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#104 fix deprecation ts #105

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18 changes: 9 additions & 9 deletions yfinance_cache/yfc_cache_manager.py
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Original file line number Diff line number Diff line change
Expand Up @@ -200,7 +200,7 @@ def ReadCacheDatum(ticker, objectName, return_metadata_too=False):
expiry = d["expiry"] if "expiry" in d else None

if expiry is not None:
dtnow = pd.Timestamp.utcnow().replace(tzinfo=ZoneInfo("UTC"))
dtnow = pd.Timestamp.now('UTC').replace(tzinfo=ZoneInfo("UTC"))
if dtnow >= expiry:
if verbose:
print("Deleting expired datum '{0}/{1}'".format(ticker, objectName))
Expand Down Expand Up @@ -238,7 +238,7 @@ def ReadCachePackedDatum(ticker, objectName, return_metadata_too=False):
expiry = objData["expiry"] if "expiry" in objData else None

if expiry is not None:
dtnow = pd.Timestamp.utcnow().replace(tzinfo=ZoneInfo("UTC"))
dtnow = pd.Timestamp.now('UTC').replace(tzinfo=ZoneInfo("UTC"))
if dtnow >= expiry:
if verbose:
print("Deleting expired packed datum '{0}/{1}'".format(ticker, objectName))
Expand Down Expand Up @@ -275,7 +275,7 @@ def StoreCacheDatum(ticker, objectName, datum, expiry=None, metadata=None):
if expiry is not None:
if isinstance(expiry, yfcd.Interval):
# Convert interval to actual datetime
expiry = pd.Timestamp.utcnow().replace(tzinfo=ZoneInfo("UTC")) + yfcd.intervalToTimedelta[expiry]
expiry = pd.Timestamp.now('UTC').replace(tzinfo=ZoneInfo("UTC")) + yfcd.intervalToTimedelta[expiry]
if not isinstance(expiry, datetime):
raise Exception("'expiry' must be datetime or yfcd.Interval")

Expand Down Expand Up @@ -339,7 +339,7 @@ def StoreCachePackedDatum(ticker, objectName, datum, expiry=None, metadata=None)
if expiry is not None:
if isinstance(expiry, yfcd.Interval):
# Convert interval to actual datetime
expiry = pd.Timestamp.utcnow().replace(tzinfo=ZoneInfo("UTC")) + yfcd.intervalToTimedelta[expiry]
expiry = pd.Timestamp.now('UTC').replace(tzinfo=ZoneInfo("UTC")) + yfcd.intervalToTimedelta[expiry]
if not isinstance(expiry, datetime):
raise Exception("'expiry' must be datetime or yfcd.Interval")
if (metadata is not None) and "Expiry" in metadata.keys():
Expand Down Expand Up @@ -508,11 +508,11 @@ def _load_option(self):
self.options = {}
# Initialise
a = self.__getattr__('max_ages')
a.calendar = '7d'
a.info = '45d'
a.options = '1d'
a.holdings = '91d'
a.analysis = '91d'
a.calendar = '7D'
a.info = '45D'
a.options = '1D'
a.holdings = '91D'
a.analysis = '91D'
c = self.__getattr__('calendar')
c.accept_unexpected_Yahoo_intervals = True

Expand Down
24 changes: 12 additions & 12 deletions yfinance_cache/yfc_financials_manager.py
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Original file line number Diff line number Diff line change
Expand Up @@ -469,7 +469,7 @@ def _get_fin_table(self, finType, period, refresh=True):
if df is None:
do_fetch = True
elif refresh:
dt_now = pd.Timestamp.utcnow().tz_convert(self.tzName)
dt_now = pd.Timestamp.now('UTC').tz_convert(self.tzName)
if df.empty:
# Nothing to estimate releases on, so just periodically check
try:
Expand Down Expand Up @@ -574,7 +574,7 @@ def _get_fin_table(self, finType, period, refresh=True):
print(msg)
df_new = getattr(self.dat, name)
df_new = df_new.astype('float')
fetch_dt = pd.Timestamp.utcnow().tz_convert(self.tzName)
fetch_dt = pd.Timestamp.now('UTC').tz_convert(self.tzName)
if md is None:
md = {'FetchDates':{}}
for dt in df_new.columns:
Expand Down Expand Up @@ -798,7 +798,7 @@ def get_release_dates(self, period, preferred_fin=yfcd.Financials.IncomeStmt, as

max_age = pd.Timedelta(yfcm._option_manager.max_ages.calendar)
dt_now = pd.Timestamp.now()
d_exchange = pd.Timestamp.utcnow().tz_convert(self.tzName).date()
d_exchange = pd.Timestamp.now('UTC').tz_convert(self.tzName).date()
if releases is None:
if md is None:
do_calc = True
Expand Down Expand Up @@ -2079,7 +2079,7 @@ def get_earnings_dates(self, start, refresh=True, clean=True):
if debug:
print(f"get_earnings_dates(start={start}, refresh={refresh})")

dt_now = pd.Timestamp.utcnow().tz_convert(self.tzName)
dt_now = pd.Timestamp.now('UTC').tz_convert(self.tzName)

last_fetch = None
if self._earnings_dates is None:
Expand Down Expand Up @@ -2163,7 +2163,7 @@ def get_earnings_dates(self, start, refresh=True, clean=True):
if debug:
print("- yf_start_date =", yf_start_date)
if last_fetch is not None:
if (last_fetch + pd.Timedelta('14d')) > dt_now:
if (last_fetch + pd.Timedelta('14D')) > dt_now:
# Avoid spamming Yahoo for data it doesn't have (empty earnings_dates).
if self._earnings_dates is None:
# Already attempted a fetch recently, Yahoo has nothing.
Expand Down Expand Up @@ -2191,17 +2191,17 @@ def get_earnings_dates(self, start, refresh=True, clean=True):
if isinstance(ei, (yfcd.ComparableRelativedelta, relativedelta)):
# Convert to normal Timedelta, don't need 100% precision
if ei.months == 3:
ei = pd.Timedelta('91d')
ei = pd.Timedelta('91D')
elif ei.months == 6:
ei = pd.Timedelta('182d')
ei = pd.Timedelta('182D')
elif ei.months == 12 or ei.years==1:
# ei = pd.Timedelta('365d')
# ei = pd.Timedelta('365D')
# Don't believe it
ei = pd.Timedelta('182d')
ei = pd.Timedelta('182D')
else:
raise Exception(ei, type(ei))

lookahead_dt = dt_now + pd.Timedelta('365d')
lookahead_dt = dt_now + pd.Timedelta('365D')
if debug:
print("- ei =", ei)
print("- lookahead_dt =", lookahead_dt)
Expand All @@ -2215,7 +2215,7 @@ def get_earnings_dates(self, start, refresh=True, clean=True):
df = self._earnings_dates.copy()
f_na = df['Reported EPS'].isna().to_numpy()
f_nna = ~f_na
f_expired = f_na & (df.index < dt_now) & ((dt_now - df['FetchDate']) > pd.Timedelta('7d')).to_numpy()
f_expired = f_na & (df.index < dt_now) & ((dt_now - df['FetchDate']) > pd.Timedelta('7D')).to_numpy()
n = df.shape[0]
if debug:
print("- n =", n)
Expand Down Expand Up @@ -2417,7 +2417,7 @@ def _fetch_earnings_dates(self, limit, refresh=True):
if debug:
print("- Yahoo returned None")
return None
df['FetchDate'] = pd.Timestamp.utcnow().tz_convert(self.tzName)
df['FetchDate'] = pd.Timestamp.now('UTC').tz_convert(self.tzName)

if df.shape[0] < limit:
if debug:
Expand Down
16 changes: 8 additions & 8 deletions yfinance_cache/yfc_prices_manager.py
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Original file line number Diff line number Diff line change
Expand Up @@ -527,7 +527,7 @@ def get(self, start=None, end=None, period=None,
yfct.SetExchangeTzName(self.exchange, self.tzName)
td_1d = timedelta(days=1)
tz_exchange = ZoneInfo(self.tzName)
dt_now = pd.Timestamp.utcnow().tz_convert(tz_exchange)
dt_now = pd.Timestamp.now('UTC').tz_convert(tz_exchange)
d_now_exchange = dt_now.date()
tomorrow_d = d_now_exchange + td_1d
if self.interday:
Expand Down Expand Up @@ -1337,7 +1337,7 @@ def _fetchAndAddRanges_sparse(self, ranges_to_fetch, prepost, debug, quiet=False

tz_exchange = self.tz
td_1d = timedelta(days=1)
dtnow = pd.Timestamp.utcnow().tz_convert(tz_exchange)
dtnow = pd.Timestamp.now('UTC').tz_convert(tz_exchange)

# Backport events that occurred since last adjustment:
self._applyNewEvents()
Expand Down Expand Up @@ -1464,7 +1464,7 @@ def _verifyCachedPrices(self, rtol=0.0001, vol_rtol=0.004, correct=False, discar
h["Volume"] = (h["Volume"].to_numpy() / h["CSF"].to_numpy()).round().astype('int')

td_1d = pd.Timedelta("1D")
dt_now = pd.Timestamp.utcnow().tz_convert(ZoneInfo("UTC"))
dt_now = pd.Timestamp.now('UTC').tz_convert(ZoneInfo("UTC"))

def _aggregate_yfdf_daily(df):
df2 = df.copy()
Expand Down Expand Up @@ -1884,7 +1884,7 @@ def _fetchYfHistory(self, start, end, prepost, debug, verify_intervals=True, dis

tz_exchange = self.tz
td_1d = timedelta(days=1)
dt_now = pd.Timestamp.utcnow().tz_convert(ZoneInfo("UTC"))
dt_now = pd.Timestamp.now('UTC').tz_convert(ZoneInfo("UTC"))

if self.intraday:
maxLookback = yfcd.yfMaxFetchLookback[self.interval] - timedelta(seconds=10)
Expand Down Expand Up @@ -2064,7 +2064,7 @@ def _fetchYfHistory(self, start, end, prepost, debug, verify_intervals=True, dis
if df.index.duplicated().any():
raise Exception("df contains duplicated dates")

fetch_dt_utc = pd.Timestamp.utcnow().tz_convert(ZoneInfo("UTC"))
fetch_dt_utc = pd.Timestamp.now('UTC').tz_convert(ZoneInfo("UTC"))

if (df is not None) and (df.index.tz is not None) and (not isinstance(df.index.tz, ZoneInfo)):
# Convert to ZoneInfo
Expand Down Expand Up @@ -2767,7 +2767,7 @@ def _reconstruct_intervals_batch(self, df, tag=-1):
if min_lookback is None:
min_dt = None
else:
min_dt = pd.Timestamp.utcnow().tz_convert(ZoneInfo("UTC")) - min_lookback
min_dt = pd.Timestamp.now('UTC').tz_convert(ZoneInfo("UTC")) - min_lookback
if debug:
print(f"- min_dt={min_dt} interval={self.interval} sub_interval={sub_interval}")
if min_dt is not None:
Expand Down Expand Up @@ -4056,7 +4056,7 @@ def _reverseYahooAdjust(self, df):
df["CSF"] = csf
df["CDF"] = cdf

h_lastDivAdjustDt = pd.Timestamp.utcnow().tz_convert(ZoneInfo("UTC"))
h_lastDivAdjustDt = pd.Timestamp.now('UTC').tz_convert(ZoneInfo("UTC"))
h_lastSplitAdjustDt = h_lastDivAdjustDt
df["LastDivAdjustDt"] = h_lastDivAdjustDt
df["LastSplitAdjustDt"] = h_lastSplitAdjustDt
Expand Down Expand Up @@ -4206,7 +4206,7 @@ def _applyNewEvents(self):
# This can happen with recent multiday intervals and that's ok, and will correct manually.
f1_oldest_idx = np.where(f1)[0][-1]
f1_oldest_dt = self.h.index[f1_oldest_idx]
is_f1_oldest_dt_recent = (pd.Timestamp.utcnow() - f1_oldest_dt) < (1.5*self.itd)
is_f1_oldest_dt_recent = (pd.Timestamp.now('UTC') - f1_oldest_dt) < (1.5*self.itd)
if self.interday and self.interval != yfcd.Interval.Days1 and is_f1_oldest_dt_recent:
# Yup, that's what happened
f[f1_oldest_idx:] = False
Expand Down
18 changes: 9 additions & 9 deletions yfinance_cache/yfc_ticker.py
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -109,7 +109,7 @@ def history(self,
raise Exception(f"Need to add mapping of exchange {exchange} to xcal (ticker={self._ticker})")
else:
raise
dt_now = pd.Timestamp.utcnow()
dt_now = pd.Timestamp.now('UTC')

# Type checks
if max_age is not None:
Expand Down Expand Up @@ -361,7 +361,7 @@ def _getExchangeAndTzAndListingDay(self):
exchange, tz_name, lday = None, None, None
i = None
try:
i = self.get_info('9999d')
i = self.get_info('9999D')
exchange = i['exchange']
if "exchangeTimezoneName" in i:
tz_name = i["exchangeTimezoneName"]
Expand Down Expand Up @@ -519,7 +519,7 @@ def _process_user_dt(self, dt):

def get_attribute(self, name, max_age=None, merge=False, metadata=False):
if max_age is None:
max_age = pd.Timedelta('365d')
max_age = pd.Timedelta('365D')
if not isinstance(max_age, (datetime.timedelta, pd.Timedelta)):
max_age = pd.Timedelta(max_age)
if max_age < pd.Timedelta(0):
Expand Down Expand Up @@ -665,15 +665,15 @@ def fast_info(self):

return self._fast_info

def get_shares(self, start=None, end=None, max_age='30d'):
def get_shares(self, start=None, end=None, max_age='30D'):
debug = False
# debug = True

max_age = pd.Timedelta(max_age)

# Process dates
exchange, tz, lday = self._getExchangeAndTzAndListingDay()
dt_now = pd.Timestamp.utcnow().tz_convert(tz)
dt_now = pd.Timestamp.now('UTC').tz_convert(tz)
if start is not None:
start_dt, start_d = self._process_user_dt(start)
start = start_d
Expand Down Expand Up @@ -704,7 +704,7 @@ def get_shares(self, start=None, end=None, max_age='30d'):
self._shares = self._fetch_shares(start, end)
if self._shares is None:
self._shares = pd.DataFrame()
yfcm.StoreCacheDatum(self._ticker, "shares", self._shares, metadata={'LastFetch':pd.Timestamp.utcnow().tz_convert(tz)})
yfcm.StoreCacheDatum(self._ticker, "shares", self._shares, metadata={'LastFetch':pd.Timestamp.now('UTC').tz_convert(tz)})
if self._shares.empty:
return None
else:
Expand All @@ -728,14 +728,14 @@ def get_shares(self, start=None, end=None, max_age='30d'):

if start < self._shares.index[0].date() and (not yfcm._option_manager.session.offline):
df_pre = self._fetch_shares(start, self._shares.index[0])
yfcm.WriteCacheMetadata(self._ticker, "shares", 'LastFetch', pd.Timestamp.utcnow().tz_convert(tz))
yfcm.WriteCacheMetadata(self._ticker, "shares", 'LastFetch', pd.Timestamp.now('UTC').tz_convert(tz))
if df_pre is not None:
self._shares = pd.concat([df_pre, self._shares])
if (end-td_1d) > self._shares.index[-1].date() and \
(end - self._shares.index[-1].date()) > max_age \
and (not yfcm._option_manager.session.offline):
df_post = self._fetch_shares(self._shares.index[-1] + td_1d, end)
yfcm.WriteCacheMetadata(self._ticker, "shares", 'LastFetch', pd.Timestamp.utcnow().tz_convert(tz))
yfcm.WriteCacheMetadata(self._ticker, "shares", 'LastFetch', pd.Timestamp.now('UTC').tz_convert(tz))
if df_post is not None:
self._shares = pd.concat([self._shares, df_post])

Expand Down Expand Up @@ -794,7 +794,7 @@ def _fetch_shares(self, start, end):
if df.empty:
return None

fetch_dt = pd.Timestamp.utcnow().tz_convert(tz)
fetch_dt = pd.Timestamp.now('UTC').tz_convert(tz)
df = pd.DataFrame(df, columns=['Shares'])

if start_d < df.index[0].date():
Expand Down
16 changes: 8 additions & 8 deletions yfinance_cache/yfc_time.py
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -238,8 +238,8 @@ def _customModSchedule(cal):
start = date(pre_range[0], 1, 1)
end = date(pre_range[1], 12, 31)
if exchange == 'CCC':
opens = pd.date_range(start=start, end=end, freq='1d').tz_localize(ZoneInfo(GetExchangeTzName(exchange)))
ends = opens + pd.Timedelta('1d')
opens = pd.date_range(start=start, end=end, freq='1D').tz_localize(ZoneInfo(GetExchangeTzName(exchange)))
ends = opens + pd.Timedelta('1D')
pre_cal = Simple247xcal(opens, ends)
else:
pre_cal = xcal.get_calendar(cal_name, start=start, end=end)
Expand All @@ -252,8 +252,8 @@ def _customModSchedule(cal):
start = date(post_range[0], 1, 1)
end = date(post_range[1], 12, 31)
if exchange == 'CCC':
opens = pd.date_range(start=start, end=end, freq='1d').tz_localize(ZoneInfo(GetExchangeTzName(exchange)))
ends = opens + pd.Timedelta('1d')
opens = pd.date_range(start=start, end=end, freq='1D').tz_localize(ZoneInfo(GetExchangeTzName(exchange)))
ends = opens + pd.Timedelta('1D')
post_cal = Simple247xcal(opens, ends)
else:
post_cal = xcal.get_calendar(cal_name, start=start, end=end)
Expand Down Expand Up @@ -417,7 +417,7 @@ def GetExchangeWeekSchedule(exchange, start, end, ignoreHolidays, ignoreWeekends
end_d = end
else:
end_d = end.astimezone(tz).date() + td_1d
dt_now = pd.Timestamp.utcnow().tz_convert(ZoneInfo("UTC"))
dt_now = pd.Timestamp.now('UTC').tz_convert(ZoneInfo("UTC"))
# td7d = timedelta(days=7)
td7d = pd.DateOffset(days=7)

Expand Down Expand Up @@ -534,7 +534,7 @@ def MapPeriodToDates(exchange, period, interval):

# Map period to start->end range so logic can intelligently fetch missing data
td_1d = timedelta(days=1)
dt_now = pd.Timestamp.utcnow().replace(tzinfo=ZoneInfo("UTC"))
dt_now = pd.Timestamp.now('UTC').replace(tzinfo=ZoneInfo("UTC"))
d_now = dt_now.astimezone(tz_exchange).date()
sched = GetExchangeSchedule(exchange, d_now-(7*td_1d), d_now+td_1d)
yf_lag = yfcd.exchangeToYfLag[exchange]
Expand Down Expand Up @@ -612,7 +612,7 @@ def GetExchangeScheduleIntervals(exchange, interval, start, end, discardTimes=No
yfc_logger.debug("GetExchangeScheduleIntervals()")
yfc_logger.debug("- " + str(locals()))

dt_now = pd.Timestamp.utcnow()
dt_now = pd.Timestamp.now('UTC')
tz = ZoneInfo(GetExchangeTzName(exchange))
td_1d = timedelta(days=1)
if not isinstance(start, datetime):
Expand Down Expand Up @@ -1795,7 +1795,7 @@ def IsPriceDatapointExpired(intervalStart, fetch_dt, repaired, max_age, exchange
if dt_now is not None:
yfcu.TypeCheckDatetime(dt_now, "dt_now")
else:
dt_now = pd.Timestamp.utcnow().tz_convert(ZoneInfo(GetExchangeTzName(exchange)))
dt_now = pd.Timestamp.now('UTC').tz_convert(ZoneInfo(GetExchangeTzName(exchange)))

if yf_lag is not None:
yfcu.TypeCheckTimedelta(yf_lag, "yf_lag")
Expand Down