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 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)))