STYLE: fix pylint reimported warnings

pandas/_testing/__init__.py

@@ -610,8 +610,6 @@ def makeCustomIndex(
     for i in range(nlevels):
 
         def keyfunc(x):
-            import re
-
             numeric_tuple = re.sub(r"[^\d_]_?", "", x).split("_")
             return [int(num) for num in numeric_tuple]
 

pandas/_testing/contexts.py

@@ -62,7 +62,6 @@ def set_timezone(tz: str) -> Generator[None, None, None]:
     ...
     'EST'
     """
-    import os
     import time
 
     def setTZ(tz) -> None:

pandas/core/generic.py

@@ -9045,8 +9045,6 @@ def compare(
         keep_equal: bool_t = False,
         result_names: Suffixes = ("self", "other"),
     ):
-        from pandas.core.reshape.concat import concat
-
         if type(self) is not type(other):
             cls_self, cls_other = type(self).__name__, type(other).__name__
             raise TypeError(

pandas/io/sql.py

@@ -741,7 +741,6 @@ def pandasSQL_builder(con, schema: str | None = None) -> SQLDatabase | SQLiteDat
     provided parameters.
     """
     import sqlite3
-    import warnings
 
     if isinstance(con, sqlite3.Connection) or con is None:
         return SQLiteDatabase(con)

pandas/plotting/_matplotlib/core.py

@@ -1655,8 +1655,6 @@ def _start_base(self):
         return self.bottom
 
     def _make_plot(self) -> None:
-        import matplotlib as mpl
-
         colors = self._get_colors()
         ncolors = len(colors)
 

pandas/tests/groupby/test_grouping.py

@@ -393,8 +393,6 @@ def test_groupby_grouper(self, df):
 
     def test_groupby_dict_mapping(self):
         # GH #679
-        from pandas import Series
-
         s = Series({"T1": 5})
         result = s.groupby({"T1": "T2"}).agg(sum)
         expected = s.groupby(["T2"]).agg(sum)

pandas/tests/indexing/test_loc.py

@@ -953,11 +953,7 @@ def test_loc_coercion(self):
 
     def test_loc_coercion2(self):
         # GH#12045
-        import datetime
-
-        df = DataFrame(
-            {"date": [datetime.datetime(2012, 1, 1), datetime.datetime(1012, 1, 2)]}
-        )
+        df = DataFrame({"date": [datetime(2012, 1, 1), datetime(1012, 1, 2)]})
         expected = df.dtypes
 
         result = df.iloc[[0]]

pandas/tests/io/excel/test_readers.py

@@ -882,10 +882,7 @@ def test_read_from_file_url(self, read_ext, datapath):
         tm.assert_frame_equal(url_table, local_table)
 
     def test_read_from_pathlib_path(self, read_ext):
-
         # GH12655
-        from pathlib import Path
-
         str_path = "test1" + read_ext
         expected = pd.read_excel(str_path, sheet_name="Sheet1", index_col=0)
 

pandas/tests/io/formats/test_format.py

@@ -5,6 +5,7 @@
 from datetime import (
     datetime,
     time,
+    timedelta,
 )
 from io import StringIO
 import itertools
@@ -994,12 +995,10 @@ def test_truncate_with_different_dtypes(self):
         # when truncated the dtypes of the splits can differ
 
         # 11594
-        import datetime
-
         s = Series(
-            [datetime.datetime(2012, 1, 1)] * 10
-            + [datetime.datetime(1012, 1, 2)]
-            + [datetime.datetime(2012, 1, 3)] * 10
+            [datetime(2012, 1, 1)] * 10
+            + [datetime(1012, 1, 2)]
+            + [datetime(2012, 1, 3)] * 10
         )
 
         with option_context("display.max_rows", 8):
@@ -1250,8 +1249,6 @@ def test_long_series(self):
             dtype="int64",
         )
 
-        import re
-
         str_rep = str(s)
         nmatches = len(re.findall("dtype", str_rep))
         assert nmatches == 1
@@ -2445,12 +2442,6 @@ def test_datetimeindex_highprecision(self, start_date):
         assert start_date in result
 
     def test_timedelta64(self):
-
-        from datetime import (
-            datetime,
-            timedelta,
-        )
-
         Series(np.array([1100, 20], dtype="timedelta64[ns]")).to_string()
 
         s = Series(date_range("2012-1-1", periods=3, freq="D"))

pandas/tests/io/json/test_normalize.py

@@ -866,8 +866,6 @@ def test_with_large_max_level(self):
 
     def test_deprecated_import(self):
         with tm.assert_produces_warning(FutureWarning):
-            from pandas.io.json import json_normalize
-
             recs = [{"a": 1, "b": 2, "c": 3}, {"a": 4, "b": 5, "c": 6}]
             json_normalize(recs)
 

pandas/tests/reductions/test_reductions.py

@@ -890,8 +890,6 @@ def test_idxmax(self):
         allna = string_series * np.nan
         assert isna(allna.idxmax())
 
-        from pandas import date_range
-
         s = Series(date_range("20130102", periods=6))
         result = s.idxmax()
         assert result == 5

pandas/tests/reshape/concat/test_datetimes.py

@@ -22,8 +22,6 @@
 
 class TestDatetimeConcat:
     def test_concat_datetime64_block(self):
-        from pandas.core.indexes.datetimes import date_range
-
         rng = date_range("1/1/2000", periods=10)
 
         df = DataFrame({"time": rng})

pandas/tests/series/accessors/test_dt_accessor.py

@@ -632,12 +632,6 @@ def test_strftime_all_nat(self, data):
         tm.assert_series_equal(result, expected)
 
     def test_valid_dt_with_missing_values(self):
-
-        from datetime import (
-            date,
-            time,
-        )
-
         # GH 8689
         ser = Series(date_range("20130101", periods=5, freq="D"))
         ser.iloc[2] = pd.NaT

pandas/tests/tseries/offsets/test_custom_business_month.py

@@ -400,8 +400,6 @@ def test_holidays(self):
 
     @pytest.mark.filterwarnings("ignore:Non:pandas.errors.PerformanceWarning")
     def test_datetimeindex(self):
-        from pandas.tseries.holiday import USFederalHolidayCalendar
-
         hcal = USFederalHolidayCalendar()
         freq = CBMonthEnd(calendar=hcal)
 

pyproject.toml

@@ -153,7 +153,6 @@ disable = [
   "raise-missing-from",
   "redefined-builtin",
   "redefined-outer-name",
-  "reimported",
   "self-assigning-variable",
   "self-cls-assignment",
   "signature-differs",