assert len(sys.argv) == 2
if sys.argv[1] == 'twitter':
database = 'feeds.db'
script = 'twitterBuild.sql'
elif sys.argv[1] == 'stocks':
database = 'stocks.db'
script = 'stocksBuild.sql'
else:
raise NotImplementedError()
# Open or create the desired sqlite database
db = QuantSQLite(database)
# Test everything is alright
print db.execute('select sqlite_version()')
# Execute sql script
db.queryFromScript(script)
db.close()
if sys.argv[1] == 'stocks':
# getQuotes() method will fetch data that is not available in database and then store it
timestamp = pd.date_range(pd.datetime(2005, 1, 1, tzinfo=pytz.utc),
pd.datetime(2012, 11, 30, tzinfo=pytz.utc),
freq=pd.datetools.BDay())
tickers = ['starbucks', 'google', 'apple', 'altair']
fill_quotes(tickers, timestamp)
elif sys.argv[1] == 'twitter':
#TODO Use script in ppQuantrade/playground/nlp/twit.py
raise NotImplementedError()
assert len(sys.argv) == 2
if sys.argv[1] == 'twitter':
database = 'feeds.db'
script = 'twitterBuild.sql'
elif sys.argv[1] == 'stocks':
database = 'stocks.db'
script = 'stocksBuild.sql'
else:
raise NotImplementedError()
# Open or create the desired sqlite database
db = QuantSQLite(database)
# Test everything is alright
print db.execute('select sqlite_version()')
# Execute sql script
db.queryFromScript(script)
db.close()
if sys.argv[1] == 'stocks':
# getQuotes() method will fetch data that is not available in database and then store it
timestamp = pd.date_range(pd.datetime(2005, 1, 1, tzinfo=pytz.utc),
pd.datetime(2012, 11, 30, tzinfo=pytz.utc),
freq=pd.datetools.BDay())
tickers = ['starbucks', 'google', 'apple', 'altair']
fill_quotes(tickers, timestamp)
elif sys.argv[1] == 'twitter':
#TODO Use script in ppQuantrade/playground/nlp/twit.py
raise NotImplementedError()
