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#dependencies http://code.google.com/p/python-twitter/ |
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# info |
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# http://stackoverflow.com/questions/4206882/named-entity-recognition-with-preset-list-of-names-for-python-php/4207128#4207128 |
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# http://alias-i.com/lingpipe/demos/tutorial/ne/read-me.html approximate dist |
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# http://streamhacker.com/2008/12/29/how-to-train-a-nltk-chunker/ more training |
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# http://www.postgresql.org/docs/9.1/static/pgtrgm.html |
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# data sources |
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# http://twitter.com/#!/ACTEmergencyInf instant site wide |
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# http://twitter.com/#!/ACTPol_Traffic |
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# http://esa.act.gov.au/feeds/currentincidents.xml |
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# source: https://gist.github.com/322906/90dea659c04570757cccf0ce1e6d26c9d06f9283 |
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import nltk |
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import twitter |
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import psycopg2 |
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def insert_service_alert_sitewide(heading, message, url): |
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def insert_service_alert_for_street(streets, heading, message, url): |
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conn_string = "host='localhost' dbname='energymapper' user='postgres' password='snmc'" |
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# print the connection string we will use to connect |
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print "Connecting to database\n ->%s" % (conn_string) |
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try: |
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# get a connection, if a connect cannot be made an exception will be raised here |
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conn = psycopg2.connect(conn_string) |
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# conn.cursor will return a cursor object, you can use this cursor to perform queries |
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cursor = conn.cursor() |
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# execute our Query |
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cursor.execute("select max(value), extract(dow from max(time)) as dow, \ |
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extract(year from max(time))::text || lpad(extract(month from max(time))::text,2,'0') \ |
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|| lpad(extract(month from max(time))::text,2,'0') as yearmonthweek, to_char(max(time),'J') \ |
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from environmentdata_values where \"dataSourceID\"='NSWAEMODemand' \ |
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group by extract(dow from time), extract(year from time), extract(week from time) \ |
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order by extract(year from time), extract(week from time), extract(dow from time)") |
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# retrieve the records from the database |
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records = cursor.fetchall() |
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for record in records: |
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ys.append(record[0]) |
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# >>> cur.execute("INSERT INTO test (num, data) VALUES (%s, %s)", (42, 'bar')) |
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#>>> cur.statusmessage |
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#'INSERT 0 1' |
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except: |
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# Get the most recent exception |
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exceptionType, exceptionValue, exceptionTraceback = sys.exc_info() |
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# Exit the script and print an error telling what happened. |
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sys.exit("Database connection failed!\n ->%s" % (exceptionValue)) |
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def get_tweets(user): |
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tapi = twitter.Api() |
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return tapi.GetUserTimeline(user) |
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def extract_entity_names(t): |
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entity_names = [] |
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if hasattr(t, 'node') and t.node: |
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if t.node == 'NE': |
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entity_names.append(' '.join([child[0] for child in t])) |
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else: |
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for child in t: |
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entity_names.extend(extract_entity_names(child)) |
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return entity_names |
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def extract_names(sample): |
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sentences = nltk.sent_tokenize(sample) |
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tokenized_sentences = [nltk.word_tokenize(sentence) for sentence in sentences] |
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tagged_sentences = [nltk.pos_tag(sentence) for sentence in tokenized_sentences] |
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chunked_sentences = nltk.batch_ne_chunk(tagged_sentences, binary=True) |
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# chunked/tagged may be enough to just find and match the nouns |
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entity_names = [] |
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for tree in chunked_sentences: |
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# Print results per sentence |
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# print extract_entity_names(tree) |
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entity_names.extend(extract_entity_names(tree)) |
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# Print all entity names |
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#print entity_names |
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# Print unique entity names |
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print set(entity_names) |
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