Fix pandas 2.2. deprecation warnings

Fixes pandas 2.2 deprecation warnings concerning deprecation of frequency units "T", "H" and "S" in favor of "min", "h" and "s".

README.md

@@ -47,7 +47,7 @@ The above call was made 21 minutes after the NYSE open. Notice that the call ret
 Any interval can be evaluated (limited only by the availability of underlying data).
 ```python
 >>> # prices over a specific session at 68 minute intervals
->>> prices.get("68T", start="2022-06-27", end="2022-06-27", force=True)
+>>> prices.get("68min", start="2022-06-27", end="2022-06-27", force=True)
 ```
 ```
 symbol                                            MSFT
@@ -108,7 +108,7 @@ Although some indices are longer than three calendar days, they all comprise of
 )
 >>> # lead_symbol determines the exchange against which the period will be evaluated and
 >>> # the default output time zone (which for Bitcoin is UTC).
->>> prices_mult.get("90T", hours=9, lead_symbol="BTC-USD")
+>>> prices_mult.get("90min", hours=9, lead_symbol="BTC-USD")
 ```
 ```
 symbol                                            MSFT                                                    9988.HK                                                       BTC-USD
@@ -127,7 +127,7 @@ By default prices are shown as missing when the exchange is closed (the time zon
 The `get` method has plenty of options to customize the output, including `fill` to fill in indices when an exchange is closed...
 ```python
 >>> # as before, only now filling in prices when exchanges are closed
->>> prices_mult.get("90T", hours=9, lead_symbol="BTC-USD", fill="both")
+>>> prices_mult.get("90min", hours=9, lead_symbol="BTC-USD", fill="both")
 ```
 ```
 symbol                                            MSFT                                                    9988.HK                                                       BTC-USD

src/market_prices/data.py

@@ -659,7 +659,7 @@ def _requested_dates_adjust(self, dr: DateRangeReq) -> DateRangeReq | None:
         elif self.bi.is_intraday:
             assert self._delay is not None
             # ten minutes to cover provider delays in publishing data.
-            rerequest_from = helpers.now() - self._delay - pd.Timedelta(10, "T")
+            rerequest_from = helpers.now() - self._delay - pd.Timedelta(10, "min")
             if end < rerequest_from:
                 return dr
             excess = end - rerequest_from

src/market_prices/daterange.py

@@ -866,7 +866,7 @@ def end_now(self) -> tuple[pd.Timestamp, pd.Timestamp]:
         # which the end is accurate as at the moment the end is requested.
         # (without the + one minute would be ignoring those price that have
         # come in since the current minute started.)
-        end_accuracy = min(end_accuracy, now + pd.Timedelta("1T"))
+        end_accuracy = min(end_accuracy, now + pd.Timedelta("1min"))
         return end, end_accuracy
 
     def _trading_index(
@@ -1055,7 +1055,7 @@ def _offset_days(self, ts: pd.Timestamp, days: int) -> pd.Timestamp:
 
         # "previous" to cover ts as close (not a trading minute).
         session = self.cal.minute_to_session(ts, "previous")
-        schedule_vals = self.cal.schedule.loc[session].dropna().view(np.int64).values
+        schedule_vals = self.cal.schedule.loc[session].dropna().astype(np.int64).values
         if ts.value in schedule_vals:
             target_i = self.cal.sessions.get_loc(session) + days
 
@@ -1199,7 +1199,7 @@ def daterange(self) -> tuple[mptypes.DateRange, pd.Timestamp]:
             if intraday_duration:
                 if intraday_duration < self.final_interval.as_minutes:
                     raise errors.PricesUnavailableIntervalDurationError(
-                        pd.Timedelta(intraday_duration, "T"), self
+                        pd.Timedelta(intraday_duration, "min"), self
                     )
                 if start is None:
                     end_ = end
@@ -1269,7 +1269,7 @@ def daterange(self) -> tuple[mptypes.DateRange, pd.Timestamp]:
             else:
                 minutes = calutils.minutes_in_period(self.cal, start, end_)
             if self.final_interval.as_minutes > minutes:
-                period_duration = pd.Timedelta(minutes, "T")
+                period_duration = pd.Timedelta(minutes, "min")
                 raise errors.PricesUnavailableIntervalPeriodError(
                     self, start, end_, period_duration
                 )

src/market_prices/errors.py

@@ -872,10 +872,10 @@ class PricesMissingWarning(PricesWarning):
 
     def __init__(self, symbol: str, bi: BI, sessions: pd.DatetimeIndex, source: str):
         date_format = "%Y-%m-%d"
-        sessions = sessions.format(date_format=date_format)
+        sessions_ = sessions.strftime(date_format).tolist()
         self._msg = (
             f"Prices from {source} are missing for '{symbol}' at the"
-            f" base interval '{bi}' for the following sessions: {sessions}."
+            f" base interval '{bi}' for the following sessions: {sessions_}."
         )
 
 

src/market_prices/helpers.py

@@ -23,8 +23,8 @@
 UTC = zoneinfo.ZoneInfo("UTC")
 
 ONE_DAY: pd.Timedelta = pd.Timedelta(1, "D")
-ONE_MIN: pd.Timedelta = pd.Timedelta(1, "T")
-ONE_SEC: pd.Timedelta = pd.Timedelta(1, "S")
+ONE_MIN: pd.Timedelta = pd.Timedelta(1, "min")
+ONE_SEC: pd.Timedelta = pd.Timedelta(1, "s")
 
 
 def symbols_to_list(symbols: mptypes.Symbols) -> list[str]:
@@ -155,7 +155,7 @@ def now(
         now_ = now_.tz_convert(None)
         res = "D"
     else:
-        res = "T"
+        res = "min"
     return now_.ceil(res) if side == "right" else now_.floor(res)
 
 
@@ -172,7 +172,7 @@ def extract_freq_parts(freq: str) -> tuple[int, str]:
     Parameters
     ----------
     freq
-        Pandas frequency, for example "5D", "30T", "4H", "33MS".
+        Pandas frequency, for example "5D", "30min", "4h", "33MS".
 
     Raises
     ------
@@ -192,8 +192,8 @@ def extract_freq_parts(freq: str) -> tuple[int, str]:
 
     Examples
     --------
-    >>> extract_freq_parts("22T")
-    (22, 'T')
+    >>> extract_freq_parts("22min")
+    (22, 'min')
     >>> extract_freq_parts("1m")
     (1, 'm')
     >>> extract_freq_parts("D")

src/market_prices/intervals.py

@@ -51,10 +51,10 @@ def as_pdtd(self) -> pd.Timedelta:
         return pd.Timedelta(self)
 
     @property
-    def freq_unit(self) -> typing.Literal["T", "H", "D"]:
+    def freq_unit(self) -> typing.Literal["min", "h", "D"]:
         """Return unit of pandas frequency represented by the member.
 
-        Returns either "T", "H" or "D".
+        Returns either "min", "h" or "D".
         """
         return self.as_pdtd.resolution_string
 
@@ -64,7 +64,7 @@ def freq_value(self) -> int:
         components = self.as_pdtd.components
         if self.freq_unit == "D":
             return components.days
-        elif self.freq_unit == "H":
+        elif self.freq_unit == "h":
             return components.hours
         else:
             return components.minutes + (components.hours * 60)
@@ -74,7 +74,7 @@ def is_intraday(self) -> bool:
         """Query if a member represents an intraday interval.
 
         An interval is considered to be intraday if it is shorter than one
-        day. The unit of intraday intervals will be either "T" or "H".
+        day. The unit of intraday intervals will be either "min" or "h".
         """
         return self < helpers.ONE_DAY
 
@@ -126,7 +126,7 @@ def as_offset(
         calendar
             Calendar against which to evaluate custom business day for
             intervals with `self.freq_unit` as "D". Not required for
-            intervals with `self.freq_unit` as "T" or "H".
+            intervals with `self.freq_unit` as "min" or "h".
 
         one_less
             If `self.freq_unit` is "D" then:
@@ -260,7 +260,7 @@ def is_intraday(self) -> bool:
         """Query if a member represents an intraday interval.
 
         An interval is considered to be intraday if it is shorter than one
-        day. The unit of intraday intervals will be either "T" or "H".
+        day. The unit of intraday intervals will be either "min" or "h".
         """
         return False
 
@@ -376,9 +376,9 @@ def create_base_intervals_enum(intervals: list[TDInterval]) -> _BaseInterval:
     for intrvl in intervals:
         unit, value = intrvl.freq_unit, intrvl.freq_value
         td_args: tuple
-        if unit == "T":
+        if unit == "min":
             td_args = (0, 0, 0, 0, value)
-        elif unit == "H":
+        elif unit == "h":
             td_args = (0, 0, 0, 0, 0, value)
         else:
             if intrvl is not TDInterval.D1:
@@ -432,6 +432,8 @@ def to_ptinterval(interval: str | timedelta | pd.Timedelta) -> PTInterval:
                 f"`interval` unit must by one of {valid_units} (or lower-"
                 f"case) although evaluated to '{unit}'."
             )
+        if unit == "MIN":
+            unit = "T"
 
     else:
         if interval <= timedelta(0):
@@ -448,7 +450,7 @@ def to_ptinterval(interval: str | timedelta | pd.Timedelta) -> PTInterval:
             ' example "1m" for one month.'
         )
 
-        valid_resolutions = ["T", "H", "D"]
+        valid_resolutions = ["min", "h", "D"]
         if interval.resolution_string not in valid_resolutions:
             raise ValueError(error_msg)
 
@@ -476,8 +478,7 @@ def raise_value_oob_error(component: str, limit: int):
     }
 
     if isinstance(interval, str):
-        if unit == "MIN":
-            unit = "T"
+
         if value > limits[unit]:
             raise_value_oob_error(components[unit], limits[unit])
         if unit == "T" and not value % 60:
@@ -487,10 +488,12 @@ def raise_value_oob_error(component: str, limit: int):
 
     else:
         unit = interval.resolution_string
-        if unit == "T":
+        if unit in ["min", "T"]:  # "T" for compatibility pandas < 2.2
             value = int(interval.total_seconds() // 60)
-        elif unit == "H":
+            unit = "T"
+        elif unit in ["h", "H"]:  # "H" for compatibility pandas < 2.2
             value = int(interval.total_seconds() // 3600)
+            unit = "H"
         else:
             value = interval.days
 

src/market_prices/parsing.py

@@ -200,12 +200,12 @@ def _parse_start_end(
         start_is_date = helpers.is_date(start)
         if not start_is_date:
             # do not include any incomplete minute
-            start = start.ceil("T")
+            start = start.ceil("min")
     if end is not None:
         end_is_date = helpers.is_date(end)
         if not end_is_date:
             # do not include incomplete minute
-            end = end.floor("T")
+            end = end.floor("min")
         # if end > now, set to None.
         now_interval = intervals.ONE_DAY if end_is_date else intervals.ONE_MIN
         now = helpers.now(now_interval, "left")

src/market_prices/prices/base.py

@@ -1123,7 +1123,7 @@ def lead_symbol_default(self) -> str:
 
     def _set_delays(self, delays: int | list[int] | dict[str, int]):
         d = self._dict_for_all_symbols("delays", delays)
-        self._delays = {k: pd.Timedelta(v, "T") for k, v in d.items()}
+        self._delays = {k: pd.Timedelta(v, "min") for k, v in d.items()}
 
     @property
     def delays(self) -> dict[str, pd.Timedelta]:
@@ -1640,8 +1640,8 @@ def _set_indices_aligned(self):
 
             index = self._trading_indexes[bi]
             nano_index = index.left.asi8
-            opens = self.cc.opens[slc].view("int64")
-            closes = self.cc.closes[slc].view("int64")
+            opens = self.cc.opens[slc].astype("int64")
+            closes = self.cc.closes[slc].astype("int64")
 
             sessions = opens.index
             srs = pd.Series(True, index=sessions)
@@ -3444,20 +3444,20 @@ def get(
                     value:
                         one or more digits.
                     unit:
-                        "min", "t", "MIN" or "T" for minutes
+                        "min", "MIN", "T" or "t" for minutes
                         "h" or "H" for hours
                         "d" or "D' for days
                         'm' or "M" for months
 
             Examples:
                 thirty minutes:
                     "30min", "30T"
-                    pd.Timedelta(30, "T"), pd.Timedelta(minutes=30)
+                    pd.Timedelta(30, "min"), pd.Timedelta(minutes=30)
                     timedelta(minutes=30)
 
                 three hours:
                     "3h", "3H"
-                    pd.Timedelta(3, "H"), pd.Timedelta(hours=3)
+                    pd.Timedelta(3, "h"), pd.Timedelta(hours=3)
                     timedelta(hours=3)
 
                 one day:
@@ -3854,8 +3854,8 @@ def get(
                     greater than the interval although the indice bounds
                     they evaluate to do not. For example, if a session
                     opens at 09.00, `start` is 09.01 and `end` is 09.09
-                    then a call for data at a "5T" `interval` will evalute
-                    the period bounds as from 09.05 through 09.05.
+                    then a call for data at a "5min" `interval` will
+                    evalute the period bounds as from 09.05 through 09.05.
 
                 errors.PricesUnavailableDOIntervalPeriodError:
                     Monthly `interval` is longer than the evaluated period.

src/market_prices/prices/yahoo.py

@@ -560,7 +560,7 @@ def _set_daily_bi_limit(self):
     @staticmethod
     def _bi_to_source_key(interval: intervals.BI) -> str:
         """Map interval to value for source's interval parameter."""
-        if interval.freq_unit == "T":
+        if interval.freq_unit == "min":
             return str(interval.freq_value) + "m"
         else:
             return interval.as_pdfreq.lower()  # as yahooquery value
@@ -868,6 +868,6 @@ def _request_data(
                 # 22 hours ensures markets opening in Americas included
                 # whilst avoiding including the following session of
                 # Australasian markets
-                end_ += pd.Timedelta(22, "H")
+                end_ += pd.Timedelta(22, "h")
             prices = self._request_yahoo(interval=interval, start=start, end=end_)
         return self._tidy_yahoo(prices, interval, start, end)