init_day = '2013-09-01 17:00:00' final_day = '2014-11-30 16:59:59' table_name = instr_name + '_LAST' compressed_table_name = table_name + '_COMPRESSED' start_stamp = pd.Timestamp(init_day).tz_localize('US/Central') start_stamp_utc = start_stamp.tz_convert('utc') final_stamp = pd.Timestamp(final_day).tz_localize('US/Central') final_stamp_utc = final_stamp.tz_convert('utc') futures_db = FuturesDatabase() futures_db.drop_table_if_exist(compressed_table_name) futures_db.create_historical_table(compressed_table_name) df_compressed = DataFrame(columns=['Date', 'Last', 'Volume']) while start_stamp_utc < final_stamp_utc: start_date = timestamp_to_SQLstring(start_stamp_utc) # get end of day timestamp end_stamp_utc = start_stamp_utc + Day() - 45*Minute() end_date = timestamp_to_SQLstring(end_stamp_utc) df = futures_db.fetch_between_dates(table_name=table_name, start_date=start_date, end_date=end_date,
import pandas as pd from util.futuresdatabase import FuturesDatabase instrument_list = ['GC', 'CL', 'ZB'] futures_db = FuturesDatabase() for instrument in instrument_list: table_name = instrument + '_LAST' futures_db.drop_table_if_exist(table_name) futures_db.create_historical_table(table_name) rootPath = "/home/aouyang1/NinjaTrader/TickData/" + instrument folders = os.listdir(rootPath) fnames = os.listdir(rootPath) for fileNames in fnames: print fileNames df = pd.read_csv(rootPath + '/' + fileNames, delimiter=";", names=['Date', 'Last', 'Volume'], parse_dates=[0], date_parser=lambda x: datetime.datetime.strptime(x, '%Y%m%d %H%M%S')) futures_db.upload_dataframe_to_table(df, table_name) futures_db.create_table_index(table_name, "Date") futures_db.close_database_connection()
init_day = '2013-09-01 17:00:00' final_day = '2014-11-30 16:59:59' table_name = instr_name + '_LAST' compressed_table_name = table_name + '_COMPRESSED' start_stamp = pd.Timestamp(init_day).tz_localize('US/Central') start_stamp_utc = start_stamp.tz_convert('utc') final_stamp = pd.Timestamp(final_day).tz_localize('US/Central') final_stamp_utc = final_stamp.tz_convert('utc') futures_db = FuturesDatabase() futures_db.drop_table_if_exist(compressed_table_name) futures_db.create_historical_table(compressed_table_name) df_compressed = DataFrame(columns=['Date', 'Last', 'Volume']) while start_stamp_utc < final_stamp_utc: start_date = timestamp_to_SQLstring(start_stamp_utc) # get end of day timestamp end_stamp_utc = start_stamp_utc + Day() - 45 * Minute() end_date = timestamp_to_SQLstring(end_stamp_utc) df = futures_db.fetch_between_dates(table_name=table_name, start_date=start_date, end_date=end_date,
import datetime import pandas as pd from util.futuresdatabase import FuturesDatabase instrument_list = ['GC', 'CL', 'ZB'] futures_db = FuturesDatabase() for instrument in instrument_list: table_name = instrument + '_LAST' futures_db.drop_table_if_exist(table_name) futures_db.create_historical_table(table_name) rootPath = "/home/aouyang1/NinjaTrader/TickData/" + instrument folders = os.listdir(rootPath) fnames = os.listdir(rootPath) for fileNames in fnames: print fileNames df = pd.read_csv(rootPath + '/' + fileNames, delimiter=";", names=['Date', 'Last', 'Volume'], parse_dates=[0], date_parser=lambda x: datetime.datetime.strptime( x, '%Y%m%d %H%M%S')) futures_db.upload_dataframe_to_table(df, table_name)