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CLN+TST: Catch specific exception in equals #28532

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Merged
merged 3 commits into from
Sep 26, 2019
Merged

CLN+TST: Catch specific exception in equals #28532

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CLN+TST: Catch specific exception in equals
jbrockmendel Sep 19, 2019
b4bf3d4
Merge branch 'master' of https://github.com/pandas-dev/pandas into fa…
jbrockmendel Sep 19, 2019
2a13ee8
Raise correct exception on MultiIndex
jbrockmendel Sep 19, 2019
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3 changes: 3 additions & 0 deletions pandas/core/arrays/datetimes.py
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Expand Up @@ -1918,6 +1918,9 @@ def sequence_to_dt64ns(
tz = validate_tz_from_dtype(dtype, tz)

if isinstance(data, ABCIndexClass):
if data.nlevels > 1:
# Without this check, data._data below is None
raise TypeError("Cannot create a DatetimeArray from a MultiIndex.")
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we should have an index method which does this no?

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For the check or the raising? The check could be isinstance(data, ABCMultiIndex). No strong preference.

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no, something that does the right thing on an Index/MultiIndex, e.g. that gets (data._data) on an index and just passes thru on a MI

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I think we want to move to use the extract_array pattern here, but that currently raises ValueError on MultiIndex (where we want to raise TypeError here)

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ok the reason I am harping on this is its an inconsistency between Index and MultiIndex. ok on merging this and creating an issue / followup ?

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creating an issue / followup ?

yes

data = data._data

# By this point we are assured to have either a numpy array or Index
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6 changes: 5 additions & 1 deletion pandas/core/indexes/datetimelike.py
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Expand Up @@ -192,7 +192,11 @@ def equals(self, other):
elif not isinstance(other, type(self)):
try:
other = type(self)(other)
except Exception:
except (ValueError, TypeError, OverflowError):
# e.g.
# ValueError -> cannot parse str entry, or OutOfBoundsDatetime
# TypeError -> trying to convert IntervalIndex to DatetimeIndex
# OverflowError -> Index([very_large_timedeltas])
return False

if not is_dtype_equal(self.dtype, other.dtype):
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5 changes: 5 additions & 0 deletions pandas/tests/arrays/test_datetimes.py
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Expand Up @@ -15,6 +15,11 @@


class TestDatetimeArrayConstructor:
def test_from_sequence_invalid_type(self):
mi = pd.MultiIndex.from_product([np.arange(5), np.arange(5)])
with pytest.raises(TypeError, match="Cannot create a DatetimeArray"):
DatetimeArray._from_sequence(mi)

def test_only_1dim_accepted(self):
arr = np.array([0, 1, 2, 3], dtype="M8[h]").astype("M8[ns]")

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12 changes: 12 additions & 0 deletions pandas/tests/indexes/datetimes/test_ops.py
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Expand Up @@ -393,6 +393,18 @@ def test_equals(self):
assert not idx.equals(list(idx3))
assert not idx.equals(pd.Series(idx3))

# check that we do not raise when comparing with OutOfBounds objects
oob = pd.Index([datetime(2500, 1, 1)] * 3, dtype=object)
assert not idx.equals(oob)
assert not idx2.equals(oob)
assert not idx3.equals(oob)

# check that we do not raise when comparing with OutOfBounds dt64
oob2 = oob.map(np.datetime64)
assert not idx.equals(oob2)
assert not idx2.equals(oob2)
assert not idx3.equals(oob2)

@pytest.mark.parametrize("values", [["20180101", "20180103", "20180105"], []])
@pytest.mark.parametrize("freq", ["2D", Day(2), "2B", BDay(2), "48H", Hour(48)])
@pytest.mark.parametrize("tz", [None, "US/Eastern"])
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13 changes: 13 additions & 0 deletions pandas/tests/indexes/timedeltas/test_ops.py
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@@ -1,3 +1,5 @@
from datetime import timedelta

import numpy as np
import pytest

Expand Down Expand Up @@ -266,6 +268,17 @@ def test_equals(self):
assert not idx.equals(list(idx2))
assert not idx.equals(pd.Series(idx2))

# Check that we dont raise OverflowError on comparisons outside the
# implementation range
oob = pd.Index([timedelta(days=10 ** 6)] * 3, dtype=object)
assert not idx.equals(oob)
assert not idx2.equals(oob)

# FIXME: oob.apply(np.timedelta64) incorrectly overflows
oob2 = pd.Index([np.timedelta64(x) for x in oob], dtype=object)
assert not idx.equals(oob2)
assert not idx2.equals(oob2)

@pytest.mark.parametrize("values", [["0 days", "2 days", "4 days"], []])
@pytest.mark.parametrize("freq", ["2D", Day(2), "48H", Hour(48)])
def test_freq_setter(self, values, freq):
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