Rename servicealerts to local terminology "Real Time Passenger Information System"
[busui.git] / rtpis / importer.py
blob:a/rtpis/importer.py -> blob:b/rtpis/importer.py
  # info
  # http://stackoverflow.com/questions/4206882/named-entity-recognition-with-preset-list-of-names-for-python-php/4207128#4207128
  # http://alias-i.com/lingpipe/demos/tutorial/ne/read-me.html approximate dist
  # http://streamhacker.com/2008/12/29/how-to-train-a-nltk-chunker/ more training
  # http://www.postgresql.org/docs/9.1/static/pgtrgm.html
   
  # data sources
  # http://twitter.com/#!/ACTEmergencyInf instant site wide
  # http://twitter.com/#!/ACTPol_Traffic
  # http://esa.act.gov.au/feeds/currentincidents.xml
   
  # source: https://gist.github.com/322906/90dea659c04570757cccf0ce1e6d26c9d06f9283
  # to install python -m nltk.downloader punkt
  import nltk
  import tweepy
  import psycopg2
  import pickle
   
  from iniparse import INIConfig
   
  def insert_service_alert_sitewide(heading, message, url):
  print "NaN"
   
  def insert_service_alert_for_street(streets, heading, message, url):
  conn_string = "host='localhost' dbname='energymapper' user='postgres' password='snmc'"
  # print the connection string we will use to connect
  print "Connecting to database\n ->%s" % (conn_string)
  try:
  # get a connection, if a connect cannot be made an exception will be raised here
  conn = psycopg2.connect(conn_string)
   
  # conn.cursor will return a cursor object, you can use this cursor to perform queries
  cursor = conn.cursor()
   
  # execute our Query
  cursor.execute("")
   
  # retrieve the records from the database
  records = cursor.fetchall()
   
  for record in records:
  ys.append(record[0])
  # >>> cur.execute("INSERT INTO test (num, data) VALUES (%s, %s)", (42, 'bar'))
  #>>> cur.statusmessage
  #'INSERT 0 1'
  except:
  # Get the most recent exception
  exceptionType, exceptionValue, exceptionTraceback = sys.exc_info()
  # Exit the script and print an error telling what happened.
  sys.exit("Database connection failed!\n ->%s" % (exceptionValue))
   
   
  def extract_entity_names(t):
  entity_names = []
   
  if hasattr(t, 'node') and t.node:
  if t.node == 'NE':
  entity_names.append(' '.join([child[0] for child in t]))
  else:
  for child in t:
  entity_names.extend(extract_entity_names(child))
   
  return entity_names
   
  def extract_names(sample):
  sentences = nltk.sent_tokenize(sample)
  tokenized_sentences = [nltk.word_tokenize(sentence) for sentence in sentences]
  tagged_sentences = [nltk.pos_tag(sentence) for sentence in tokenized_sentences]
  chunked_sentences = nltk.batch_ne_chunk(tagged_sentences, binary=True)
  # chunked/tagged may be enough to just find and match the nouns
   
  entity_names = []
  for tree in chunked_sentences:
  # Print results per sentence
  # print extract_entity_names(tree)
   
  entity_names.extend(extract_entity_names(tree))
   
  # Print all entity names
  #print entity_names
   
  # Print unique entity names
  print set(entity_names)
   
  cfg = INIConfig(open('/tmp/aws.ini'))
   
  auth = tweepy.OAuthHandler(cfg.api_keys.twitter_consumer_key, cfg.api_keys.twitter_consumer_secret)
  auth.set_access_token(cfg.api_keys.twitter_access_token, cfg.api_keys.twitter_access_token_secret)
   
  #api = tweepy.API(auth)
  api = tweepy.API()
  # If the authentication was successful, you should
  # see the name of the account print out
  #print api.me().name
  # https://github.com/tweepy/tweepy/blob/master/tweepy/api.py
  for status in api.user_timeline(screen_name="ACTPol_Traffic",exclude_replies='true'):
  print status.text
  print status.created_at
  print extract_names(status.text)
  # print api.update_status(status="test")
   
  last_tweet_ids = { "lion": "111", "kitty": "2222" }
  pickle.dump( last_tweet_ids, open( "save.p", "wb" ) )
  last_tweet_ids = pickle.load( open( "save.p", "rb" ) )