text: '''
  (c) 2011, 2012 Georgia Tech Research Corporation
  This source code is released under the New BSD license.  Please see
  http://wiki.quantsoftware.org/index.php?title=QSTK_License
  for license details.
  
  Created on January, 24, 2013
  
  @author: Sourabh Bajaj
  @contact: sourabhbajaj@gatech.edu
  @summary: An example to show how dataAccess works.
  '''
  
  # QSTK Imports
  import QSTK.qstkutil.qsdateutil as du
  import QSTK.qstkutil.tsutil as tsu
  import QSTK.qstkutil.DataAccess as da
  
  # Third Party Imports
  import datetime as dt
  import matplotlib.pyplot as plt
  import pandas as pd
  
  
  def main():
      ''' Main Function'''
      # Creating an object of DataAccess Class
      c_dataobj = da.DataAccess('Yahoo')
  
      # Getting a list of symbols from Lists
      # Lists : S&P5002012, S&P5002008, Index
      ls_symbols = c_dataobj.get_symbols_from_list('sp5002012')
      print "Symbols from the list : ", ls_symbols
  
      # All symbols possible
      ls_all_syms = c_dataobj.get_all_symbols()
      print "All symbols : ", ls_all_syms
  
      ls_syms_toread = ['AAPL', 'GOOG']
  
      # List of TimeStamps to read
      ldt_timestamps = []
      ldt_timestamps.append(dt.datetime(2010, 10, 14, 16))
      ldt_timestamps.append(dt.datetime(2010, 10, 15, 16))
      ldt_timestamps.append(dt.datetime(2010, 11, 21, 16))
      ldt_timestamps.append(dt.datetime(2010, 11, 22, 16))
      ldt_timestamps.append(dt.datetime(2010, 11, 23, 16))
      ldt_timestamps.append(dt.datetime(2010, 11, 24, 16))
      ldt_timestamps.append(dt.datetime(2010, 11, 25, 16))
      ldt_timestamps.append(dt.datetime(2010, 11, 26, 16))
      ldt_timestamps.append(dt.datetime(2010, 11, 27, 10))
      ldt_timestamps.append(dt.datetime(2010, 11, 27, 16))
      ldt_timestamps.append(dt.datetime(2020, 11, 27, 16))
      ldt_timestamps.append(dt.datetime(2020, 11, 27, 18))
  
      # Reading the data
      # By default it'll read data from the default data provided,
      # But a path can be provided using either an environment variable or
      # as a prarameter.
      df_close = c_dataobj.get_data(ldt_timestamps, ls_syms_toread, "close")
      print df_close
  
  
  if __name__ == '__main__':
      main()
  