def bdib(ticker, dt, typ='TRADE', batch=False, log=logs.LOG_LEVEL) -> pd.DataFrame:
"""
Download intraday data and save to cache
Args:
ticker: ticker name
dt: date to download
typ: [TRADE, BID, ASK, BID_BEST, ASK_BEST, BEST_BID, BEST_ASK]
batch: whether is batch process to download data
log: level of logs
Returns:
pd.DataFrame
"""
from xbbg.core import missing
logger = logs.get_logger(bdib, level=log)
t_1 = pd.Timestamp('today').date() - pd.Timedelta('1D')
whole_day = pd.Timestamp(dt).date() < t_1
if (not whole_day) and batch:
logger.warning(f'querying date {t_1} is too close, ignoring download ...')
return pd.DataFrame()
cur_dt = pd.Timestamp(dt).strftime('%Y-%m-%d')
asset = ticker.split()[-1]
info_log = f'{ticker} / {cur_dt} / {typ}'
if asset in ['Equity', 'Curncy', 'Index', 'Comdty']:
exch = const.exch_info(ticker=ticker)
if exch.empty: return pd.DataFrame()
else:
logger.error(f'unknown asset type: {asset}')
return pd.DataFrame()
time_fmt = '%Y-%m-%dT%H:%M:%S'
time_idx = pd.DatetimeIndex([
f'{cur_dt} {exch.allday[0]}', f'{cur_dt} {exch.allday[-1]}']
).tz_localize(exch.tz).tz_convert(DEFAULT_TZ).tz_convert('UTC')
if time_idx[0] > time_idx[1]: time_idx -= pd.TimedeltaIndex(['1D', '0D'])
q_tckr = ticker
if exch.get('is_fut', False):
if 'freq' not in exch:
logger.error(f'[freq] missing in info for {info_log} ...')
is_sprd = exch.get('has_sprd', False) and (len(ticker[:-1]) != exch['tickers'][0])
if not is_sprd:
q_tckr = fut_ticker(gen_ticker=ticker, dt=dt, freq=exch['freq'])
if q_tckr == '':
logger.error(f'cannot find futures ticker for {ticker} ...')
return pd.DataFrame()
info_log = f'{q_tckr} / {cur_dt} / {typ}'
miss_kw = dict(ticker=ticker, dt=dt, typ=typ, func='bdib')
cur_miss = missing.current_missing(**miss_kw)
if cur_miss >= 2:
if batch: return pd.DataFrame()
logger.info(f'{cur_miss} trials with no data {info_log}')
return pd.DataFrame()
logger.info(f'loading data from Bloomberg: {info_log} ...')
con, _ = create_connection()
data = con.bdib(
ticker=q_tckr, event_type=typ, interval=1,
start_datetime=time_idx[0].strftime(time_fmt),
end_datetime=time_idx[1].strftime(time_fmt),
)
if not isinstance(data, pd.DataFrame):
raise ValueError(f'unknown output format: {type(data)}')
if data.empty:
logger.warning(f'no data for {info_log} ...')
missing.update_missing(**miss_kw)
return pd.DataFrame()
data = data.tz_localize('UTC').tz_convert(exch.tz)
storage.save_intraday(data=data, ticker=ticker, dt=dt, typ=typ)
return pd.DataFrame() if batch else assist.format_intraday(data=data, ticker=ticker)
def wrapper(*args, **kwargs):
scope = utils.func_scope(func=func)
param = inspect.signature(func).parameters
port = kwargs.pop('port', _PORT_)
timeout = kwargs.pop('timeout', _TIMEOUT_)
restart = kwargs.pop('restart', False)
all_kw = {
k: args[n] if n < len(args) else v.default
for n, (k, v) in enumerate(param.items()) if k != 'kwargs'
}
all_kw.update(kwargs)
log_level = kwargs.get('log', logs.LOG_LEVEL)
for to_list in ['tickers', 'flds']:
conv = all_kw.get(to_list, None)
if hasattr(conv, 'tolist'):
all_kw[to_list] = getattr(conv, 'tolist')()
if isinstance(conv, str):
all_kw[to_list] = [conv]
cached_data = []
if scope in ['xbbg.blp.bdp', 'xbbg.blp.bds']:
to_qry = cached.bdp_bds_cache(func=func.__name__, **all_kw)
cached_data += to_qry.cached_data
if not (to_qry.tickers and to_qry.flds):
if not cached_data: return pd.DataFrame()
res = pd.concat(cached_data, sort=False).reset_index(drop=True)
if not all_kw.get('raw', False):
res = assist.format_output(data=res,
source=func.__name__,
col_maps=all_kw.get(
'col_maps', dict()))
return res
all_kw['tickers'] = to_qry.tickers
all_kw['flds'] = to_qry.flds
if scope in ['xbbg.blp.bdib']:
data_file = storage.hist_file(
ticker=all_kw['ticker'],
dt=all_kw['dt'],
typ=all_kw['typ'],
)
if files.exists(data_file):
logger = logs.get_logger(func, level=log_level)
if all_kw.get('batch', False): return
logger.debug(f'reading from {data_file} ...')
return assist.format_intraday(data=pd.read_parquet(data_file),
**all_kw)
_, new = create_connection(port=port, timeout=timeout, restart=restart)
res = func(
**
{k: v
for k, v in all_kw.items() if k not in ['raw', 'col_maps']})
if new: delete_connection()
if scope.startswith('xbbg.blp.') and isinstance(res, list):
final = cached_data + res
if not final: return pd.DataFrame()
res = pd.DataFrame(pd.concat(final, sort=False))
if (scope in ['xbbg.blp.bdp', 'xbbg.blp.bds']) \
and (not all_kw.get('raw', False)):
res = assist.format_output(
data=res.reset_index(drop=True),
source=func.__name__,
col_maps=all_kw.get('col_maps', dict()),
)
return res