TST: Added match argument for most uses of tm.assert_produces_warning (#58396)

* Fix for all FutureWarnings

* Add match for most warnings

* Cleaner code

---------

Co-authored-by: Abdulaziz Aloqeely <[email protected]>

Author: Aloqeely

doc/source/development/contributing_codebase.rst

@@ -557,11 +557,12 @@ is being raised, using ``pytest.raises`` instead.
 Testing a warning
 ^^^^^^^^^^^^^^^^^
 
-Use ``tm.assert_produces_warning`` as a context manager to check that a block of code raises a warning.
+Use ``tm.assert_produces_warning`` as a context manager to check that a block of code raises a warning
+and specify the warning message using the ``match`` argument.
 
 .. code-block:: python
 
-    with tm.assert_produces_warning(DeprecationWarning):
+    with tm.assert_produces_warning(DeprecationWarning, match="the warning message"):
         pd.deprecated_function()
 
 If a warning should specifically not happen in a block of code, pass ``False`` into the context manager.

pandas/tests/arrays/sparse/test_constructors.py

@@ -90,13 +90,13 @@ def test_constructor_warns_when_losing_timezone(self):
         dti = pd.date_range("2016-01-01", periods=3, tz="US/Pacific")
 
         expected = SparseArray(np.asarray(dti, dtype="datetime64[ns]"))
-
-        with tm.assert_produces_warning(UserWarning):
+        msg = "loses timezone information"
+        with tm.assert_produces_warning(UserWarning, match=msg):
             result = SparseArray(dti)
 
         tm.assert_sp_array_equal(result, expected)
 
-        with tm.assert_produces_warning(UserWarning):
+        with tm.assert_produces_warning(UserWarning, match=msg):
             result = SparseArray(pd.Series(dti))
 
         tm.assert_sp_array_equal(result, expected)

pandas/tests/arrays/test_datetimelike.py

@@ -778,7 +778,7 @@ def test_to_period_2d(self, arr1d):
         arr2d = arr1d.reshape(1, -1)
 
         warn = None if arr1d.tz is None else UserWarning
-        with tm.assert_produces_warning(warn):
+        with tm.assert_produces_warning(warn, match="will drop timezone information"):
             result = arr2d.to_period("D")
             expected = arr1d.to_period("D").reshape(1, -1)
         tm.assert_period_array_equal(result, expected)

pandas/tests/computation/test_eval.py

@@ -1014,7 +1014,8 @@ def test_performance_warning_for_poor_alignment(
         else:
             seen = False
 
-        with tm.assert_produces_warning(seen):
+        msg = "Alignment difference on axis 1 is larger than an order of magnitude"
+        with tm.assert_produces_warning(seen, match=msg):
             pd.eval("df + s", engine=engine, parser=parser)
 
         s = Series(np.random.default_rng(2).standard_normal(1000))
@@ -1036,7 +1037,7 @@ def test_performance_warning_for_poor_alignment(
         else:
             wrn = False
 
-        with tm.assert_produces_warning(wrn) as w:
+        with tm.assert_produces_warning(wrn, match=msg) as w:
             pd.eval("df + s", engine=engine, parser=parser)
 
             if not is_python_engine and performance_warning:

pandas/tests/dtypes/test_common.py

@@ -797,5 +797,5 @@ def test_pandas_dtype_numpy_warning():
 
 def test_pandas_dtype_ea_not_instance():
     # GH 31356 GH 54592
-    with tm.assert_produces_warning(UserWarning):
+    with tm.assert_produces_warning(UserWarning, match="without any arguments"):
         assert pandas_dtype(CategoricalDtype) == CategoricalDtype()

pandas/tests/dtypes/test_generic.py

@@ -124,7 +124,7 @@ def test_setattr_warnings():
         #  this should not raise a warning
         df.two.not_an_index = [1, 2]
 
-    with tm.assert_produces_warning(UserWarning):
+    with tm.assert_produces_warning(UserWarning, match="doesn't allow columns"):
         #  warn when setting column to nonexistent name
         df.four = df.two + 2
         assert df.four.sum() > df.two.sum()

pandas/tests/frame/indexing/test_indexing.py

@@ -145,7 +145,7 @@ def test_getitem_boolean(self, mixed_float_frame, mixed_int_frame, datetime_fram
         # we are producing a warning that since the passed boolean
         # key is not the same as the given index, we will reindex
         # not sure this is really necessary
-        with tm.assert_produces_warning(UserWarning):
+        with tm.assert_produces_warning(UserWarning, match="will be reindexed"):
             indexer_obj = indexer_obj.reindex(datetime_frame.index[::-1])
             subframe_obj = datetime_frame[indexer_obj]
             tm.assert_frame_equal(subframe_obj, subframe)

pandas/tests/frame/indexing/test_setitem.py

@@ -711,7 +711,10 @@ def test_setitem_npmatrix_2d(self):
         df["np-array"] = a
 
         # Instantiation of `np.matrix` gives PendingDeprecationWarning
-        with tm.assert_produces_warning(PendingDeprecationWarning):
+        with tm.assert_produces_warning(
+            PendingDeprecationWarning,
+            match="matrix subclass is not the recommended way to represent matrices",
+        ):
             df["np-matrix"] = np.matrix(a)
 
         tm.assert_frame_equal(df, expected)

pandas/tests/frame/methods/test_to_dict.py

@@ -166,7 +166,7 @@ def test_to_dict_not_unique_warning(self):
         # GH#16927: When converting to a dict, if a column has a non-unique name
         # it will be dropped, throwing a warning.
         df = DataFrame([[1, 2, 3]], columns=["a", "a", "b"])
-        with tm.assert_produces_warning(UserWarning):
+        with tm.assert_produces_warning(UserWarning, match="columns will be omitted"):
             df.to_dict()
 
     @pytest.mark.filterwarnings("ignore::UserWarning")

pandas/tests/frame/test_arithmetic.py

@@ -1097,25 +1097,24 @@ def test_binop_other(self, op, value, dtype, switch_numexpr_min_elements):
                     and expr.USE_NUMEXPR
                     and switch_numexpr_min_elements == 0
                 ):
-                    warn = UserWarning  # "evaluating in Python space because ..."
+                    warn = UserWarning
             else:
                 msg = (
                     f"cannot perform __{op.__name__}__ with this "
                     "index type: (DatetimeArray|TimedeltaArray)"
                 )
 
             with pytest.raises(TypeError, match=msg):
-                with tm.assert_produces_warning(warn):
+                with tm.assert_produces_warning(warn, match="evaluating in Python"):
                     op(df, elem.value)
 
         elif (op, dtype) in skip:
             if op in [operator.add, operator.mul]:
                 if expr.USE_NUMEXPR and switch_numexpr_min_elements == 0:
-                    # "evaluating in Python space because ..."
                     warn = UserWarning
                 else:
                     warn = None
-                with tm.assert_produces_warning(warn):
+                with tm.assert_produces_warning(warn, match="evaluating in Python"):
                     op(df, elem.value)
 
             else: