""" Tests for offsets.BDay """ from __future__ import annotations from datetime import ( date, datetime, timedelta, ) import numpy as np import pytest from pandas._libs.tslibs import iNaT from pandas._libs.tslibs.offsets import BDay import pandas as pd import pandas._testing as tm from pandas.tests.tseries.offsets.common import ( assert_is_on_offset, assert_offset_equal, ) from pandas.tseries import offsets @pytest.fixture def dt(): return datetime(2008, 1, 1) @pytest.fixture def _offset(): return BDay @pytest.fixture def offset(_offset): return _offset() @pytest.fixture def offset2(_offset): return _offset(2) class TestBusinessDay: def test_different_normalize_equals(self, _offset, offset2): # GH#21404 changed __eq__ to return False when `normalize` does not match offset = _offset() offset2 = _offset(normalize=True) assert offset != offset2 def test_repr(self, offset, offset2): assert repr(offset) == "" assert repr(offset2) == "<2 * BusinessDays>" expected = "" assert repr(offset + timedelta(1)) == expected def test_with_offset(self, dt, offset): offset = offset + timedelta(hours=2) assert (dt + offset) == datetime(2008, 1, 2, 2) @pytest.mark.parametrize( "td", [ pd.Timedelta(hours=2), pd.Timedelta(hours=2).to_pytimedelta(), pd.Timedelta(hours=2).to_timedelta64(), ], ids=lambda x: type(x), ) def test_with_offset_index(self, td, dt, offset): dti = pd.DatetimeIndex([dt]) expected = pd.DatetimeIndex([datetime(2008, 1, 2, 2)]) result = dti + (td + offset) tm.assert_index_equal(result, expected) result = dti + (offset + td) tm.assert_index_equal(result, expected) def test_eq(self, offset2): assert offset2 == offset2 def test_hash(self, offset2): assert hash(offset2) == hash(offset2) def test_add_datetime(self, dt, offset2): assert offset2 + dt == datetime(2008, 1, 3) assert offset2 + np.datetime64("2008-01-01 00:00:00") == datetime(2008, 1, 3) def testRollback1(self, dt, _offset): assert _offset(10).rollback(dt) == dt def testRollback2(self, _offset): assert _offset(10).rollback(datetime(2008, 1, 5)) == datetime(2008, 1, 4) def testRollforward1(self, dt, _offset): assert _offset(10).rollforward(dt) == dt def testRollforward2(self, _offset): assert _offset(10).rollforward(datetime(2008, 1, 5)) == datetime(2008, 1, 7) def test_roll_date_object(self, offset): dt = date(2012, 9, 15) result = offset.rollback(dt) assert result == datetime(2012, 9, 14) result = offset.rollforward(dt) assert result == datetime(2012, 9, 17) offset = offsets.Day() result = offset.rollback(dt) assert result == datetime(2012, 9, 15) result = offset.rollforward(dt) assert result == datetime(2012, 9, 15) @pytest.mark.parametrize( "dt, expected", [ (datetime(2008, 1, 1), True), (datetime(2008, 1, 5), False), ], ) def test_is_on_offset(self, offset, dt, expected): assert_is_on_offset(offset, dt, expected) apply_cases: list[tuple[int, dict[datetime, datetime]]] = [ ( 1, { datetime(2008, 1, 1): datetime(2008, 1, 2), datetime(2008, 1, 4): datetime(2008, 1, 7), datetime(2008, 1, 5): datetime(2008, 1, 7), datetime(2008, 1, 6): datetime(2008, 1, 7), datetime(2008, 1, 7): datetime(2008, 1, 8), }, ), ( 2, { datetime(2008, 1, 1): datetime(2008, 1, 3), datetime(2008, 1, 4): datetime(2008, 1, 8), datetime(2008, 1, 5): datetime(2008, 1, 8), datetime(2008, 1, 6): datetime(2008, 1, 8), datetime(2008, 1, 7): datetime(2008, 1, 9), }, ), ( -1, { datetime(2008, 1, 1): datetime(2007, 12, 31), datetime(2008, 1, 4): datetime(2008, 1, 3), datetime(2008, 1, 5): datetime(2008, 1, 4), datetime(2008, 1, 6): datetime(2008, 1, 4), datetime(2008, 1, 7): datetime(2008, 1, 4), datetime(2008, 1, 8): datetime(2008, 1, 7), }, ), ( -2, { datetime(2008, 1, 1): datetime(2007, 12, 28), datetime(2008, 1, 4): datetime(2008, 1, 2), datetime(2008, 1, 5): datetime(2008, 1, 3), datetime(2008, 1, 6): datetime(2008, 1, 3), datetime(2008, 1, 7): datetime(2008, 1, 3), datetime(2008, 1, 8): datetime(2008, 1, 4), datetime(2008, 1, 9): datetime(2008, 1, 7), }, ), ( 0, { datetime(2008, 1, 1): datetime(2008, 1, 1), datetime(2008, 1, 4): datetime(2008, 1, 4), datetime(2008, 1, 5): datetime(2008, 1, 7), datetime(2008, 1, 6): datetime(2008, 1, 7), datetime(2008, 1, 7): datetime(2008, 1, 7), }, ), ] @pytest.mark.parametrize("case", apply_cases) def test_apply(self, case, _offset): n, cases = case offset = _offset(n) for base, expected in cases.items(): assert_offset_equal(offset, base, expected) def test_apply_large_n(self, _offset): dt = datetime(2012, 10, 23) result = dt + _offset(10) assert result == datetime(2012, 11, 6) result = dt + _offset(100) - _offset(100) assert result == dt off = _offset() * 6 rs = datetime(2012, 1, 1) - off xp = datetime(2011, 12, 23) assert rs == xp st = datetime(2011, 12, 18) rs = st + off xp = datetime(2011, 12, 26) assert rs == xp off = _offset() * 10 rs = datetime(2014, 1, 5) + off # see #5890 xp = datetime(2014, 1, 17) assert rs == xp def test_apply_array_lands_on_nat_sentinel(): # GH#66552 the sum fits in int64 but *is* iNaT, so storing it would be # indistinguishable from a missing value dti = pd.DatetimeIndex([pd.Timestamp(iNaT + 86400 * 10**9)]) assert dti[0].weekday() == 2 with pytest.raises(OverflowError, match="Overflow in int64 addition"): dti + BDay(-1) def test_apply_array_out_of_bounds(): # GH#66552 the array path wrapped where the scalar path raises dti = pd.DatetimeIndex(np.array([946857600 * 10**9], dtype="M8[ns]")) assert dti[0].weekday() == 0 with pytest.raises(OverflowError, match="Overflow in int64 addition"): dti + BDay(2**31 - 1) def test_apply_array_large_n(): # GH#66549 n was held in a C int, so a multiple of 2**32 was a no-op dti = pd.DatetimeIndex(np.array([946857600], dtype="M8[s]")) assert dti[0].weekday() == 0 result = dti + BDay(2**32) # 2**32 business days from a Monday is 2**32 // 5 whole weeks plus the # remaining 1 day shift = 7 * (2**32 // 5) + 1 expected = pd.DatetimeIndex(np.array([946857600 + shift * 86400], dtype="M8[s]")) tm.assert_index_equal(result, expected) def test_apply_array_preserves_nat(): dti = pd.DatetimeIndex([None, "2000-01-03"]) result = dti + BDay(1) expected = pd.DatetimeIndex([None, "2000-01-04"]) tm.assert_index_equal(result, expected)