def lookup_symbol(self, symbol, as_of_date, fuzzy=False):
"""
Return matching Equity of name symbol in database.
If multiple Equities are found and as_of_date is not set,
raises MultipleSymbolsFound.
If no Equity was active at as_of_date raises SymbolNotFound.
"""
company_symbol, share_class_symbol, fuzzy_symbol = split_delimited_symbol(symbol)
if as_of_date:
# Format inputs
as_of_date = pd.Timestamp(as_of_date).normalize()
ad_value = as_of_date.value
if fuzzy:
# Search for a single exact match on the fuzzy column
candidates = self._get_fuzzy_candidates_in_range(fuzzy_symbol, ad_value)
# If exactly one SID exists for fuzzy_symbol, return that sid
if len(candidates) == 1:
return self._get_best_candidate(candidates)
# Search for exact matches of the split-up company_symbol and
# share_class_symbol
candidates = self._get_split_candidates_in_range(company_symbol, share_class_symbol, ad_value)
# If exactly one SID exists for symbol, return that symbol
# If multiple SIDs exist for symbol, return latest start_date with
# end_date as a tie-breaker
if candidates:
return self._get_best_candidate(candidates)
# If no SID exists for symbol, return SID with the
# highest-but-not-over end_date
elif not candidates:
candidates = self._resolve_no_matching_candidates(company_symbol, share_class_symbol, ad_value)
if candidates:
return self._get_best_candidate(candidates)
raise SymbolNotFound(symbol=symbol)
else:
# If this is a fuzzy look-up, check if there is exactly one match
# for the fuzzy symbol
if fuzzy:
candidates = self._get_fuzzy_candidates(fuzzy_symbol)
if len(candidates) == 1:
return self._get_best_candidate(candidates)
candidates = self._get_split_candidates(company_symbol, share_class_symbol)
if len(candidates) == 1:
return self._get_best_candidate(candidates)
elif not candidates:
raise SymbolNotFound(symbol=symbol)
else:
raise MultipleSymbolsFound(symbol=symbol, options=self._get_equities_from_candidates(candidates))
def lookup_symbol(self, symbol, as_of_date, fuzzy=False):
"""
Return matching Equity of name symbol in database.
If multiple Equities are found and as_of_date is not set,
raises MultipleSymbolsFound.
If no Equity was active at as_of_date raises SymbolNotFound.
"""
company_symbol, share_class_symbol, fuzzy_symbol = \
split_delimited_symbol(symbol)
if as_of_date:
# Format inputs
as_of_date = pd.Timestamp(as_of_date).normalize()
ad_value = as_of_date.value
if fuzzy:
# Search for a single exact match on the fuzzy column
candidates = self._get_fuzzy_candidates_in_range(fuzzy_symbol,
ad_value)
# If exactly one SID exists for fuzzy_symbol, return that sid
if len(candidates) == 1:
return self._get_best_candidate(candidates)
# Search for exact matches of the split-up company_symbol and
# share_class_symbol
candidates = self._get_split_candidates_in_range(
company_symbol,
share_class_symbol,
ad_value
)
# If exactly one SID exists for symbol, return that symbol
# If multiple SIDs exist for symbol, return latest start_date with
# end_date as a tie-breaker
if candidates:
return self._get_best_candidate(candidates)
# If no SID exists for symbol, return SID with the
# highest-but-not-over end_date
elif not candidates:
candidates = self._resolve_no_matching_candidates(
company_symbol,
share_class_symbol,
ad_value
)
if candidates:
return self._get_best_candidate(candidates)
raise SymbolNotFound(symbol=symbol)
else:
# If this is a fuzzy look-up, check if there is exactly one match
# for the fuzzy symbol
if fuzzy:
candidates = self._get_fuzzy_candidates(fuzzy_symbol)
if len(candidates) == 1:
return self._get_best_candidate(candidates)
candidates = self._get_split_candidates(company_symbol,
share_class_symbol)
if len(candidates) == 1:
return self._get_best_candidate(candidates)
elif not candidates:
raise SymbolNotFound(symbol=symbol)
else:
raise MultipleSymbolsFound(
symbol=symbol,
options=self._get_equities_from_candidates(candidates)
)
def lookup_symbol(self, symbol, as_of_date, fuzzy=False):
"""
Return matching Equity of name symbol in database.
If multiple Equities are found and as_of_date is not set,
raises MultipleSymbolsFound.
If no Equity was active at as_of_date raises SymbolNotFound.
"""
# Format inputs
symbol = symbol.upper()
if as_of_date is not None:
as_of_date = pd.Timestamp(normalize_date(as_of_date))
company_symbol, share_class_symbol, fuzzy_symbol = \
split_delimited_symbol(symbol)
equities_cols = self.equities.c
if as_of_date:
ad_value = as_of_date.value
if fuzzy:
# Search for a single exact match on the fuzzy column
fuzzy_candidates = sa.select((equities_cols.sid,)).where(
(equities_cols.fuzzy_symbol == fuzzy_symbol) &
(equities_cols.start_date <= ad_value) &
(equities_cols.end_date >= ad_value),
).execute().fetchall()
# If exactly one SID exists for fuzzy_symbol, return that sid
if len(fuzzy_candidates) == 1:
return self._retrieve_equity(fuzzy_candidates[0]['sid'])
# Search for exact matches of the split-up company_symbol and
# share_class_symbol
candidates = sa.select((equities_cols.sid,)).where(
(equities_cols.company_symbol == company_symbol) &
(equities_cols.share_class_symbol == share_class_symbol) &
(equities_cols.start_date <= ad_value) &
(equities_cols.end_date >= ad_value),
).execute().fetchall()
# If exactly one SID exists for symbol, return that symbol
if len(candidates) == 1:
return self._retrieve_equity(candidates[0]['sid'])
# If no SID exists for symbol, return SID with the
# highest-but-not-over end_date
elif not candidates:
sid = sa.select((equities_cols.sid,)).where(
(equities_cols.company_symbol == company_symbol) &
(equities_cols.share_class_symbol == share_class_symbol) &
(equities_cols.start_date <= ad_value),
).order_by(
equities_cols.end_date.desc(),
).scalar()
if sid is not None:
return self._retrieve_equity(sid)
# If multiple SIDs exist for symbol, return latest start_date with
# end_date as a tie-breaker
elif len(candidates) > 1:
sid = sa.select((equities_cols.sid,)).where(
(equities_cols.company_symbol == company_symbol) &
(equities_cols.share_class_symbol == share_class_symbol) &
(equities_cols.start_date <= ad_value),
).order_by(
equities_cols.start_date.desc(),
equities_cols.end_date.desc(),
).scalar()
if sid is not None:
return self._retrieve_equity(sid)
raise SymbolNotFound(symbol=symbol)
else:
# If this is a fuzzy look-up, check if there is exactly one match
# for the fuzzy symbol
if fuzzy:
fuzzy_sids = sa.select((equities_cols.sid,)).where(
(equities_cols.fuzzy_symbol == fuzzy_symbol)
).execute().fetchall()
if len(fuzzy_sids) == 1:
return self._retrieve_equity(fuzzy_sids[0]['sid'])
sids = sa.select((equities_cols.sid,)).where(
(equities_cols.company_symbol == company_symbol) &
(equities_cols.share_class_symbol == share_class_symbol)
).execute().fetchall()
if len(sids) == 1:
return self._retrieve_equity(sids[0]['sid'])
elif not sids:
raise SymbolNotFound(symbol=symbol)
else:
raise MultipleSymbolsFound(
symbol=symbol,
options=list(map(
compose(self._retrieve_equity, itemgetter('sid')),
sids,
))
)
def lookup_symbol(self, symbol, as_of_date, fuzzy=False):
"""
Return matching Equity of name symbol in database.
If multiple Equities are found and as_of_date is not set,
raises MultipleSymbolsFound.
If no Equity was active at as_of_date raises SymbolNotFound.
"""
# Format inputs
if as_of_date is not None:
as_of_date = pd.Timestamp(normalize_date(as_of_date))
company_symbol, share_class_symbol, fuzzy_symbol = \
split_delimited_symbol(symbol)
equities_cols = self.equities.c
if as_of_date:
ad_value = as_of_date.value
if fuzzy:
# Search for a single exact match on the fuzzy column
fuzzy_candidates = sa.select((equities_cols.sid, )).where(
(equities_cols.fuzzy_symbol == fuzzy_symbol) &
(equities_cols.start_date <= ad_value) &
(equities_cols.end_date >=
ad_value), ).execute().fetchall()
# If exactly one SID exists for fuzzy_symbol, return that sid
if len(fuzzy_candidates) == 1:
return self._retrieve_equity(fuzzy_candidates[0]['sid'])
# Search for exact matches of the split-up company_symbol and
# share_class_symbol
candidates = sa.select((equities_cols.sid, )).where(
(equities_cols.company_symbol == company_symbol) &
(equities_cols.share_class_symbol == share_class_symbol) &
(equities_cols.start_date <= ad_value) &
(equities_cols.end_date >= ad_value), ).execute().fetchall()
# If exactly one SID exists for symbol, return that symbol
if len(candidates) == 1:
return self._retrieve_equity(candidates[0]['sid'])
# If no SID exists for symbol, return SID with the
# highest-but-not-over end_date
elif not candidates:
sid = sa.select((equities_cols.sid, )).where(
(equities_cols.company_symbol == company_symbol) &
(equities_cols.share_class_symbol == share_class_symbol) &
(equities_cols.start_date <= ad_value), ).order_by(
equities_cols.end_date.desc(), ).scalar()
if sid is not None:
return self._retrieve_equity(sid)
# If multiple SIDs exist for symbol, return latest start_date with
# end_date as a tie-breaker
elif len(candidates) > 1:
sid = sa.select((equities_cols.sid, )).where(
(equities_cols.company_symbol == company_symbol) &
(equities_cols.share_class_symbol == share_class_symbol) &
(equities_cols.start_date <= ad_value), ).order_by(
equities_cols.start_date.desc(),
equities_cols.end_date.desc(),
).scalar()
if sid is not None:
return self._retrieve_equity(sid)
raise SymbolNotFound(symbol=symbol)
else:
# If this is a fuzzy look-up, check if there is exactly one match
# for the fuzzy symbol
if fuzzy:
fuzzy_sids = sa.select((equities_cols.sid, )).where(
(equities_cols.fuzzy_symbol == fuzzy_symbol
)).execute().fetchall()
if len(fuzzy_sids) == 1:
return self._retrieve_equity(fuzzy_sids[0]['sid'])
sids = sa.select((equities_cols.sid, )).where(
(equities_cols.company_symbol == company_symbol)
& (equities_cols.share_class_symbol == share_class_symbol)
).execute().fetchall()
if len(sids) == 1:
return self._retrieve_equity(sids[0]['sid'])
elif not sids:
raise SymbolNotFound(symbol=symbol)
else:
raise MultipleSymbolsFound(symbol=symbol,
options=list(
map(
compose(
self._retrieve_equity,
itemgetter('sid')),
sids,
)))