def construct_vendor_md_request(self, md_request):
"""Creates a MarketDataRequest with the vendor tickers
Parameters
----------
md_request : MarketDataRequest
contains all the various parameters detailing time series start and
finish, tickers etc
Returns
-------
MarketDataRequest
"""
symbols_vendor = self.translate_to_vendor_ticker(md_request)
fields_vendor = self.translate_to_vendor_field(md_request)
md_request_vendor = MarketDataRequest(
md_request=md_request)
md_request_vendor.tickers = symbols_vendor
md_request_vendor.fields = fields_vendor
md_request_vendor.old_tickers = md_request.tickers
return md_request_vendor
def load_ticker(self, md_request):
"""Retrieves market data from external data source (in this case
Bloomberg)
Parameters
----------
md_request : MarketDataRequest
contains all the various parameters detailing time series start
and finish, tickers etc
Returns
-------
DataFrame
"""
constants = DataConstants()
md_request = MarketDataRequest(md_request=md_request)
md_request_vendor = self.construct_vendor_md_request(md_request)
data_frame = None
logger = LoggerManager().getLogger(__name__)
logger.info("Request Bloomberg data")
# Do we need daily or intraday data?
if (md_request.freq
in ['daily', 'weekly', 'monthly', 'quarterly', 'yearly']):
# Work out the fields which need to be downloaded via Bloomberg ref request (BDP) and
# those that can be downloaded via Historical request (BDH)
ref_fields = []
ref_vendor_fields = []
# Get user defined list of BBG fields/vendor fields which need to
# be downloaded by BDP
bbg_ref_fields = list(constants.bbg_ref_fields.keys())
bbg_ref_vendor_fields = list(constants.bbg_ref_fields.values())
for i in range(0, len(md_request.fields)):
if md_request.fields[i] in bbg_ref_fields \
or md_request_vendor.fields[
i] in bbg_ref_vendor_fields:
ref_fields.append(md_request.fields[i])
ref_vendor_fields.append(md_request_vendor.fields[i])
non_ref_fields = []
non_ref_vendor_fields = []
for i in range(0, len(md_request.fields)):
if md_request.fields[i] not in bbg_ref_fields \
and md_request_vendor.fields[
i] not in bbg_ref_vendor_fields:
non_ref_fields.append(md_request.fields[i])
non_ref_vendor_fields.append(md_request_vendor.fields[i])
# For certain cases, need to use ReferenceDataRequest
# eg. for events times/dates, last tradeable date fields (when specified)
if len(ref_fields) > 0:
# Careful: make sure you copy the market data request object
# (when threading, altering that can
# cause concurrency issues!)
old_fields = copy.deepcopy(md_request.fields)
old_vendor_fields = copy.deepcopy(md_request_vendor.fields)
# md_request = MarketDataRequest(md_request=md_request_copy)
md_request.fields = ref_fields
md_request.vendor_fields = ref_vendor_fields
md_request_vendor = self.construct_vendor_md_request(
md_request)
# Just select those reference fields to download via reference
datetime_data_frame = self.get_reference_data(
md_request_vendor, md_request)
# Download all the other event or non-ref fields
# (uses HistoricalDataRequest to Bloomberg)
# concatenate with date time fields
if len(non_ref_fields) > 0:
md_request.fields = non_ref_fields
md_request.vendor_fields = non_ref_vendor_fields
md_request_vendor = self.construct_vendor_md_request(
md_request)
events_data_frame = self.get_daily_data(
md_request, md_request_vendor)
col = events_data_frame.index.name
events_data_frame = events_data_frame.reset_index(
drop=False)
data_frame = pd.concat(
[events_data_frame, datetime_data_frame], axis=1)
temp = data_frame[col]
del data_frame[col]
data_frame.index = temp
else:
data_frame = datetime_data_frame
md_request.fields = copy.deepcopy(old_fields)
md_request_vendor.fields = copy.deepcopy(old_vendor_fields)
# For all other daily/monthly/quarter data, we can use
# HistoricalDataRequest to Bloomberg
else:
data_frame = self.get_daily_data(md_request, md_request_vendor)
# if data_frame is not None:
# # Convert fields with release-dt to dates (special case!) and assume everything else numerical
# for c in data_frame.columns:
# try:
# if 'release-dt' in c:
# data_frame[c] = (data_frame[c]).astype('int').astype(str).apply(
# lambda x: pd.to_datetime(x, format='%Y%m%d'))
# else:
# data_frame[c] = pd.to_numeric(data_frame[c])
# except:
# pass
# Assume one ticker only for intraday data and use IntradayDataRequest
# to Bloomberg
if (md_request.freq
in ['tick', 'intraday', 'second', 'minute', 'hourly']):
md_request_vendor.tickers = \
md_request_vendor.tickers[0]
if md_request.freq in ['tick', 'second']:
data_frame = self.download_tick(md_request_vendor)
else:
data_frame = self.download_intraday(md_request_vendor)
if data_frame is not None:
if data_frame.empty:
try:
logger.info("No tickers returned for: " +
md_request_vendor.tickers)
except:
pass
return None
cols = data_frame.columns.values
import pytz
try:
data_frame = data_frame.tz_localize(pytz.utc)
except:
data_frame = data_frame.tz_convert(pytz.utc)
cols = md_request.tickers[0] + "." + cols
data_frame.columns = cols
logger.info("Completed request from Bloomberg.")
return data_frame
