def bdh(tickers,
flds=None,
start_date=None,
end_date='today',
adjust=None,
**kwargs) -> pd.DataFrame:
"""
Bloomberg historical data
Args:
tickers: ticker(s)
flds: field(s)
start_date: start date
end_date: end date - default today
adjust: `all`, `dvd`, `normal`, `abn` (=abnormal), `split`, `-` or None
exact match of above words will adjust for corresponding events
Case 0: `-` no adjustment for dividend or split
Case 1: `dvd` or `normal|abn` will adjust for all dividends except splits
Case 2: `adjust` will adjust for splits and ignore all dividends
Case 3: `all` == `dvd|split` == adjust for all
Case 4: None == Bloomberg default OR use kwargs
**kwargs: overrides
Returns:
pd.DataFrame
"""
logger = logs.get_logger(bdh, **kwargs)
if flds is None: flds = ['Last_Price']
e_dt = utils.fmt_dt(end_date, fmt='%Y%m%d')
if start_date is None:
start_date = pd.Timestamp(e_dt) - pd.Timedelta(weeks=8)
s_dt = utils.fmt_dt(start_date, fmt='%Y%m%d')
request = process.create_request(
service='//blp/refdata',
request='HistoricalDataRequest',
**kwargs,
)
process.init_request(request=request,
tickers=tickers,
flds=flds,
start_date=s_dt,
end_date=e_dt,
adjust=adjust,
**kwargs)
logger.debug(f'Sending request to Bloomberg ...\n{request}')
conn.send_request(request=request, **kwargs)
res = pd.DataFrame(process.rec_events(process.process_hist, **kwargs))
if kwargs.get('raw', False): return res
if res.empty or any(fld not in res for fld in ['ticker', 'date']):
return pd.DataFrame()
return (res.set_index(['ticker', 'date']).unstack(level=0).rename_axis(
index=None, columns=[None, None]).swaplevel(
0, 1, axis=1).reindex(columns=utils.flatten(tickers),
level=0).reindex(columns=utils.flatten(flds),
level=1))
def beqs(screen,
asof=None,
typ='PRIVATE',
group='General',
**kwargs) -> pd.DataFrame:
"""
Bloomberg equity screening
Args:
screen: screen name
asof: as of date
typ: GLOBAL/B (Bloomberg) or PRIVATE/C (Custom, default)
group: group name if screen is organized into groups
Returns:
pd.DataFrame
"""
logger = logs.get_logger(beqs, **kwargs)
service = conn.bbg_service(service='//blp/refdata', **kwargs)
request = service.createRequest('BeqsRequest')
request.set('screenName', screen)
request.set('screenType',
'GLOBAL' if typ[0].upper() in ['G', 'B'] else 'PRIVATE')
request.set('Group', group)
if asof:
overrides = request.getElement('overrides')
ovrd = overrides.appendElement()
ovrd.setElement('fieldId', 'PiTDate')
ovrd.setElement('value', utils.fmt_dt(asof, '%Y%m%d'))
logger.debug(f'Sending request to Bloomberg ...\n{request}')
conn.send_request(request=request, **kwargs)
res = pd.DataFrame(process.rec_events(func=process.process_ref, **kwargs))
if res.empty:
if kwargs.get('trial', 0): return pd.DataFrame()
else:
return beqs(screen=screen,
asof=asof,
typ=typ,
group=group,
trial=1,
**kwargs)
if kwargs.get('raw', False): return res
cols = res.field.unique()
return (res.set_index(['ticker', 'field']).unstack(level=1).rename_axis(
index=None,
columns=[None, None
]).droplevel(axis=1,
level=0).loc[:,
cols].pipe(pipeline.standard_cols))
def bds(tickers, flds, **kwargs) -> pd.DataFrame:
"""
Bloomberg block data
Args:
tickers: ticker(s)
flds: field
**kwargs: other overrides for query
Returns:
pd.DataFrame: block data
"""
logger = logs.get_logger(bds, **kwargs)
service = conn.bbg_service(service='//blp/refdata', **kwargs)
request = service.createRequest('ReferenceDataRequest')
if isinstance(tickers, str):
data_file = storage.ref_file(ticker=tickers,
fld=flds,
has_date=True,
ext='pkl',
**kwargs)
if files.exists(data_file):
logger.debug(f'Loading Bloomberg data from: {data_file}')
return pd.DataFrame(pd.read_pickle(data_file))
process.init_request(request=request,
tickers=tickers,
flds=flds,
**kwargs)
logger.debug(f'Sending request to Bloomberg ...\n{request}')
conn.send_request(request=request, **kwargs)
res = pd.DataFrame(
process.rec_events(func=process.process_ref, **kwargs))
if kwargs.get('raw', False): return res
if res.empty or any(fld not in res for fld in ['ticker', 'field']):
return pd.DataFrame()
data = (res.set_index(['ticker', 'field']).droplevel(
axis=0, level=1).rename_axis(index=None).pipe(
pipeline.standard_cols, col_maps=kwargs.get('col_maps', None)))
if data_file:
logger.debug(f'Saving Bloomberg data to: {data_file}')
files.create_folder(data_file, is_file=True)
data.to_pickle(data_file)
return data
return pd.DataFrame(
pd.concat(
[bds(tickers=ticker, flds=flds, **kwargs) for ticker in tickers],
sort=False))
def _bds_(
ticker: str,
fld: str,
logger: logs.logging.Logger,
use_port: bool = False,
**kwargs,
) -> pd.DataFrame:
"""
Get data of BDS of single ticker
"""
if 'has_date' not in kwargs: kwargs['has_date'] = True
data_file = storage.ref_file(ticker=ticker, fld=fld, ext='pkl', **kwargs)
if files.exists(data_file):
logger.debug(f'Loading Bloomberg data from: {data_file}')
return pd.DataFrame(pd.read_pickle(data_file))
request = process.create_request(
service='//blp/refdata',
request='PortfolioDataRequest' if use_port else 'ReferenceDataRequest',
**kwargs,
)
process.init_request(request=request, tickers=ticker, flds=fld, **kwargs)
logger.debug(f'Sending request to Bloomberg ...\n{request}')
conn.send_request(request=request, **kwargs)
res = pd.DataFrame(process.rec_events(func=process.process_ref, **kwargs))
if kwargs.get('raw', False): return res
if res.empty or any(fld not in res for fld in ['ticker', 'field']):
return pd.DataFrame()
data = (res.set_index(['ticker', 'field']).droplevel(
axis=0, level=1).rename_axis(index=None).pipe(pipeline.standard_cols,
col_maps=kwargs.get(
'col_maps', None)))
if data_file:
logger.debug(f'Saving Bloomberg data to: {data_file}')
files.create_folder(data_file, is_file=True)
data.to_pickle(data_file)
return data
def bdp(tickers, flds, **kwargs) -> pd.DataFrame:
"""
Bloomberg reference data
Args:
tickers: tickers
flds: fields to query
**kwargs: Bloomberg overrides
Returns:
pd.DataFrame
"""
logger = logs.get_logger(bdp, **kwargs)
if isinstance(tickers, str): tickers = [tickers]
if isinstance(flds, str): flds = [flds]
request = process.create_request(
service='//blp/refdata',
request='ReferenceDataRequest',
**kwargs,
)
process.init_request(request=request, tickers=tickers, flds=flds, **kwargs)
logger.debug(f'Sending request to Bloomberg ...\n{request}')
conn.send_request(request=request, **kwargs)
res = pd.DataFrame(process.rec_events(func=process.process_ref, **kwargs))
if kwargs.get('raw', False): return res
if res.empty or any(fld not in res for fld in ['ticker', 'field']):
return pd.DataFrame()
return (res.set_index(['ticker', 'field']).unstack(level=1).rename_axis(
index=None,
columns=[None,
None]).droplevel(axis=1,
level=0).loc[:, res.field.unique()].pipe(
pipeline.standard_cols,
col_maps=kwargs.get('col_maps', None)))
def bdtick(ticker,
dt,
session='allday',
time_range=None,
types=None,
**kwargs) -> pd.DataFrame:
"""
Bloomberg tick data
Args:
ticker: ticker name
dt: date to download
session: [allday, day, am, pm, pre, post]
time_range: tuple of start and end time (must be converted into UTC)
if this is given, `dt` and `session` will be ignored
types: str or list, one or combinations of [
TRADE, AT_TRADE, BID, ASK, MID_PRICE,
BID_BEST, ASK_BEST, BEST_BID, BEST_ASK,
]
Returns:
pd.DataFrame
"""
logger = logs.get_logger(bdtick, **kwargs)
if types is None: types = ['TRADE']
exch = const.exch_info(ticker=ticker, **kwargs)
if exch.empty: raise LookupError(f'Cannot find exchange info for {ticker}')
if isinstance(time_range, (tuple, list)) and (len(time_range) == 2):
cur_dt = pd.Timestamp(dt).strftime('%Y-%m-%d')
time_rng = (pd.DatetimeIndex([
f'{cur_dt} {time_range[0]}',
f'{cur_dt} {time_range[1]}',
]).tz_localize(exch.tz).tz_convert(
process.DEFAULT_TZ).tz_convert('UTC'))
else:
time_rng = process.time_range(dt=dt,
ticker=ticker,
session=session,
**kwargs)
while conn.bbg_session(**kwargs).tryNextEvent():
pass
request = process.create_request(
service='//blp/refdata',
request='IntradayTickRequest',
settings=[
('security', ticker),
('startDateTime', time_rng[0]),
('endDateTime', time_rng[1]),
('includeConditionCodes', True),
('includeExchangeCodes', True),
('includeNonPlottableEvents', True),
('includeBrokerCodes', True),
('includeRpsCodes', True),
('includeTradeTime', True),
('includeActionCodes', True),
('includeIndicatorCodes', True),
],
append={'eventTypes': types},
**kwargs,
)
logger.debug(f'Sending request to Bloomberg ...\n{request}')
conn.send_request(request=request)
res = pd.DataFrame(
process.rec_events(func=process.process_bar, typ='t', **kwargs))
if kwargs.get('raw', False): return res
if res.empty or ('time' not in res): return pd.DataFrame()
return (res.set_index('time').rename_axis(
index=None).tz_localize('UTC').tz_convert(exch.tz).pipe(
pipeline.add_ticker, ticker=ticker).rename(
columns={
'size': 'volume',
'type': 'typ',
'conditionCodes': 'cond',
'exchangeCode': 'exch',
'tradeTime': 'trd_time',
}))
def bdib(ticker: str,
dt,
session='allday',
typ='TRADE',
**kwargs) -> pd.DataFrame:
"""
Bloomberg intraday bar data
Args:
ticker: ticker name
dt: date to download
session: [allday, day, am, pm, pre, post]
typ: [TRADE, BID, ASK, BID_BEST, ASK_BEST, BEST_BID, BEST_ASK]
**kwargs:
ref: reference ticker or exchange
used as supplement if exchange info is not defined for `ticker`
batch: whether is batch process to download data
log: level of logs
Returns:
pd.DataFrame
"""
from xbbg.core import trials
logger = logs.get_logger(bdib, **kwargs)
ex_info = const.exch_info(ticker=ticker, **kwargs)
if ex_info.empty: raise KeyError(f'Cannot find exchange info for {ticker}')
ss_rng = process.time_range(dt=dt,
ticker=ticker,
session=session,
tz=ex_info.tz,
**kwargs)
data_file = storage.bar_file(ticker=ticker, dt=dt, typ=typ)
if files.exists(data_file) and kwargs.get(
'cache', True) and (not kwargs.get('reload', False)):
res = (pd.read_parquet(data_file).pipe(
pipeline.add_ticker, ticker=ticker).loc[ss_rng[0]:ss_rng[1]])
if not res.empty:
logger.debug(f'Loading Bloomberg intraday data from: {data_file}')
return res
if not process.check_current(dt=dt, logger=logger, **kwargs):
return pd.DataFrame()
cur_dt = pd.Timestamp(dt).strftime('%Y-%m-%d')
q_tckr = ticker
if ex_info.get('is_fut', False):
is_sprd = ex_info.get(
'has_sprd', False) and (len(ticker[:-1]) != ex_info['tickers'][0])
if not is_sprd:
q_tckr = fut_ticker(gen_ticker=ticker, dt=dt, freq=ex_info['freq'])
if q_tckr == '':
logger.error(f'cannot find futures ticker for {ticker} ...')
return pd.DataFrame()
info_log = f'{q_tckr} / {cur_dt} / {typ}'
trial_kw = dict(ticker=ticker, dt=dt, typ=typ, func='bdib')
num_trials = trials.num_trials(**trial_kw)
if num_trials >= 2:
if kwargs.get('batch', False): return pd.DataFrame()
logger.info(f'{num_trials} trials with no data {info_log}')
return pd.DataFrame()
while conn.bbg_session(**kwargs).tryNextEvent():
pass
time_rng = process.time_range(dt=dt,
ticker=ticker,
session='allday',
**kwargs)
request = process.create_request(
service='//blp/refdata',
request='IntradayBarRequest',
settings=[
('security', ticker),
('eventType', typ),
('interval', kwargs.get('interval', 1)),
('startDateTime', time_rng[0]),
('endDateTime', time_rng[1]),
],
**kwargs,
)
logger.debug(f'Sending request to Bloomberg ...\n{request}')
conn.send_request(request=request, **kwargs)
res = pd.DataFrame(process.rec_events(func=process.process_bar, **kwargs))
if res.empty or ('time' not in res):
logger.warning(f'No data for {info_log} ...')
trials.update_trials(cnt=num_trials + 1, **trial_kw)
return pd.DataFrame()
data = (res.set_index('time').rename_axis(index=None).rename(
columns={
'numEvents': 'num_trds'
}).tz_localize('UTC').tz_convert(ex_info.tz).pipe(pipeline.add_ticker,
ticker=ticker))
if kwargs.get('cache', True):
storage.save_intraday(data=data[ticker],
ticker=ticker,
dt=dt,
typ=typ,
**kwargs)
return data.loc[ss_rng[0]:ss_rng[1]]
def bdtick(ticker, dt, session='allday', types=None, **kwargs) -> pd.DataFrame:
"""
Bloomberg tick data
Args:
ticker: ticker name
dt: date to download
session: [allday, day, am, pm, pre, post]
types: str or list, one or combinations of [
TRADE, AT_TRADE, BID, ASK, MID_PRICE,
BID_BEST, ASK_BEST, BEST_BID, BEST_ASK,
]
Returns:
pd.DataFrame
"""
logger = logs.get_logger(bdtick, **kwargs)
exch = const.exch_info(ticker=ticker, **kwargs)
time_rng = process.time_range(dt=dt,
ticker=ticker,
session=session,
tz=exch.tz,
**kwargs)
service = conn.bbg_service(service='//blp/refdata', **kwargs)
request = service.createRequest('IntradayTickRequest')
while conn.bbg_session(**kwargs).tryNextEvent():
pass
if types is None: types = ['TRADE']
if isinstance(types, str): types = [types]
request.set('security', ticker)
for typ in types:
request.append('eventTypes', typ)
request.set('startDateTime', time_rng[0])
request.set('endDateTime', time_rng[1])
request.set('includeConditionCodes', True)
request.set('includeExchangeCodes', True)
request.set('includeNonPlottableEvents', True)
request.set('includeBrokerCodes', True)
request.set('includeRpsCodes', True)
request.set('includeTradeTime', True)
request.set('includeActionCodes', True)
request.set('includeIndicatorCodes', True)
logger.debug(f'Sending request to Bloomberg ...\n{request}')
conn.send_request(request=request)
res = pd.DataFrame(
process.rec_events(func=process.process_bar, typ='t', **kwargs))
if kwargs.get('raw', False): return res
if res.empty or ('time' not in res): return pd.DataFrame()
return (res.set_index('time').rename_axis(
index=None).tz_localize('UTC').tz_convert(exch.tz).pipe(
pipeline.add_ticker, ticker=ticker).rename(
columns={
'size': 'volume',
'type': 'typ',
'conditionCodes': 'cond',
'exchangeCode': 'exch',
'tradeTime': 'trd_time',
}))
