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Fix cases of inconsistent namespacing in tests #37842

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Nov 15, 2020
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Fix cases of inconsistent namespacing in tests #37842

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128 changes: 63 additions & 65 deletions pandas/tests/arithmetic/test_period.py
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2 changes: 1 addition & 1 deletion pandas/tests/arrays/floating/test_construction.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,7 @@


def test_uses_pandas_na():
a = pd.array([1, None], dtype=pd.Float64Dtype())
a = pd.array([1, None], dtype=Float64Dtype())
assert a[1] is pd.NA


Expand Down
4 changes: 2 additions & 2 deletions pandas/tests/arrays/sparse/test_dtype.py
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Original file line number Diff line number Diff line change
Expand Up @@ -200,10 +200,10 @@ def test_update_dtype_raises(original, dtype, expected_error_msg):

def test_repr():
# GH-34352
result = str(pd.SparseDtype("int64", fill_value=0))
result = str(SparseDtype("int64", fill_value=0))
expected = "Sparse[int64, 0]"
assert result == expected

result = str(pd.SparseDtype(object, fill_value="0"))
result = str(SparseDtype(object, fill_value="0"))
expected = "Sparse[object, '0']"
assert result == expected
48 changes: 24 additions & 24 deletions pandas/tests/arrays/test_datetimelike.py
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Original file line number Diff line number Diff line change
Expand Up @@ -31,7 +31,7 @@ def period_index(freqstr):
the PeriodIndex behavior.
"""
# TODO: non-monotone indexes; NaTs, different start dates
pi = pd.period_range(start=pd.Timestamp("2000-01-01"), periods=100, freq=freqstr)
pi = pd.period_range(start=Timestamp("2000-01-01"), periods=100, freq=freqstr)
return pi


Expand All @@ -45,7 +45,7 @@ def datetime_index(freqstr):
the DatetimeIndex behavior.
"""
# TODO: non-monotone indexes; NaTs, different start dates, timezones
dti = pd.date_range(start=pd.Timestamp("2000-01-01"), periods=100, freq=freqstr)
dti = pd.date_range(start=Timestamp("2000-01-01"), periods=100, freq=freqstr)
return dti


Expand All @@ -58,7 +58,7 @@ def timedelta_index():
the TimedeltaIndex behavior.
"""
# TODO: flesh this out
return pd.TimedeltaIndex(["1 Day", "3 Hours", "NaT"])
return TimedeltaIndex(["1 Day", "3 Hours", "NaT"])


class SharedTests:
Expand Down Expand Up @@ -139,7 +139,7 @@ def test_take(self):

tm.assert_index_equal(self.index_cls(result), expected)

@pytest.mark.parametrize("fill_value", [2, 2.0, pd.Timestamp.now().time])
@pytest.mark.parametrize("fill_value", [2, 2.0, Timestamp.now().time])
def test_take_fill_raises(self, fill_value):
data = np.arange(10, dtype="i8") * 24 * 3600 * 10 ** 9

Expand Down Expand Up @@ -539,7 +539,7 @@ def test_median(self, arr1d):
class TestDatetimeArray(SharedTests):
index_cls = pd.DatetimeIndex
array_cls = DatetimeArray
dtype = pd.Timestamp
dtype = Timestamp

@pytest.fixture
def arr1d(self, tz_naive_fixture, freqstr):
Expand Down Expand Up @@ -741,7 +741,7 @@ def test_take_fill_valid(self, arr1d):
arr = arr1d
dti = self.index_cls(arr1d)

now = pd.Timestamp.now().tz_localize(dti.tz)
now = Timestamp.now().tz_localize(dti.tz)
result = arr.take([-1, 1], allow_fill=True, fill_value=now)
assert result[0] == now

Expand All @@ -752,10 +752,10 @@ def test_take_fill_valid(self, arr1d):

with pytest.raises(TypeError, match=msg):
# fill_value Period invalid
arr.take([-1, 1], allow_fill=True, fill_value=pd.Period("2014Q1"))
arr.take([-1, 1], allow_fill=True, fill_value=Period("2014Q1"))

tz = None if dti.tz is not None else "US/Eastern"
now = pd.Timestamp.now().tz_localize(tz)
now = Timestamp.now().tz_localize(tz)
msg = "Cannot compare tz-naive and tz-aware datetime-like objects"
with pytest.raises(TypeError, match=msg):
# Timestamp with mismatched tz-awareness
Expand Down Expand Up @@ -828,22 +828,22 @@ def test_strftime_nat(self):


class TestTimedeltaArray(SharedTests):
index_cls = pd.TimedeltaIndex
index_cls = TimedeltaIndex
array_cls = TimedeltaArray
dtype = pd.Timedelta

def test_from_tdi(self):
tdi = pd.TimedeltaIndex(["1 Day", "3 Hours"])
tdi = TimedeltaIndex(["1 Day", "3 Hours"])
arr = TimedeltaArray(tdi)
assert list(arr) == list(tdi)

# Check that Index.__new__ knows what to do with TimedeltaArray
tdi2 = pd.Index(arr)
assert isinstance(tdi2, pd.TimedeltaIndex)
assert isinstance(tdi2, TimedeltaIndex)
assert list(tdi2) == list(arr)

def test_astype_object(self):
tdi = pd.TimedeltaIndex(["1 Day", "3 Hours"])
tdi = TimedeltaIndex(["1 Day", "3 Hours"])
arr = TimedeltaArray(tdi)
asobj = arr.astype("O")
assert isinstance(asobj, np.ndarray)
Expand All @@ -868,7 +868,7 @@ def test_total_seconds(self, timedelta_index):

tm.assert_numpy_array_equal(result, expected.values)

@pytest.mark.parametrize("propname", pd.TimedeltaIndex._field_ops)
@pytest.mark.parametrize("propname", TimedeltaIndex._field_ops)
def test_int_properties(self, timedelta_index, propname):
tdi = timedelta_index
arr = TimedeltaArray(tdi)
Expand Down Expand Up @@ -928,7 +928,7 @@ def test_take_fill_valid(self, timedelta_index):
result = arr.take([-1, 1], allow_fill=True, fill_value=td1)
assert result[0] == td1

now = pd.Timestamp.now()
now = Timestamp.now()
value = now
msg = f"value should be a '{arr._scalar_type.__name__}' or 'NaT'. Got"
with pytest.raises(TypeError, match=msg):
Expand All @@ -947,9 +947,9 @@ def test_take_fill_valid(self, timedelta_index):


class TestPeriodArray(SharedTests):
index_cls = pd.PeriodIndex
index_cls = PeriodIndex
array_cls = PeriodArray
dtype = pd.Period
dtype = Period

@pytest.fixture
def arr1d(self, period_index):
Expand All @@ -962,7 +962,7 @@ def test_from_pi(self, arr1d):

# Check that Index.__new__ knows what to do with PeriodArray
pi2 = pd.Index(arr)
assert isinstance(pi2, pd.PeriodIndex)
assert isinstance(pi2, PeriodIndex)
assert list(pi2) == list(arr)

def test_astype_object(self, arr1d):
Expand Down Expand Up @@ -1075,7 +1075,7 @@ def test_strftime_nat(self):
"array,casting_nats",
[
(
pd.TimedeltaIndex(["1 Day", "3 Hours", "NaT"])._data,
TimedeltaIndex(["1 Day", "3 Hours", "NaT"])._data,
(pd.NaT, np.timedelta64("NaT", "ns")),
),
(
Expand All @@ -1099,7 +1099,7 @@ def test_casting_nat_setitem_array(array, casting_nats):
"array,non_casting_nats",
[
(
pd.TimedeltaIndex(["1 Day", "3 Hours", "NaT"])._data,
TimedeltaIndex(["1 Day", "3 Hours", "NaT"])._data,
(np.datetime64("NaT", "ns"), pd.NaT.value),
),
(
Expand Down Expand Up @@ -1164,8 +1164,8 @@ def test_to_numpy_extra(array):
"values",
[
pd.to_datetime(["2020-01-01", "2020-02-01"]),
pd.TimedeltaIndex([1, 2], unit="D"),
pd.PeriodIndex(["2020-01-01", "2020-02-01"], freq="D"),
TimedeltaIndex([1, 2], unit="D"),
PeriodIndex(["2020-01-01", "2020-02-01"], freq="D"),
],
)
@pytest.mark.parametrize(
Expand Down Expand Up @@ -1195,12 +1195,12 @@ def test_searchsorted_datetimelike_with_listlike(values, klass, as_index):
"values",
[
pd.to_datetime(["2020-01-01", "2020-02-01"]),
pd.TimedeltaIndex([1, 2], unit="D"),
pd.PeriodIndex(["2020-01-01", "2020-02-01"], freq="D"),
TimedeltaIndex([1, 2], unit="D"),
PeriodIndex(["2020-01-01", "2020-02-01"], freq="D"),
],
)
@pytest.mark.parametrize(
"arg", [[1, 2], ["a", "b"], [pd.Timestamp("2020-01-01", tz="Europe/London")] * 2]
"arg", [[1, 2], ["a", "b"], [Timestamp("2020-01-01", tz="Europe/London")] * 2]
)
def test_searchsorted_datetimelike_with_listlike_invalid_dtype(values, arg):
# https://github.com/pandas-dev/pandas/issues/32762
Expand Down
26 changes: 13 additions & 13 deletions pandas/tests/indexes/categorical/test_formats.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,18 +3,18 @@
"""
import pandas._config.config as cf

import pandas as pd
from pandas import CategoricalIndex
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this is because "CategoricalIndex" appears in some strings already



class TestCategoricalIndexRepr:
def test_string_categorical_index_repr(self):
# short
idx = pd.CategoricalIndex(["a", "bb", "ccc"])
idx = CategoricalIndex(["a", "bb", "ccc"])
expected = """CategoricalIndex(['a', 'bb', 'ccc'], categories=['a', 'bb', 'ccc'], ordered=False, dtype='category')""" # noqa
assert repr(idx) == expected

# multiple lines
idx = pd.CategoricalIndex(["a", "bb", "ccc"] * 10)
idx = CategoricalIndex(["a", "bb", "ccc"] * 10)
expected = """CategoricalIndex(['a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a',
'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb',
'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc'],
Expand All @@ -23,7 +23,7 @@ def test_string_categorical_index_repr(self):
assert repr(idx) == expected

# truncated
idx = pd.CategoricalIndex(["a", "bb", "ccc"] * 100)
idx = CategoricalIndex(["a", "bb", "ccc"] * 100)
expected = """CategoricalIndex(['a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a',
...
'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc', 'a', 'bb', 'ccc'],
Expand All @@ -32,20 +32,20 @@ def test_string_categorical_index_repr(self):
assert repr(idx) == expected

# larger categories
idx = pd.CategoricalIndex(list("abcdefghijklmmo"))
idx = CategoricalIndex(list("abcdefghijklmmo"))
expected = """CategoricalIndex(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l',
'm', 'm', 'o'],
categories=['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', ...], ordered=False, dtype='category')""" # noqa

assert repr(idx) == expected

# short
idx = pd.CategoricalIndex(["あ", "いい", "ううう"])
idx = CategoricalIndex(["あ", "いい", "ううう"])
expected = """CategoricalIndex(['あ', 'いい', 'ううう'], categories=['あ', 'いい', 'ううう'], ordered=False, dtype='category')""" # noqa
assert repr(idx) == expected

# multiple lines
idx = pd.CategoricalIndex(["あ", "いい", "ううう"] * 10)
idx = CategoricalIndex(["あ", "いい", "ううう"] * 10)
expected = """CategoricalIndex(['あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ',
'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい',
'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう'],
Expand All @@ -54,7 +54,7 @@ def test_string_categorical_index_repr(self):
assert repr(idx) == expected

# truncated
idx = pd.CategoricalIndex(["あ", "いい", "ううう"] * 100)
idx = CategoricalIndex(["あ", "いい", "ううう"] * 100)
expected = """CategoricalIndex(['あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ',
...
'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう'],
Expand All @@ -63,7 +63,7 @@ def test_string_categorical_index_repr(self):
assert repr(idx) == expected

# larger categories
idx = pd.CategoricalIndex(list("あいうえおかきくけこさしすせそ"))
idx = CategoricalIndex(list("あいうえおかきくけこさしすせそ"))
expected = """CategoricalIndex(['あ', 'い', 'う', 'え', 'お', 'か', 'き', 'く', 'け', 'こ', 'さ', 'し',
'す', 'せ', 'そ'],
categories=['あ', 'い', 'う', 'え', 'お', 'か', 'き', 'く', ...], ordered=False, dtype='category')""" # noqa
Expand All @@ -74,12 +74,12 @@ def test_string_categorical_index_repr(self):
with cf.option_context("display.unicode.east_asian_width", True):

# short
idx = pd.CategoricalIndex(["あ", "いい", "ううう"])
idx = CategoricalIndex(["あ", "いい", "ううう"])
expected = """CategoricalIndex(['あ', 'いい', 'ううう'], categories=['あ', 'いい', 'ううう'], ordered=False, dtype='category')""" # noqa
assert repr(idx) == expected

# multiple lines
idx = pd.CategoricalIndex(["あ", "いい", "ううう"] * 10)
idx = CategoricalIndex(["あ", "いい", "ううう"] * 10)
expected = """CategoricalIndex(['あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい',
'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう',
'あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい',
Expand All @@ -89,7 +89,7 @@ def test_string_categorical_index_repr(self):
assert repr(idx) == expected

# truncated
idx = pd.CategoricalIndex(["あ", "いい", "ううう"] * 100)
idx = CategoricalIndex(["あ", "いい", "ううう"] * 100)
expected = """CategoricalIndex(['あ', 'いい', 'ううう', 'あ', 'いい', 'ううう', 'あ', 'いい',
'ううう', 'あ',
...
Expand All @@ -100,7 +100,7 @@ def test_string_categorical_index_repr(self):
assert repr(idx) == expected

# larger categories
idx = pd.CategoricalIndex(list("あいうえおかきくけこさしすせそ"))
idx = CategoricalIndex(list("あいうえおかきくけこさしすせそ"))
expected = """CategoricalIndex(['あ', 'い', 'う', 'え', 'お', 'か', 'き', 'く', 'け', 'こ',
'さ', 'し', 'す', 'せ', 'そ'],
categories=['あ', 'い', 'う', 'え', 'お', 'か', 'き', 'く', ...], ordered=False, dtype='category')""" # noqa
Expand Down
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