old_contents: import sys
  import os
  from threading import Thread
  from flask import Flask
  import pandas as pd
  sys.path.insert(0, "../financialScraper")
  from financialScraper import getqf
  #from sqlalchemy import create_engine
  
  app = Flask(__name__)
  # app.config['DATABASE'] = os.environ.get(
  # 	'HEROKU_POSTGRESQL_GOLD_URL', ''
  # 	)
  # engine = create_engine(app.config['DATABASE'])
  
  display_val = u"Loading data..."
  
  # def load_data():
  # 	dfdict = getqf.scraper()
  # 	df = dfdict['nsdqct.csv']
  # 	df.to_sql(name='entries', con = engine, if_exists = 'replace')
  # 	output = pd.read_sql_query('SELECT * FROM entries', engine)
  # 	mean = output[[2]].mean()
  # 	display_val = u"The mean is :" + str(mean)
  
  # thread1 = Thread(target = load_data)
  # thread1.start()
  
  @app.route('/')
  def hello():
  	return u'hello'
  	
  
  if __name__ == "__main__":
      app.run(debug=True)
  
new_contents: # import sys
  # import os
  # from threading import Thread
  from flask import Flask
  # import pandas as pd
  # sys.path.insert(0, "../financialScraper")
  # from financialScraper import getqf
  #from sqlalchemy import create_engine
  
  app = Flask(__name__)
  # app.config['DATABASE'] = os.environ.get(
  # 	'HEROKU_POSTGRESQL_GOLD_URL', ''
  # 	)
  # engine = create_engine(app.config['DATABASE'])
  
  display_val = u"Loading data..."
  
  # def load_data():
  # 	dfdict = getqf.scraper()
  # 	df = dfdict['nsdqct.csv']
  # 	df.to_sql(name='entries', con = engine, if_exists = 'replace')
  # 	output = pd.read_sql_query('SELECT * FROM entries', engine)
  # 	mean = output[[2]].mean()
  # 	display_val = u"The mean is :" + str(mean)
  
  # thread1 = Thread(target = load_data)
  # thread1.start()
  
  @app.route('/')
  def hello():
  	return u'hello'
  	
  
  if __name__ == "__main__":
      app.run(debug=True)
  
subject: Comment out imports