mreid

The INSTALL instructions that come with Vowpal Wabbit appear not to work on Mac OS X Lion. Here's what I did to get it to compile. You will need the developer tools that come with the XCode installation.

The only dependency VW has is the boost C++ library. So first, download and install Boost

To install Boost, do the following:

$ cp ~/Downloads/boost_1_48_0.tar.bz2 ./

scotttam

import socket, ssl, json, struct
import binascii

# device token returned when the iPhone application
# registers to receive alerts
deviceToken = '39cac56f 986a0e66 3c4fd4f4 68df5598 024d2ca3 8b9f307c 741c180e 9fc30c62'

thePayLoad = {
     'aps': {
          'alert':'Oh no! Server\'s Down!',

ehazlett

[program:mongodb]
command=/opt/mongodb/bin/mongod --dbpath /storage/mongodb_data --rest
directory=/opt/mongodb
user=root
autostart=false

fermion

import socket, ssl, json, struct
import binascii

# device token returned when the iPhone application
# registers to receive alerts
deviceToken = '39cac56f 986a0e66 3c4fd4f4 68df5598 024d2ca3 8b9f307c 741c180e 9fc30c62'

thePayLoad = {
     'aps': {
          'alert':'Oh no! Server\'s Down!',

py_example.py

#!/usr/bin/env python

class BidAskParseError(Exception): pass

import datetime
from twisted.internet import reactor
from twisted.protocols.basic import LineReceiver
from twisted.internet.protocol import ClientFactory

class ExampleClient(LineReceiver):

jpoehls

var cluster = require('cluster');

if (cluster.isWorker) {

  console.log('Worker ' + process.pid + ' has started.');

  // Send message to master process.
  process.send({msgFromWorker: 'This is from worker ' + process.pid + '.'})

  // Receive messages from the master process.

jholster

import tornado.web
import tornado.httpserver
import tornado.ioloop

class MainHandler(tornado.web.RequestHandler):
	def get(self):
		self.write("Greetings from the instance %s!" % tornado.process.task_id())

app = tornado.web.Application([
	(r"/", MainHandler),

fonnesbeck

joferkington

import numpy as np

def process_file(filename, num_cols, delimiter='\t'):
    def items(infile):
        for line in infile:
            for item in line.rstrip().split(delimiter):
                yield float(item)

    with open(filename, 'r') as infile:
        data = np.fromiter(items(infile))

alaiacano

my.reduce <- function(df.in, f1, f2){
  x <- ddply(df.in, .(f1, f2), summarize,
             value=sum(value)
             )
  x
}

df <- data.frame(
  state=rep(c("MA", "NY", "CA"), each=10),
  year=rep((2001:2010), 3),