update repr tests

Author: TomAugspurger

doc/source/whatsnew/v0.24.0.txt

@@ -858,7 +858,7 @@ update the ``ExtensionDtype._metadata`` tuple to match the signature of your
 - :meth:`DataFrame.stack` no longer converts to object dtype for DataFrames where each column has the same extension dtype. The output Series will have the same dtype as the columns (:issue:`23077`).
 - :meth:`Series.unstack` and :meth:`DataFrame.unstack` no longer convert extension arrays to object-dtype ndarrays. Each column in the output ``DataFrame`` will now have the same dtype as the input (:issue:`23077`).
 - Bug when grouping :meth:`Dataframe.groupby()` and aggregating on ``ExtensionArray`` it was not returning the actual ``ExtensionArray`` dtype (:issue:`23227`).
-- A default repr for ExtensionArrays is now provided (:issue:`23601`).
+- A default repr for :class:`ExtensionArray` is now provided (:issue:`23601`).
 
 .. _whatsnew_0240.api.incompatibilities:
 

pandas/core/arrays/base.py

@@ -675,7 +675,7 @@ def __unicode__(self):
         # repr does. So we include a newline in our template, and strip
         # any trailing newlines from format_object_summary
         data = format_object_summary(self, self._formatter(), name=False,
-                                     trailing_comma=False).rstrip('\n')
+                                     trailing_comma=False).rstrip()
         name = self.__class__.__name__
         return template.format(class_name=name, data=data,
                                length=len(self),

pandas/tests/arrays/test_integer.py

@@ -57,28 +57,27 @@ def test_dtypes(dtype):
     assert dtype.name is not None
 
 
-def test_repr_array(data):
-    result = repr(data)
-    assert '<IntegerArray>' in result
-
-    # not long
-    assert '...' not in result
-    assert 'Length: ' in result
-    assert 'dtype: ' in result
-
-
-def test_na_repr(data):
-    result = repr(integer_array([1, None]))
-    assert 'NaN' in result
-
+def test_repr_array():
+    result = repr(integer_array([1, None, 3]))
+    expected = (
+        '<IntegerArray>\n'
+        '[1, NaN, 3]\n'
+        'Length: 3, dtype: Int64'
+    )
+    assert result == expected
 
-def test_repr_array_long(data):
-    # some arrays may be able to assert a ... in the repr
-    with pd.option_context('display.max_seq_items', 1):
-        result = repr(data)
 
-        assert '...' in result
-        assert 'Length' in result
+def test_repr_array_long():
+    data = integer_array([1, 2, None] * 1000)
+    expected = (
+        "<IntegerArray>\n"
+        "[  1,   2, NaN,   1,   2, NaN,   1,   2, NaN,   1,\n"
+        " ...\n"
+        " NaN,   1,   2, NaN,   1,   2, NaN,   1,   2, NaN]\n"
+        "Length: 3000, dtype: Int64"
+    )
+    result = repr(data)
+    assert result == expected
 
 
 class TestConstructors(object):