CLN/BUG: Allow assert_produces_warning to raise during an exception

pandas/_libs/tslibs/offsets.pyx

@@ -389,7 +389,6 @@ cdef class BaseOffset:
     _attributes = tuple(["n", "normalize"])
     _use_relativedelta = False
     _adjust_dst = True
-    _deprecations = frozenset(["isAnchored", "onOffset"])
 
     # cdef readonly:
     #    int64_t n

pandas/_testing/_warnings.py

@@ -87,22 +87,22 @@ class for all warnings. To raise multiple types of exceptions,
 
     with warnings.catch_warnings(record=True) as w:
         warnings.simplefilter(filter_level)
-        yield w
-
-        if expected_warning:
-            expected_warning = cast(Type[Warning], expected_warning)
-            _assert_caught_expected_warning(
-                caught_warnings=w,
-                expected_warning=expected_warning,
-                match=match,
-                check_stacklevel=check_stacklevel,
-            )
-
-        if raise_on_extra_warnings:
-            _assert_caught_no_extra_warnings(
-                caught_warnings=w,
-                expected_warning=expected_warning,
-            )
+        try:
+            yield w
+        finally:
+            if expected_warning:
+                expected_warning = cast(Type[Warning], expected_warning)
+                _assert_caught_expected_warning(
+                    caught_warnings=w,
+                    expected_warning=expected_warning,
+                    match=match,
+                    check_stacklevel=check_stacklevel,
+                )
+            if raise_on_extra_warnings:
+                _assert_caught_no_extra_warnings(
+                    caught_warnings=w,
+                    expected_warning=expected_warning,
+                )
 
 
 def maybe_produces_warning(warning: type[Warning], condition: bool, **kwargs):

pandas/core/arrays/datetimes.py

@@ -2182,8 +2182,8 @@ def objects_to_datetime64ns(
 
 def maybe_convert_dtype(data, copy: bool, tz: tzinfo | None = None):
     """
-    Convert data based on dtype conventions, issuing deprecation warnings
-    or errors where appropriate.
+    Convert data based on dtype conventions, issuing
+    errors where appropriate.
 
     Parameters
     ----------

pandas/tests/apply/test_invalid_arg.py

@@ -348,7 +348,7 @@ def test_transform_wont_agg_series(string_series, func):
     warn = RuntimeWarning if func[0] == "sqrt" else None
     warn_msg = "invalid value encountered in sqrt"
     with pytest.raises(ValueError, match=msg):
-        with tm.assert_produces_warning(warn, match=warn_msg):
+        with tm.assert_produces_warning(warn, match=warn_msg, check_stacklevel=False):
             string_series.transform(func)
 
 

pandas/tests/extension/test_arrow.py

@@ -527,7 +527,9 @@ def test_groupby_extension_transform(self, data_for_grouping, request):
                 )
             )
         with tm.maybe_produces_warning(
-            PerformanceWarning, pa_version_under7p0, check_stacklevel=False
+            PerformanceWarning,
+            pa_version_under7p0 and not pa.types.is_duration(pa_dtype),
+            check_stacklevel=False,
         ):
             super().test_groupby_extension_transform(data_for_grouping)
 
@@ -543,7 +545,9 @@ def test_groupby_extension_apply(
                 )
             )
         with tm.maybe_produces_warning(
-            PerformanceWarning, pa_version_under7p0, check_stacklevel=False
+            PerformanceWarning,
+            pa_version_under7p0 and not pa.types.is_duration(pa_dtype),
+            check_stacklevel=False,
         ):
             super().test_groupby_extension_apply(data_for_grouping, groupby_apply_op)
 
@@ -565,7 +569,9 @@ def test_groupby_extension_agg(self, as_index, data_for_grouping, request):
                 )
             )
         with tm.maybe_produces_warning(
-            PerformanceWarning, pa_version_under7p0, check_stacklevel=False
+            PerformanceWarning,
+            pa_version_under7p0 and not pa.types.is_duration(pa_dtype),
+            check_stacklevel=False,
         ):
             super().test_groupby_extension_agg(as_index, data_for_grouping)
 
@@ -804,7 +810,9 @@ def test_value_counts_with_normalize(self, data, request):
                 )
             )
         with tm.maybe_produces_warning(
-            PerformanceWarning, pa_version_under7p0, check_stacklevel=False
+            PerformanceWarning,
+            pa_version_under7p0 and not pa.types.is_duration(pa_dtype),
+            check_stacklevel=False,
         ):
             super().test_value_counts_with_normalize(data)
 
@@ -923,7 +931,9 @@ def test_sort_values_frame(self, data_for_sorting, ascending, request):
                 )
             )
         with tm.maybe_produces_warning(
-            PerformanceWarning, pa_version_under7p0, check_stacklevel=False
+            PerformanceWarning,
+            pa_version_under7p0 and not pa.types.is_duration(pa_dtype),
+            check_stacklevel=False,
         ):
             super().test_sort_values_frame(data_for_sorting, ascending)
 

pandas/tests/extension/test_sparse.py

@@ -480,8 +480,7 @@ class TestParsing(BaseSparseTests, base.BaseParsingTests):
     def test_EA_types(self, engine, data):
         expected_msg = r".*must implement _from_sequence_of_strings.*"
         with pytest.raises(NotImplementedError, match=expected_msg):
-            with tm.assert_produces_warning(FutureWarning, match="astype from"):
-                super().test_EA_types(engine, data)
+            super().test_EA_types(engine, data)
 
 
 class TestNoNumericAccumulations(base.BaseAccumulateTests):

pandas/tests/frame/indexing/test_getitem.py

@@ -156,8 +156,7 @@ def test_getitem_listlike(self, idx_type, levels, float_frame):
 
         idx = idx_type(keys + [missing])
         with pytest.raises(KeyError, match="not in index"):
-            with tm.assert_produces_warning(FutureWarning):
-                frame[idx]
+            frame[idx]
 
     def test_getitem_iloc_generator(self):
         # GH#39614
@@ -357,8 +356,7 @@ def test_getitem_boolean_frame_unaligned_with_duplicate_columns(self, df_dup_col
         df = df_dup_cols
         msg = "cannot reindex on an axis with duplicate labels"
         with pytest.raises(ValueError, match=msg):
-            with tm.assert_produces_warning(FutureWarning, match="non-unique"):
-                df[df.A > 6]
+            df[df.A > 6]
 
     def test_getitem_boolean_series_with_duplicate_columns(self, df_dup_cols):
         # boolean indexing

pandas/tests/frame/indexing/test_setitem.py

@@ -85,8 +85,7 @@ def test_setitem_error_msmgs(self):
         )
         msg = "cannot reindex on an axis with duplicate labels"
         with pytest.raises(ValueError, match=msg):
-            with tm.assert_produces_warning(FutureWarning, match="non-unique"):
-                df["newcol"] = ser
+            df["newcol"] = ser
 
         # GH 4107, more descriptive error message
         df = DataFrame(np.random.randint(0, 2, (4, 4)), columns=["a", "b", "c", "d"])

pandas/tests/frame/methods/test_reindex.py

@@ -808,8 +808,7 @@ def test_reindex_dups(self):
         # reindex fails
         msg = "cannot reindex on an axis with duplicate labels"
         with pytest.raises(ValueError, match=msg):
-            with tm.assert_produces_warning(FutureWarning, match="non-unique"):
-                df.reindex(index=list(range(len(df))))
+            df.reindex(index=list(range(len(df))))
 
     def test_reindex_with_duplicate_columns(self):
 
@@ -819,11 +818,9 @@ def test_reindex_with_duplicate_columns(self):
         )
         msg = "cannot reindex on an axis with duplicate labels"
         with pytest.raises(ValueError, match=msg):
-            with tm.assert_produces_warning(FutureWarning, match="non-unique"):
-                df.reindex(columns=["bar"])
+            df.reindex(columns=["bar"])
         with pytest.raises(ValueError, match=msg):
-            with tm.assert_produces_warning(FutureWarning, match="non-unique"):
-                df.reindex(columns=["bar", "foo"])
+            df.reindex(columns=["bar", "foo"])
 
     def test_reindex_axis_style(self):
         # https://github.com/pandas-dev/pandas/issues/12392
@@ -1091,8 +1088,7 @@ def test_reindex_with_categoricalindex(self):
         # passed duplicate indexers are not allowed
         msg = "cannot reindex on an axis with duplicate labels"
         with pytest.raises(ValueError, match=msg):
-            with tm.assert_produces_warning(FutureWarning, match="non-unique"):
-                df2.reindex(["a", "b"])
+            df2.reindex(["a", "b"])
 
         # args NotImplemented ATM
         msg = r"argument {} is not implemented for CategoricalIndex\.reindex"

pandas/tests/frame/methods/test_sort_index.py

@@ -44,14 +44,12 @@ def test_sort_index_and_reconstruction_doc_example(self):
         assert result.index.is_monotonic_increasing
         tm.assert_frame_equal(result, expected)
 
-    # FIXME: the FutureWarning is issued on a setitem-with-expansion
-    #  which will *not* change behavior, so should not get a warning.
-    @pytest.mark.filterwarnings("ignore:.*will attempt to set.*:FutureWarning")
     def test_sort_index_non_existent_label_multiindex(self):
         # GH#12261
         df = DataFrame(0, columns=[], index=MultiIndex.from_product([[], []]))
-        df.loc["b", "2"] = 1
-        df.loc["a", "3"] = 1
+        with tm.assert_produces_warning(None):
+            df.loc["b", "2"] = 1
+            df.loc["a", "3"] = 1
         result = df.sort_index().index.is_monotonic_increasing
         assert result is True
 

pandas/tests/frame/test_arithmetic.py

@@ -1067,7 +1067,7 @@ def test_frame_with_frame_reindex(self):
         ],
         ids=lambda x: x.__name__,
     )
-    def test_binop_other(self, op, value, dtype, switch_numexpr_min_elements):
+    def test_binop_other(self, op, value, dtype, switch_numexpr_min_elements, request):
 
         skip = {
             (operator.truediv, "bool"),
@@ -1099,10 +1099,14 @@ def test_binop_other(self, op, value, dtype, switch_numexpr_min_elements):
                 msg = None
             elif dtype == "complex128":
                 msg = "ufunc 'remainder' not supported for the input types"
-                warn = UserWarning  # "evaluating in Python space because ..."
             elif op is operator.sub:
                 msg = "numpy boolean subtract, the `-` operator, is "
-                warn = UserWarning  # "evaluating in Python space because ..."
+                if (
+                    dtype == "bool"
+                    and expr.USE_NUMEXPR
+                    and switch_numexpr_min_elements == 0
+                ):
+                    warn = UserWarning  # "evaluating in Python space because ..."
             else:
                 msg = (
                     f"cannot perform __{op.__name__}__ with this "

pandas/tests/groupby/test_categorical.py

@@ -1893,10 +1893,7 @@ def test_category_order_transformer(
         df = df.set_index(keys)
     args = get_groupby_method_args(transformation_func, df)
     gb = df.groupby(keys, as_index=as_index, sort=sort, observed=observed)
-    msg = "is deprecated and will be removed in a future version"
-    warn = FutureWarning if transformation_func == "tshift" else None
-    with tm.assert_produces_warning(warn, match=msg):
-        op_result = getattr(gb, transformation_func)(*args)
+    op_result = getattr(gb, transformation_func)(*args)
     result = op_result.index.get_level_values("a").categories
     expected = Index([1, 4, 3, 2])
     tm.assert_index_equal(result, expected)

pandas/tests/groupby/transform/test_transform.py

@@ -1362,10 +1362,7 @@ def test_null_group_str_transformer(request, dropna, transformation_func):
         # ngroup/cumcount always returns a Series as it counts the groups, not values
         expected = expected["B"].rename(None)
 
-    warn = FutureWarning if transformation_func in ("backfill", "pad") else None
-    msg = f"{transformation_func} is deprecated"
-    with tm.assert_produces_warning(warn, match=msg):
-        result = gb.transform(transformation_func, *args)
+    result = gb.transform(transformation_func, *args)
 
     tm.assert_equal(result, expected)
 
@@ -1411,7 +1408,7 @@ def test_null_group_str_reducer_series(request, dropna, reduction_func):
     tm.assert_series_equal(result, expected)
 
 
-def test_null_group_str_transformer_series(request, dropna, transformation_func):
+def test_null_group_str_transformer_series(dropna, transformation_func):
     # GH 17093
     ser = Series([1, 2, 2], index=[1, 2, 3])
     args = get_groupby_method_args(transformation_func, ser)
@@ -1432,9 +1429,7 @@ def test_null_group_str_transformer_series(request, dropna, transformation_func)
         buffer.append(Series([np.nan], index=[3], dtype=dtype))
     expected = concat(buffer)
 
-    warn = FutureWarning if transformation_func in ("backfill", "pad") else None
-    msg = f"{transformation_func} is deprecated"
-    with tm.assert_produces_warning(warn, match=msg):
+    with tm.assert_produces_warning(None):
         result = gb.transform(transformation_func, *args)
 
     tm.assert_equal(result, expected)

pandas/tests/indexes/interval/test_base.py

@@ -61,8 +61,7 @@ def test_getitem_2d_deprecated(self, simple_index):
         # GH#30588 multi-dim indexing is deprecated, but raising is also acceptable
         idx = simple_index
         with pytest.raises(ValueError, match="multi-dimensional indexing not allowed"):
-            with tm.assert_produces_warning(FutureWarning):
-                idx[:, None]
+            idx[:, None]
         with pytest.raises(ValueError, match="multi-dimensional indexing not allowed"):
             # GH#44051
             idx[True]

pandas/tests/indexes/multi/test_reindex.py

@@ -106,8 +106,7 @@ def test_reindex_non_unique():
 
     msg = "cannot handle a non-unique multi-index!"
     with pytest.raises(ValueError, match=msg):
-        with tm.assert_produces_warning(FutureWarning, match="non-unique"):
-            a.reindex(new_idx)
+        a.reindex(new_idx)
 
 
 @pytest.mark.parametrize("values", [[["a"], ["x"]], [[], []]])

pandas/tests/indexes/test_common.py

@@ -23,7 +23,6 @@
 import pandas as pd
 from pandas import (
     CategoricalIndex,
-    DatetimeIndex,
     MultiIndex,
     PeriodIndex,
     RangeIndex,
@@ -389,14 +388,7 @@ def test_astype_preserves_name(self, index, dtype):
             index.name = "idx"
 
         warn = None
-        if (
-            isinstance(index, DatetimeIndex)
-            and index.tz is not None
-            and dtype == "datetime64[ns]"
-        ):
-            # This astype is deprecated in favor of tz_localize
-            warn = FutureWarning
-        elif index.dtype.kind == "c" and dtype in ["float64", "int64", "uint64"]:
+        if index.dtype.kind == "c" and dtype in ["float64", "int64", "uint64"]:
             # imaginary components discarded
             warn = np.ComplexWarning
 

pandas/tests/indexing/test_indexing.py

@@ -69,8 +69,7 @@ def test_setitem_ndarray_1d_2(self):
 
         msg = "Must have equal len keys and value when setting with an iterable"
         with pytest.raises(ValueError, match=msg):
-            with tm.assert_produces_warning(FutureWarning, match="label-based"):
-                df[2:5] = np.arange(1, 4) * 1j
+            df[2:5] = np.arange(1, 4) * 1j
 
     def test_getitem_ndarray_3d(
         self, index, frame_or_series, indexer_sli, using_array_manager

pandas/tests/io/parser/test_parse_dates.py

@@ -924,9 +924,7 @@ def test_parse_dates_custom_euro_format(all_parsers, kwargs):
         tm.assert_frame_equal(df, expected)
     else:
         msg = "got an unexpected keyword argument 'day_first'"
-        with pytest.raises(TypeError, match=msg), tm.assert_produces_warning(
-            FutureWarning
-        ):
+        with pytest.raises(TypeError, match=msg):
             parser.read_csv(
                 StringIO(data),
                 names=["time", "Q", "NTU"],

pandas/tests/io/test_stata.py

@@ -1725,8 +1725,7 @@ def test_invalid_file_not_written(self, version):
                 r"ordinal not in range\(128\)"
             )
             with pytest.raises(UnicodeEncodeError, match=f"{msg1}|{msg2}"):
-                with tm.assert_produces_warning(ResourceWarning):
-                    df.to_stata(path)
+                df.to_stata(path)
 
     def test_strl_latin1(self):
         # GH 23573, correct GSO data to reflect correct size