def get_data_ib(instrument,
start,
resolution="1 min",
blotter=None,
output_path=None):
"""
Downloads historical data from Interactive Brokers
:Parameters:
instrument : mixed
IB contract tuple / string (same as that given to strategy)
start : str
Backtest start date (YYYY-MM-DD [HH:MM:SS[.MS])
:Optional:
resolution : str
1 sec, 5 secs, 15 secs, 30 secs, 1 min (default), 2 mins, 3 mins, 5 mins, 15 mins, 30 mins, 1 hour, 1 day
blotter : str
Store MySQL server used by this Blotter (default is "auto detect")
output_path : str
Path to the location where the resulting CSV should be saved (default: ``None``)
:Returns:
data : pd.DataFrame
Pandas DataFrame in a QTPyLib-compatible format and timezone
"""
global _ib_history_downloaded
# load blotter settings
blotter_args = load_blotter_args(blotter,
logger=logging.getLogger(__name__))
# create contract string (no need for connection)
ibConn = ezIBpy()
ibConn.ibCallback = ibCallback
if not ibConn.connected:
ibConn.connect(clientId=0,
port=int(blotter_args['ibport']),
host=str(blotter_args['ibserver']))
# generate a valid ib tuple
instrument = tools.create_ib_tuple(instrument)
contract_string = ibConn.contractString(instrument)
contract = ibConn.createContract(instrument)
ibConn.requestHistoricalData(contracts=[contract],
data="TRADES",
resolution=resolution,
lookback=tools.ib_duration_str(start),
rth=False)
while not _ib_history_downloaded:
time.sleep(.1)
ibConn.disconnect()
data = ibConn.historicalData[contract_string]
data['datetime'] = data.index
return prepare_data(instrument, data, output_path=output_path)
def get_data_ib(instrument, start, resolution="1 min", blotter=None, output_path=None):
"""
Downloads historical data from Interactive Brokers
:Parameters:
instrument : mixed
IB contract tuple / string (same as that given to strategy)
start : str
Backtest start date (YYYY-MM-DD [HH:MM:SS[.MS])
:Optional:
resolution : str
1 sec, 5 secs, 15 secs, 30 secs, 1 min (default), 2 mins, 3 mins, 5 mins, 15 mins, 30 mins, 1 hour, 1 day
blotter : str
Store MySQL server used by this Blotter (default is "auto detect")
output_path : str
Path to the location where the resulting CSV should be saved (default: ``None``)
:Returns:
data : pd.DataFrame
Pandas DataFrame in a QTPyLib-compatible format and timezone
"""
global _ib_history_downloaded
# load blotter settings
blotter_args = load_blotter_args(
blotter, logger=logging.getLogger(__name__))
# create contract string (no need for connection)
ibConn = ezIBpy()
ibConn.ibCallback = ibCallback
if not ibConn.connected:
ibConn.connect(clientId=0,
port=int(blotter_args['ibport']), host=str(blotter_args['ibserver']))
# generate a valid ib tuple
instrument = tools.create_ib_tuple(instrument)
contract_string = ibConn.contractString(instrument)
contract = ibConn.createContract(instrument)
ibConn.requestHistoricalData(contracts=[contract],
data="TRADES", resolution=resolution, lookback=tools.ib_duration_str(start), rth=False)
while not _ib_history_downloaded:
time.sleep(.1)
ibConn.disconnect()
data = ibConn.historicalData[contract_string]
data['datetime'] = data.index
return prepare_data(instrument, data, output_path=output_path)