scripting

{
    "created_at": "Fri Sep 19 12:20:23 +0000 2014",
    "id": 512939257850511360,
    "id_str": "512939257850511360",
    "text": "\"I never used the Blackberry again.\" https://t.co/CYsbbBDtOh",
    "source": "<a href=\"http://radio3.io/\" rel=\"nofollow\">radio3.io</a>",
    "truncated": false,
    "in_reply_to_status_id": null,
    "in_reply_to_status_id_str": null,
    "in_reply_to_user_id": null,

antiface

{
    "created_at": "Fri Sep 19 12:20:23 +0000 2014",
    "id": 512939257850511360,
    "id_str": "512939257850511360",
    "text": "\"I never used the Blackberry again.\" https://t.co/CYsbbBDtOh",
    "source": "<a href=\"http://radio3.io/\" rel=\"nofollow\">radio3.io</a>",
    "truncated": false,
    "in_reply_to_status_id": null,
    "in_reply_to_status_id_str": null,
    "in_reply_to_user_id": null,

antiface

class Pet(object):
    
    def __init__(self, name, species):
        self.name = name
        self.species = species

    def getName(self):
        return self.name

    def getSpecies(self):

jcsalterego

#!/usr/bin/env python
#
# Generates non-unique word list from Twitter Search meeting certain
# criteria (as set in the configuration, below).
#
# EXAMPLE (word wrap inserted for ease of reading):
#
# $ python hashtag_wordle.py 
# Fetching http://search.twitter.com/search.json?q=%23spinuzzi-project&rpp=30&page=1...
# Fetching http://search.twitter.com/search.json?q=%23spinuzzi-project&rpp=30&page=2...

taboularasa

http://search.twitter.com/search.json?q=%40human_bot


{
    "results": [{
        "text": "@human_bot Are you feeling okay? Sounds like you've been smoking some crack with the way you've been talking lately.",
        "to_user_id": 5740619,
        "to_user": "human_bot",
        "from_user": "taboularasa",
        "id": 1306533155,

storborg

"""
walk through related tags on twitter.

start it with something like python twitterwalk.py sxsw
"""

import sys, re
from twitter import Twitter

if len(sys.argv) > 1:

criccomini

# print a user's tweets
import simplejson
import re
import urllib2
import string

me = urllib2.urlopen('http://twitter.com/statuses/user_timeline/peteskomoroch.json?count=200')

for tweet in simplejson.loads(me.read()):
	print tweet['text'].encode('utf-8')

criccomini

# poll a search term every 60 seconds and print tweets out
import time
import simplejson
import re
import urllib2
import urllib

last_id = False

while True:

code

import gaerun

from google.appengine.ext import db 
from google.appengine.api import urlfetch
from google.appengine.api import memcache
import simplejson
import logging

class User(db.Model):
    name = db.StringProperty()

NaiveBayesClassifier.py

import nltk
import random

class Categorizer(object):
    def __init__(self, categories):
        self.categories = categories

    def prep_seed(self, content):
        """Convert seed content into nltk.Text"""
        raw = nltk.clean_html(content)