lrvick

#include <Wire.h>
#include <SPI.h>
#include <Ethernet.h>
   
byte mac[] = { 0xDE, 0xAD, 0xBE, 0xEF, 0xCA, 0xFE };
 
EthernetServer server(80);

const int lockPin = 2;
const int ledPin = 13;

lrvick

#!/bin/bash

URL=$1
LOG_FILE=$2
WORKER_STEPS=( 10 100 200 500 1000 1500 )
DELAY=10
TEST_LENGTH=60s

for WORKERS in "${WORKER_STEPS[@]}"; do

lrvick

import httplib,pycurl,json
from django.conf import settings
from tasks import ProcessTweet

QUERY="android"

class Twitter():
    default_retry_delay = 5
    def run(self,query):
        self.buffer = ""

lrvick

import urllib2,httplib,re

def url_title(url,**kwargs):
    title = None
    request = urllib2.Request(url)
    try:
        response = urllib2.urlopen(request)
        data = response.read()
    except urllib2.HTTPError:
        data = None

lrvick

import urllib2, json, base64, sys, termios, tty, os 

USER = "your_twitter_user"
PASS = "your_twitter_pass"

neg_filename = "negative.txt"
pos_filename = "postive.txt"

queries = ['awesome','beautiful','shit','fuck','android','iphone','blackberry','windows','linux','apple','google']

lrvick

USER = "your_twitter_user"
PASS = "your_twitter_pass"

if "your_twitter" in USER+PASS:
    print "You didn't set your twitter username and password in the script!"
    USER = raw_input("Username>")
    PASS = raw_input("Password>")

import urllib2, json, base64, sys, os 

lrvick

import time,sys

total_loops = 500;

complete_loops = 0;
 
while (complete_loops < total_loops): 
    percent = int(complete_loops*100/total_loops)
    time.sleep(1)
    complete_loops +=1

lrvick

#!/bin/python

import random

def rgb_to_int(r,g,b):
    i = str()
    for c in r,g,b:
        for d in str("%03d" % (c,)):
            i += '%s%s%s' % (d,d,d)
    return i

lrvick

#The goal is to emulate the following bash line properly in python:
#wget -O - "https://github.com/downloads/Tawlk/synt/sample_data.bz2" | bzcat | sqlite3 sample_data.db

import bz2                                                                       
import sqlite3                                                                   
import time                                                                      
import urllib2                                                                   
import os                                                                        
from cStringIO import StringIO                                                   

lrvick

from nltk.probability import DictionaryProbDist
from nltk import NaiveBayesClassifier

train_samples = {
    'I hate you and you are a bad person': 'neg',
    'I love you and you are a good person': 'pos',
    'I fail at everything and I want to kill people' : 'neg',
    'I win at everything and I want to love people' : 'pos',
    'sad are things are heppening. fml' : 'neg',
    'good are things are heppening. gbu' : 'pos',