STY: use pytest.raises context syntax (series) (#24812)

Author: simonjayhawkins

pandas/tests/series/test_alter_axes.py

@@ -16,11 +16,16 @@ class TestSeriesAlterAxes(object):
 
     def test_setindex(self, string_series):
         # wrong type
-        pytest.raises(TypeError, setattr, string_series, 'index', None)
+        msg = (r"Index\(\.\.\.\) must be called with a collection of some"
+               r" kind, None was passed")
+        with pytest.raises(TypeError, match=msg):
+            string_series.index = None
 
         # wrong length
-        pytest.raises(Exception, setattr, string_series, 'index',
-                      np.arange(len(string_series) - 1))
+        msg = (r"Length mismatch: Expected axis has (30|100) elements, new"
+               r" values have (29|99) elements")
+        with pytest.raises(ValueError, match=msg):
+            string_series.index = np.arange(len(string_series) - 1)
 
         # works
         string_series.index = np.arange(len(string_series))

pandas/tests/series/test_analytics.py

@@ -97,8 +97,10 @@ def test_argsort_stable(self):
                                check_dtype=False)
         tm.assert_series_equal(qindexer, Series(qexpected),
                                check_dtype=False)
-        pytest.raises(AssertionError, tm.assert_numpy_array_equal,
-                      qindexer, mindexer)
+        msg = (r"ndarray Expected type <(class|type) 'numpy\.ndarray'>,"
+               r" found <class 'pandas\.core\.series\.Series'> instead")
+        with pytest.raises(AssertionError, match=msg):
+            tm.assert_numpy_array_equal(qindexer, mindexer)
 
     def test_cumsum(self, datetime_series):
         self._check_accum_op('cumsum', datetime_series)
@@ -476,8 +478,13 @@ def test_dot(self):
         assert_almost_equal(a.dot(b['1']), expected['1'])
         assert_almost_equal(a.dot(b2['1']), expected['1'])
 
-        pytest.raises(Exception, a.dot, a.values[:3])
-        pytest.raises(ValueError, a.dot, b.T)
+        msg = r"Dot product shape mismatch, \(4L?,\) vs \(3L?,\)"
+        # exception raised is of type Exception
+        with pytest.raises(Exception, match=msg):
+            a.dot(a.values[:3])
+        msg = "matrices are not aligned"
+        with pytest.raises(ValueError, match=msg):
+            a.dot(b.T)
 
     @pytest.mark.skipif(not PY35,
                         reason='matmul supported for Python>=3.5')
@@ -541,8 +548,13 @@ def test_matmul(self):
                           index=['1', '2', '3'])
         assert_series_equal(result, expected)
 
-        pytest.raises(Exception, a.dot, a.values[:3])
-        pytest.raises(ValueError, a.dot, b.T)
+        msg = r"Dot product shape mismatch, \(4,\) vs \(3,\)"
+        # exception raised is of type Exception
+        with pytest.raises(Exception, match=msg):
+            a.dot(a.values[:3])
+        msg = "matrices are not aligned"
+        with pytest.raises(ValueError, match=msg):
+            a.dot(b.T)
 
     def test_clip(self, datetime_series):
         val = datetime_series.median()
@@ -697,11 +709,13 @@ def test_isin(self):
     def test_isin_with_string_scalar(self):
         # GH4763
         s = Series(['A', 'B', 'C', 'a', 'B', 'B', 'A', 'C'])
-        with pytest.raises(TypeError):
+        msg = (r"only list-like objects are allowed to be passed to isin\(\),"
+               r" you passed a \[str\]")
+        with pytest.raises(TypeError, match=msg):
             s.isin('a')
 
-        with pytest.raises(TypeError):
-            s = Series(['aaa', 'b', 'c'])
+        s = Series(['aaa', 'b', 'c'])
+        with pytest.raises(TypeError, match=msg):
             s.isin('aaa')
 
     def test_isin_with_i8(self):
@@ -771,18 +785,21 @@ def test_ptp(self):
         with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
             tm.assert_series_equal(s.ptp(level=0, skipna=False), expected)
 
-        with pytest.raises(ValueError):
+        msg = r"No axis named 1 for object type <(class|type) 'type'>"
+        with pytest.raises(ValueError, match=msg):
             with tm.assert_produces_warning(FutureWarning,
                                             check_stacklevel=False):
                 s.ptp(axis=1)
 
         s = pd.Series(['a', 'b', 'c', 'd', 'e'])
-        with pytest.raises(TypeError):
+        msg = r"unsupported operand type\(s\) for -: 'str' and 'str'"
+        with pytest.raises(TypeError, match=msg):
             with tm.assert_produces_warning(FutureWarning,
                                             check_stacklevel=False):
                 s.ptp()
 
-        with pytest.raises(NotImplementedError):
+        msg = r"Series\.ptp does not implement numeric_only\."
+        with pytest.raises(NotImplementedError, match=msg):
             with tm.assert_produces_warning(FutureWarning,
                                             check_stacklevel=False):
                 s.ptp(numeric_only=True)
@@ -1103,29 +1120,38 @@ def test_validate_any_all_out_keepdims_raises(self, kwargs, func):
         param = list(kwargs)[0]
         name = func.__name__
 
-        msg = "the '{}' parameter .* {}".format(param, name)
+        msg = (r"the '{arg}' parameter is not "
+               r"supported in the pandas "
+               r"implementation of {fname}\(\)").format(arg=param, fname=name)
         with pytest.raises(ValueError, match=msg):
             func(s, **kwargs)
 
     @td.skip_if_np_lt_115
     def test_validate_sum_initial(self):
         s = pd.Series([1, 2])
-        with pytest.raises(ValueError, match="the 'initial' .* sum"):
+        msg = (r"the 'initial' parameter is not "
+               r"supported in the pandas "
+               r"implementation of sum\(\)")
+        with pytest.raises(ValueError, match=msg):
             np.sum(s, initial=10)
 
     def test_validate_median_initial(self):
         s = pd.Series([1, 2])
-        with pytest.raises(ValueError,
-                           match="the 'overwrite_input' .* median"):
+        msg = (r"the 'overwrite_input' parameter is not "
+               r"supported in the pandas "
+               r"implementation of median\(\)")
+        with pytest.raises(ValueError, match=msg):
             # It seems like np.median doesn't dispatch, so we use the
             # method instead of the ufunc.
             s.median(overwrite_input=True)
 
     @td.skip_if_np_lt_115
     def test_validate_stat_keepdims(self):
         s = pd.Series([1, 2])
-        with pytest.raises(ValueError,
-                           match="the 'keepdims'"):
+        msg = (r"the 'keepdims' parameter is not "
+               r"supported in the pandas "
+               r"implementation of sum\(\)")
+        with pytest.raises(ValueError, match=msg):
             np.sum(s, keepdims=True)
 
 

pandas/tests/series/test_api.py

@@ -289,8 +289,11 @@ def test_index_tab_completion(self, index):
     def test_not_hashable(self):
         s_empty = Series()
         s = Series([1])
-        pytest.raises(TypeError, hash, s_empty)
-        pytest.raises(TypeError, hash, s)
+        msg = "'Series' objects are mutable, thus they cannot be hashed"
+        with pytest.raises(TypeError, match=msg):
+            hash(s_empty)
+        with pytest.raises(TypeError, match=msg):
+            hash(s)
 
     def test_contains(self):
         tm.assert_contains_all(self.ts.index, self.ts)
@@ -333,7 +336,8 @@ def test_items(self):
 
     def test_raise_on_info(self):
         s = Series(np.random.randn(10))
-        with pytest.raises(AttributeError):
+        msg = "'Series' object has no attribute 'info'"
+        with pytest.raises(AttributeError, match=msg):
             s.info()
 
     def test_copy(self):
@@ -555,15 +559,17 @@ def test_cat_accessor_updates_on_inplace(self):
     def test_categorical_delegations(self):
 
         # invalid accessor
-        pytest.raises(AttributeError, lambda: Series([1, 2, 3]).cat)
-        with pytest.raises(AttributeError,
-                           match=(r"Can only use .cat accessor "
-                                  r"with a 'category' dtype")):
+        msg = r"Can only use \.cat accessor with a 'category' dtype"
+        with pytest.raises(AttributeError, match=msg):
+            Series([1, 2, 3]).cat
+        with pytest.raises(AttributeError, match=msg):
             Series([1, 2, 3]).cat()
-        pytest.raises(AttributeError, lambda: Series(['a', 'b', 'c']).cat)
-        pytest.raises(AttributeError, lambda: Series(np.arange(5.)).cat)
-        pytest.raises(AttributeError,
-                      lambda: Series([Timestamp('20130101')]).cat)
+        with pytest.raises(AttributeError, match=msg):
+            Series(['a', 'b', 'c']).cat
+        with pytest.raises(AttributeError, match=msg):
+            Series(np.arange(5.)).cat
+        with pytest.raises(AttributeError, match=msg):
+            Series([Timestamp('20130101')]).cat
 
         # Series should delegate calls to '.categories', '.codes', '.ordered'
         # and the methods '.set_categories()' 'drop_unused_categories()' to the
@@ -605,10 +611,10 @@ def test_categorical_delegations(self):
 
         # This method is likely to be confused, so test that it raises an error
         # on wrong inputs:
-        def f():
+        msg = "'Series' object has no attribute 'set_categories'"
+        with pytest.raises(AttributeError, match=msg):
             s.set_categories([4, 3, 2, 1])
 
-        pytest.raises(Exception, f)
         # right: s.cat.set_categories([4,3,2,1])
 
         # GH18862 (let Series.cat.rename_categories take callables)

pandas/tests/series/test_combine_concat.py

@@ -25,8 +25,9 @@ def test_append(self, datetime_series, string_series, object_series):
             else:
                 raise AssertionError("orphaned index!")
 
-        pytest.raises(ValueError, datetime_series.append, datetime_series,
-                      verify_integrity=True)
+        msg = "Indexes have overlapping values:"
+        with pytest.raises(ValueError, match=msg):
+            datetime_series.append(datetime_series, verify_integrity=True)
 
     def test_append_many(self, datetime_series):
         pieces = [datetime_series[:5], datetime_series[5:10],

pandas/tests/series/test_constructors.py

@@ -65,8 +65,10 @@ def test_constructor(self, datetime_series, empty_series):
 
         assert not empty_series.index.is_all_dates
         assert not Series({}).index.is_all_dates
-        pytest.raises(Exception, Series, np.random.randn(3, 3),
-                      index=np.arange(3))
+
+        # exception raised is of type Exception
+        with pytest.raises(Exception, match="Data must be 1-dimensional"):
+            Series(np.random.randn(3, 3), index=np.arange(3))
 
         mixed.name = 'Series'
         rs = Series(mixed).name
@@ -75,7 +77,9 @@ def test_constructor(self, datetime_series, empty_series):
 
         # raise on MultiIndex GH4187
         m = MultiIndex.from_arrays([[1, 2], [3, 4]])
-        pytest.raises(NotImplementedError, Series, m)
+        msg = "initializing a Series from a MultiIndex is not supported"
+        with pytest.raises(NotImplementedError, match=msg):
+            Series(m)
 
     @pytest.mark.parametrize('input_class', [list, dict, OrderedDict])
     def test_constructor_empty(self, input_class):
@@ -495,7 +499,9 @@ def test_constructor_broadcast_list(self):
         # GH 19342
         # construction with single-element container and index
         # should raise
-        pytest.raises(ValueError, Series, ['foo'], index=['a', 'b', 'c'])
+        msg = "Length of passed values is 1, index implies 3"
+        with pytest.raises(ValueError, match=msg):
+            Series(['foo'], index=['a', 'b', 'c'])
 
     def test_constructor_corner(self):
         df = tm.makeTimeDataFrame()
@@ -675,10 +681,17 @@ def test_constructor_dtype_datetime64(self):
         assert s.dtype == 'M8[ns]'
 
         # GH3414 related
+        # msg = (r"cannot astype a datetimelike from \[datetime64\[ns\]\] to"
+        #        r" \[int32\]")
+        # with pytest.raises(TypeError, match=msg):
+        #     Series(Series(dates).astype('int') / 1000000, dtype='M8[ms]')
         pytest.raises(TypeError, lambda x: Series(
             Series(dates).astype('int') / 1000000, dtype='M8[ms]'))
-        pytest.raises(TypeError,
-                      lambda x: Series(dates, dtype='datetime64'))
+
+        msg = (r"The 'datetime64' dtype has no unit\. Please pass in"
+               r" 'datetime64\[ns\]' instead\.")
+        with pytest.raises(ValueError, match=msg):
+            Series(dates, dtype='datetime64')
 
         # invalid dates can be help as object
         result = Series([datetime(2, 1, 1)])
@@ -984,9 +997,11 @@ def test_constructor_dict_of_tuples(self):
 
     def test_constructor_set(self):
         values = {1, 2, 3, 4, 5}
-        pytest.raises(TypeError, Series, values)
+        with pytest.raises(TypeError, match="'set' type is unordered"):
+            Series(values)
         values = frozenset(values)
-        pytest.raises(TypeError, Series, values)
+        with pytest.raises(TypeError, match="'frozenset' type is unordered"):
+            Series(values)
 
     # https://github.com/pandas-dev/pandas/issues/22698
     @pytest.mark.filterwarnings("ignore:elementwise comparison:FutureWarning")
@@ -1081,14 +1096,16 @@ def test_constructor_dtype_timedelta64(self):
         td.astype('int64')
 
         # invalid casting
-        pytest.raises(TypeError, td.astype, 'int32')
+        msg = (r"cannot astype a timedelta from \[timedelta64\[ns\]\] to"
+               r" \[int32\]")
+        with pytest.raises(TypeError, match=msg):
+            td.astype('int32')
 
         # this is an invalid casting
-        def f():
+        msg = "Could not convert object to NumPy timedelta"
+        with pytest.raises(ValueError, match=msg):
             Series([timedelta(days=1), 'foo'], dtype='m8[ns]')
 
-        pytest.raises(Exception, f)
-
         # leave as object here
         td = Series([timedelta(days=i) for i in range(3)] + ['foo'])
         assert td.dtype == 'object'
@@ -1134,9 +1151,11 @@ def test_constructor_name_hashable(self):
                 assert s.name == n
 
     def test_constructor_name_unhashable(self):
+        msg = r"Series\.name must be a hashable type"
         for n in [['name_list'], np.ones(2), {1: 2}]:
             for data in [['name_list'], np.ones(2), {1: 2}]:
-                pytest.raises(TypeError, Series, data, name=n)
+                with pytest.raises(TypeError, match=msg):
+                    Series(data, name=n)
 
     def test_auto_conversion(self):
         series = Series(list(date_range('1/1/2000', periods=10)))