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tests/test_api_typing.py

Lines changed: 25 additions & 30 deletions
Original file line numberDiff line numberDiff line change
@@ -1,7 +1,5 @@
11
"""Test module for classes in pandas.api.typing."""
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3-
from pathlib import Path
4-
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import numpy as np
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import pandas as pd
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from pandas._testing import ensure_clean
@@ -20,6 +18,7 @@
2018
Rolling,
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RollingGroupby,
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SeriesGroupBy,
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StataReader,
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TimedeltaIndexResamplerGroupby,
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TimeGrouper,
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Window,
@@ -30,7 +29,12 @@
3029
from tests import check
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from pandas.io.json._json import read_json
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from pandas.io.stata import StataReader
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ResamplerGroupBy = (
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DatetimeIndexResamplerGroupby
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| PeriodIndexResamplerGroupby
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| TimedeltaIndexResamplerGroupby
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)
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def test_dataframegroupby():
@@ -59,13 +63,10 @@ def tests_datetimeindexersamplergroupby() -> None:
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)
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gb_df = df.groupby("col2")
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62-
# TODO the groupby here is too wide and returns _ResamplerGroupby alias
63-
# def f1(gb: DatetimeIndexResamplerGroupby):
64-
# check(gb, DatetimeIndexResamplerGroupby)
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#
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# f1(gb_df.resample("ME"))
66+
def f1(gb: ResamplerGroupBy):
67+
check(gb, DatetimeIndexResamplerGroupby)
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68-
check(gb_df.resample("ME"), DatetimeIndexResamplerGroupby)
69+
f1(gb_df.resample("ME"))
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def test_timedeltaindexresamplergroupby() -> None:
@@ -75,27 +76,21 @@ def test_timedeltaindexresamplergroupby() -> None:
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)
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gb_df = df.groupby("col2")
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# TODO the groupby here is too wide and returns _ResamplerGroupby alias
79-
# def f1(gb: TimedeltaIndexResamplerGroupby):
80-
# check(gb, TimedeltaIndexResamplerGroupby)
81-
#
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# f1(gb_df.resample("1D"))
79+
def f1(gb: ResamplerGroupBy):
80+
check(gb, TimedeltaIndexResamplerGroupby)
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84-
check(gb_df.resample("1D"), TimedeltaIndexResamplerGroupby)
82+
f1(gb_df.resample("1D"))
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@pytest.mark.skip("Resampling with a PeriodIndex is deprecated.")
8886
def test_periodindexresamplergroupby() -> None:
8987
idx = pd.period_range("2020-01-28 09:00", periods=4, freq="D")
9088
df = pd.DataFrame(data=4 * [range(2)], index=idx, columns=["a", "b"])
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92-
# TODO the groupby here is too wide and returns _ResamplerGroupby alias
93-
# def f1(gb: PeriodIndexResamplerGroupby):
94-
# check(gb, PeriodIndexResamplerGroupby)
95-
#
96-
# f1(df.groupby("a").resample("3min"))
90+
def f1(gb: ResamplerGroupBy):
91+
check(gb, PeriodIndexResamplerGroupby)
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98-
check(df.groupby("a").resample("3min"), PeriodIndexResamplerGroupby)
93+
f1(df.groupby("a").resample("3min"))
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def test_natype() -> None:
@@ -204,17 +199,17 @@ def f1(gb: Window):
204199
f1(ser.rolling(2, win_type="gaussian"))
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206201

207-
def test_statereader(tmp_path: Path) -> None:
202+
def test_statereader() -> None:
208203
df = pd.DataFrame([[1, 2], [3, 4]], columns=["col_1", "col_2"])
209204
time_stamp = pd.Timestamp(2000, 2, 29, 14, 21)
210205
variable_labels = {"col_1": "This is an example"}
211-
path = tmp_path / "file"
212-
df.to_stata(
213-
path, time_stamp=time_stamp, variable_labels=variable_labels, version=None
214-
)
206+
with ensure_clean() as path:
207+
df.to_stata(
208+
path, time_stamp=time_stamp, variable_labels=variable_labels, version=None
209+
)
215210

216-
def f1(gb: StataReader):
217-
check(gb, StataReader)
211+
def f1(gb: StataReader):
212+
check(gb, StataReader)
218213

219-
with StataReader(path) as reader:
220-
f1(reader)
214+
with StataReader(path) as reader:
215+
f1(reader)

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