processed_list = [ [ 'wage_lag_15m', 'mlag(wage_us_yoy,15)' ], [ 'zillow_median_sale_price_15m', 'mlag(zillow_median_sale_price_yoy,15)' ], ] df = DataFrameClient('localhost',8086,'root','root') if({'name':'Econ'} not in df.get_list_database()): df.create_database('Econ') df.switch_database('Econ') #add all items in interested list start = timeit.default_timer() for item in interest_list: if item[0] in df.get_list_series(): df.delete_series(item[0]) results = influx_Fred.interpret(item[1]) results = results.replace(to_replace='NaN',value='.') results = DataFrame({'value':results['value']}) df.write_points({item[0]:results}) print item print 'total time in seconds: %.2f' % (timeit.default_timer() - start) #add all items in processed list start = timeit.default_timer() influx_Econ = InfluxDB(db_name='Econ') for item in processed_list: if item[0] in df.get_list_series(): df.delete_series(item[0]) results = influx_Econ.interpret(item[1]) results = results.replace(to_replace='NaN',value='.')
''' Created on Jul 8, 2015 @author: shaunz ''' from QuandlAPI import QuandlAPI from influxdb.influxdb08 import DataFrameClient from QuandlTicker import Quandl_ticker_list import timeit quandl = QuandlAPI() df = DataFrameClient('localhost', 8086, 'root', 'root') if({'name':'Quandl'} not in df.get_list_database()): df.create_database('Quandl') df.switch_database('Quandl') for series in df.get_list_series(): df.delete_series(series) start = timeit.default_timer() for item in Quandl_ticker_list: results = quandl.get_series(item[1],item[2],item[3]) results = results.replace(to_replace='NaN',value='.') print item df.write_points({item[0]:results}) print 'total time in seconds: %.2f' % (timeit.default_timer() - start)