CI: Check for inconsistent pandas namespace usage

ci/code_checks.sh

@@ -37,6 +37,12 @@ function invgrep {
     return $((! $EXIT_STATUS))
 }
 
+function check_namespace {
+    local -r CLASS="${1}"
+    grep -R -l --include "*.py" " ${CLASS}(" pandas/tests | xargs grep -n "pd\.${CLASS}("
+    test $? -gt 0
+}
+
 if [[ "$GITHUB_ACTIONS" == "true" ]]; then
     FLAKE8_FORMAT="##[error]%(path)s:%(row)s:%(col)s:%(code)s:%(text)s"
     INVGREP_PREPEND="##[error]"
@@ -195,6 +201,11 @@ if [[ -z "$CHECK" || "$CHECK" == "patterns" ]]; then
     MSG='Check code for instances of os.remove' ; echo $MSG
     invgrep -R --include="*.py*" --exclude "common.py" --exclude "test_writers.py" --exclude "test_store.py" -E "os\.remove" pandas/tests/
     RET=$(($RET + $?)) ; echo $MSG "DONE"
+
+    MSG='Check for inconsistent use of pandas namespace in tests' ; echo $MSG
+    check_namespace "Series"
+    RET=$(($RET + $?))
+    echo $MSG "DONE"
 fi
 
 ### CODE ###

pandas/tests/arithmetic/test_datetime64.py

@@ -140,11 +140,11 @@ def test_dt64arr_nat_comparison(self, tz_naive_fixture, box_with_array):
         xbox = box if box not in [pd.Index, pd.array] else np.ndarray
 
         ts = pd.Timestamp.now(tz)
-        ser = pd.Series([ts, pd.NaT])
+        ser = Series([ts, pd.NaT])
 
         obj = tm.box_expected(ser, box)
 
-        expected = pd.Series([True, False], dtype=np.bool_)
+        expected = Series([True, False], dtype=np.bool_)
         expected = tm.box_expected(expected, xbox)
 
         result = obj == ts
@@ -278,7 +278,7 @@ def test_series_comparison_scalars(self, val):
     def test_timestamp_compare_series(self, left, right):
         # see gh-4982
         # Make sure we can compare Timestamps on the right AND left hand side.
-        ser = pd.Series(pd.date_range("20010101", periods=10), name="dates")
+        ser = Series(pd.date_range("20010101", periods=10), name="dates")
         s_nat = ser.copy(deep=True)
 
         ser[0] = pd.Timestamp("nat")
@@ -313,7 +313,7 @@ def test_dt64arr_timestamp_equality(self, box_with_array):
             box_with_array if box_with_array not in [pd.Index, pd.array] else np.ndarray
         )
 
-        ser = pd.Series([pd.Timestamp("2000-01-29 01:59:00"), "NaT"])
+        ser = Series([pd.Timestamp("2000-01-29 01:59:00"), "NaT"])
         ser = tm.box_expected(ser, box_with_array)
 
         result = ser != ser
@@ -973,7 +973,7 @@ def test_dt64arr_sub_timestamp(self, box_with_array):
 
         ser = tm.box_expected(ser, box_with_array)
 
-        delta_series = pd.Series([np.timedelta64(0, "D"), np.timedelta64(1, "D")])
+        delta_series = Series([np.timedelta64(0, "D"), np.timedelta64(1, "D")])
         expected = tm.box_expected(delta_series, box_with_array)
 
         tm.assert_equal(ser - ts, expected)
@@ -985,15 +985,15 @@ def test_dt64arr_sub_NaT(self, box_with_array):
         ser = tm.box_expected(dti, box_with_array)
 
         result = ser - pd.NaT
-        expected = pd.Series([pd.NaT, pd.NaT], dtype="timedelta64[ns]")
+        expected = Series([pd.NaT, pd.NaT], dtype="timedelta64[ns]")
         expected = tm.box_expected(expected, box_with_array)
         tm.assert_equal(result, expected)
 
         dti_tz = dti.tz_localize("Asia/Tokyo")
         ser_tz = tm.box_expected(dti_tz, box_with_array)
 
         result = ser_tz - pd.NaT
-        expected = pd.Series([pd.NaT, pd.NaT], dtype="timedelta64[ns]")
+        expected = Series([pd.NaT, pd.NaT], dtype="timedelta64[ns]")
         expected = tm.box_expected(expected, box_with_array)
         tm.assert_equal(result, expected)
 
@@ -1606,7 +1606,7 @@ def test_dt64_series_arith_overflow(self):
         dt = pd.Timestamp("1700-01-31")
         td = pd.Timedelta("20000 Days")
         dti = pd.date_range("1949-09-30", freq="100Y", periods=4)
-        ser = pd.Series(dti)
+        ser = Series(dti)
         msg = "Overflow in int64 addition"
         with pytest.raises(OverflowError, match=msg):
             ser - dt
@@ -1618,7 +1618,7 @@ def test_dt64_series_arith_overflow(self):
             td + ser
 
         ser.iloc[-1] = pd.NaT
-        expected = pd.Series(
+        expected = Series(
             ["2004-10-03", "2104-10-04", "2204-10-04", "NaT"], dtype="datetime64[ns]"
         )
         res = ser + td
@@ -1627,9 +1627,7 @@ def test_dt64_series_arith_overflow(self):
         tm.assert_series_equal(res, expected)
 
         ser.iloc[1:] = pd.NaT
-        expected = pd.Series(
-            ["91279 Days", "NaT", "NaT", "NaT"], dtype="timedelta64[ns]"
-        )
+        expected = Series(["91279 Days", "NaT", "NaT", "NaT"], dtype="timedelta64[ns]")
         res = ser - dt
         tm.assert_series_equal(res, expected)
         res = dt - ser
@@ -1830,8 +1828,8 @@ def test_dt64tz_series_sub_dtitz(self):
         # GH#19071 subtracting tzaware DatetimeIndex from tzaware Series
         # (with same tz) raises, fixed by #19024
         dti = pd.date_range("1999-09-30", periods=10, tz="US/Pacific")
-        ser = pd.Series(dti)
-        expected = pd.Series(pd.TimedeltaIndex(["0days"] * 10))
+        ser = Series(dti)
+        expected = Series(pd.TimedeltaIndex(["0days"] * 10))
 
         res = dti - ser
         tm.assert_series_equal(res, expected)

pandas/tests/arithmetic/test_interval.py

@@ -290,6 +290,6 @@ def test_index_series_compat(self, op, constructor, expected_type, assert_func):
     def test_comparison_operations(self, scalars):
         # GH #28981
         expected = Series([False, False])
-        s = pd.Series([pd.Interval(0, 1), pd.Interval(1, 2)], dtype="interval")
+        s = Series([pd.Interval(0, 1), pd.Interval(1, 2)], dtype="interval")
         result = s == scalars
         tm.assert_series_equal(result, expected)