""" Helper functions to generate range-like data for DatetimeArray (and possibly TimedeltaArray/PeriodArray) """ from typing import Tuple import numpy as np from pandas._libs.tslibs import OutOfBoundsDatetime, Timestamp from pandas.tseries.offsets import DateOffset, Tick, generate_range def generate_regular_range( start: Timestamp, end: Timestamp, periods: int, freq: DateOffset ) -> Tuple[np.ndarray, str]: """ Generate a range of dates with the spans between dates described by the given `freq` DateOffset. Parameters ---------- start : Timestamp or None first point of produced date range end : Timestamp or None last point of produced date range periods : int number of periods in produced date range freq : DateOffset describes space between dates in produced date range Returns ------- ndarray[np.int64] representing nanosecond unix timestamps """ if isinstance(freq, Tick): stride = freq.nanos if periods is None: b = Timestamp(start).value # cannot just use e = Timestamp(end) + 1 because arange breaks when # stride is too large, see GH10887 e = b + (Timestamp(end).value - b) // stride * stride + stride // 2 + 1 # end.tz == start.tz by this point due to _generate implementation tz = start.tz elif start is not None: b = Timestamp(start).value e = _generate_range_overflow_safe(b, periods, stride, side="start") tz = start.tz elif end is not None: e = Timestamp(end).value + stride b = _generate_range_overflow_safe(e, periods, stride, side="end") tz = end.tz else: raise ValueError( "at least 'start' or 'end' should be specified " "if a 'period' is given." ) with np.errstate(over="raise"): # If the range is sufficiently large, np.arange may overflow # and incorrectly return an empty array if not caught. try: values = np.arange(b, e, stride, dtype=np.int64) except FloatingPointError: xdr = [b] while xdr[-1] != e: xdr.append(xdr[-1] + stride) values = np.array(xdr[:-1], dtype=np.int64) else: tz = None # start and end should have the same timezone by this point if start is not None: tz = start.tz elif end is not None: tz = end.tz xdr = generate_range(start=start, end=end, periods=periods, offset=freq) values = np.array([x.value for x in xdr], dtype=np.int64) return values, tz def _generate_range_overflow_safe( endpoint: int, periods: int, stride: int, side: str = "start" ) -> int: """ Calculate the second endpoint for passing to np.arange, checking to avoid an integer overflow. Catch OverflowError and re-raise as OutOfBoundsDatetime. Parameters ---------- endpoint : int nanosecond timestamp of the known endpoint of the desired range periods : int number of periods in the desired range stride : int nanoseconds between periods in the desired range side : {'start', 'end'} which end of the range `endpoint` refers to Returns ------- other_end : int Raises ------ OutOfBoundsDatetime """ # GH#14187 raise instead of incorrectly wrapping around assert side in ["start", "end"] i64max = np.uint64(np.iinfo(np.int64).max) msg = f"Cannot generate range with {side}={endpoint} and periods={periods}" with np.errstate(over="raise"): # if periods * strides cannot be multiplied within the *uint64* bounds, # we cannot salvage the operation by recursing, so raise try: addend = np.uint64(periods) * np.uint64(np.abs(stride)) except FloatingPointError: raise OutOfBoundsDatetime(msg) if np.abs(addend) <= i64max: # relatively easy case without casting concerns return _generate_range_overflow_safe_signed(endpoint, periods, stride, side) elif (endpoint > 0 and side == "start" and stride > 0) or ( endpoint < 0 and side == "end" and stride > 0 ): # no chance of not-overflowing raise OutOfBoundsDatetime(msg) elif side == "end" and endpoint > i64max and endpoint - stride <= i64max: # in _generate_regular_range we added `stride` thereby overflowing # the bounds. Adjust to fix this. return _generate_range_overflow_safe( endpoint - stride, periods - 1, stride, side ) # split into smaller pieces mid_periods = periods // 2 remaining = periods - mid_periods assert 0 < remaining < periods, (remaining, periods, endpoint, stride) midpoint = _generate_range_overflow_safe(endpoint, mid_periods, stride, side) return _generate_range_overflow_safe(midpoint, remaining, stride, side) def _generate_range_overflow_safe_signed( endpoint: int, periods: int, stride: int, side: str ) -> int: """ A special case for _generate_range_overflow_safe where `periods * stride` can be calculated without overflowing int64 bounds. """ assert side in ["start", "end"] if side == "end": stride *= -1 with np.errstate(over="raise"): addend = np.int64(periods) * np.int64(stride) try: # easy case with no overflows return np.int64(endpoint) + addend except (FloatingPointError, OverflowError): # with endpoint negative and addend positive we risk # FloatingPointError; with reversed signed we risk OverflowError pass # if stride and endpoint had opposite signs, then endpoint + addend # should never overflow. so they must have the same signs assert (stride > 0 and endpoint >= 0) or (stride < 0 and endpoint <= 0) if stride > 0: # watch out for very special case in which we just slightly # exceed implementation bounds, but when passing the result to # np.arange will get a result slightly within the bounds result = np.uint64(endpoint) + np.uint64(addend) i64max = np.uint64(np.iinfo(np.int64).max) assert result > i64max if result <= i64max + np.uint64(stride): return result raise OutOfBoundsDatetime( f"Cannot generate range with {side}={endpoint} and periods={periods}" )