GH1055 Fix tests

Author: loicdiridollou

tests/test_api_typing.py

@@ -1,32 +1,55 @@
 """Test module for classes in pandas.api.typing."""
 
+from pathlib import Path
+
 import numpy as np
 import pandas as pd
+from pandas._testing import ensure_clean
 from pandas.api.typing import (
     DataFrameGroupBy,
     DatetimeIndexResamplerGroupby,
+    Expanding,
+    ExpandingGroupby,
+    ExponentialMovingWindow,
+    ExponentialMovingWindowGroupby,
+    JsonReader,
+    NaTType,
     NAType,
+    PeriodIndexResamplerGroupby,
+    Resampler,
+    Rolling,
+    RollingGroupby,
     SeriesGroupBy,
+    TimedeltaIndexResamplerGroupby,
+    TimeGrouper,
+    Window,
 )
+import pytest
 from typing_extensions import assert_type
 
 from tests import check
 
+from pandas.io.json._json import read_json
+from pandas.io.stata import StataReader
+
 
 def test_dataframegroupby():
     df = pd.DataFrame({"a": [1, 2, 3]})
-    check(
-        assert_type(df.groupby("a"), DataFrameGroupBy),
-        DataFrameGroupBy,
-    )
+    group = df.groupby("a")
+
+    def f1(gb: DataFrameGroupBy):
+        check(gb, DataFrameGroupBy)
+
+    f1(group)
 
 
 def test_seriesgroupby():
-    sr: pd.Series[int] = pd.Series([1, 2, 3], index=pd.Index(["a", "b", "a"]))
-    check(
-        assert_type(sr.groupby(level=0), SeriesGroupBy),
-        SeriesGroupBy,
-    )
+    sr = pd.Series([1, 2, 3], index=pd.Index(["a", "b", "a"]))
+
+    def f1(gb: SeriesGroupBy):
+        check(gb, SeriesGroupBy)
+
+    f1(sr.groupby(level=0))
 
 
 def tests_datetimeindexersamplergroupby() -> None:
@@ -35,13 +58,100 @@ def tests_datetimeindexersamplergroupby() -> None:
         np.random.standard_normal((365, 2)), index=idx, columns=["col1", "col2"]
     )
     gb_df = df.groupby("col2")
-    check(
-        assert_type(gb_df.resample("ME"), DatetimeIndexResamplerGroupby),
-        DatetimeIndexResamplerGroupby,
-        pd.DataFrame,
+    check(gb_df.resample("ME"), DatetimeIndexResamplerGroupby)
+
+
+def test_timedeltaindexresamplergroupby() -> None:
+    idx = pd.TimedeltaIndex(["0 days", "1 days", "2 days", "3 days", "4 days"])
+    df = pd.DataFrame(
+        np.random.standard_normal((5, 2)), index=idx, columns=["col1", "col2"]
     )
+    gb_df = df.groupby("col2")
+    check(gb_df.resample("1D"), TimedeltaIndexResamplerGroupby)
 
 
 def test_natype() -> None:
     i64dt = pd.Int64Dtype()
     check(assert_type(i64dt.na_value, NAType), NAType)
+
+
+def test_nattype() -> None:
+    td = pd.Timedelta("1 day")
+    as_nat = pd.NaT
+    check(assert_type(td + as_nat, NaTType), NaTType)
+
+
+def test_expanding() -> None:
+    df = pd.DataFrame({"B": [0, 1, 2, np.nan, 4]})
+    check(df.expanding(), Expanding)
+
+
+def test_expanding_groubpy() -> None:
+    df = pd.DataFrame({"B": [0, 1, 2, np.nan, 4]})
+    check(df.groupby("B").expanding(), ExpandingGroupby)
+
+
+def test_ewm() -> None:
+    df = pd.DataFrame({"B": [0, 1, 2, np.nan, 4]})
+    check(df.ewm(2), ExponentialMovingWindow)
+
+
+def test_ewm_groubpy() -> None:
+    df = pd.DataFrame({"B": [0, 1, 2, np.nan, 4]})
+    check(df.groupby("B").ewm(2), ExponentialMovingWindowGroupby)
+
+
+def test_json_reader() -> None:
+    df = pd.DataFrame({"B": [0, 1, 2, np.nan, 4]})
+
+    with ensure_clean() as path:
+        check(assert_type(df.to_json(path), None), type(None))
+        json_reader = read_json(path, chunksize=1, lines=True)
+        check(json_reader, JsonReader)
+        json_reader.close()
+
+
+@pytest.mark.skip("Resampling with a PeriodIndex is deprecated.")
+def test_periodindexresamplergroupby() -> None:
+    idx = pd.period_range("2020-01-28 09:00", periods=4, freq="D")
+    df = pd.DataFrame(data=4 * [range(2)], index=idx, columns=["a", "b"])
+    check(
+        df.groupby("a").resample("3min"),
+        PeriodIndexResamplerGroupby,
+    )
+
+
+def test_resampler() -> None:
+    s = pd.Series([1, 2, 3, 4, 5], index=pd.date_range("20130101", periods=5, freq="s"))
+    check(s.resample("3min"), Resampler)
+
+
+def test_rolling() -> None:
+    df = pd.DataFrame({"B": [0, 1, 2, np.nan, 4]})
+    check(df.rolling(2), Rolling)
+
+
+def test_rolling_groupby() -> None:
+    df = pd.DataFrame({"B": [0, 1, 2, np.nan, 4]})
+    check(df.groupby("B").rolling(2), RollingGroupby)
+
+
+def test_timegrouper() -> None:
+    check(pd.Grouper(key="Publish date", freq="1W"), TimeGrouper)
+
+
+def test_window() -> None:
+    ser = pd.Series([0, 1, 5, 2, 8])
+    check(ser.rolling(2, win_type="gaussian"), Window)
+
+
+def test_statereader(tmp_path: Path) -> None:
+    df = pd.DataFrame([[1, 2], [3, 4]], columns=["col_1", "col_2"])
+    time_stamp = pd.Timestamp(2000, 2, 29, 14, 21)
+    variable_labels = {"col_1": "This is an example"}
+    path = tmp_path / "file"
+    df.to_stata(
+        path, time_stamp=time_stamp, variable_labels=variable_labels, version=None
+    )
+    with StataReader(path) as reader:
+        check(reader, StataReader)