License: GPL <http://www.gnu.org/copyleft/gpl.html>

from image_utils import ImageText

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#############################################################################
# current prompt
#############################################################################
# \d – Current date
# \t – Current time
# \h – Host name
# \# – Command number
# \u – User name
# \W – Current working directory (ie: Desktop/)
# \w – Current working directory, full path (ie: /Users/Admin/Desktop)

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While I was working on a personal project, I decided to compare foreach vs array_map to iterate over a large set of items. 

So to support my decision, I ran a benchmark on both foreach and array_map. 

With a simple array of 1,000,000 objects, I iterate over them with foreach and array_map. And surprisingly, foreach ran in 0.24sec average, while array_map took over 3.30sec. 

Also array_map ran out of memory, I had to do an ini_set("memory_limit","512M"); to at least get some results.

My system:
Macbook

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#!/usr/bin/env python

# sample usage: checksites.py eriwen.com nixtutor.com yoursite.org

import pickle, os, sys, logging
from httplib import HTTPConnection, socket
from smtplib import SMTP

def email_alert(message, status):
    fromaddr = 'you@gmail.com'