Require EAs to implement _from_sequence_of_strings to be used in parsers

Author: kprestel

pandas/_libs/parsers.pyx

@@ -1223,8 +1223,12 @@ cdef class TextReader:
                 result = dtype.construct_array_type() \
                               ._from_sequence_of_strings(result, dtype=dtype)
             except NotImplementedError:
-                result = dtype.construct_array_type() \
-                              ._from_sequence(result, dtype=dtype)
+                raise NotImplementedError(
+                        "Extension Array: {ea} must implement "
+                        "_from_sequence_of_strings in order "
+                        "to be used in parser methods".format(
+                                ea=dtype.construct_array_type()))
+
             return result, na_count
 
         elif is_integer_dtype(dtype):

pandas/core/arrays/base.py

@@ -125,7 +125,7 @@ def _from_sequence(cls, scalars, dtype=None, copy=False):
 
     @classmethod
     def _from_sequence_of_strings(cls, strings, dtype=None, copy=False):
-        """Construct a new ExtensionArray from a sequence of scalars.
+        """Construct a new ExtensionArray from a sequence of strings.
 
         .. versionadded:: 0.24.0
 
@@ -145,7 +145,7 @@ def _from_sequence_of_strings(cls, strings, dtype=None, copy=False):
         ExtensionArray
 
         """
-        raise AbstractMethodError(cls)
+        raise NotImplementedError(cls)
 
     @classmethod
     def _from_factorized(cls, values, original):

pandas/core/arrays/integer.py

@@ -267,7 +267,7 @@ def _from_sequence(cls, scalars, dtype=None, copy=False):
 
     @classmethod
     def _from_sequence_of_strings(cls, strings, dtype=None, copy=False):
-        scalars = to_numeric(strings, errors='raise')
+        scalars = to_numeric(strings, errors="raise")
         return cls._from_sequence(scalars, dtype, copy)
 
     @classmethod

pandas/core/dtypes/cast.py

@@ -4,7 +4,6 @@
 
 import numpy as np
 
-from pandas.errors import AbstractMethodError
 from pandas._libs import lib, tslib, tslibs
 from pandas._libs.tslibs import OutOfBoundsDatetime, Period, iNaT
 from pandas.compat import PY3, string_types, text_type, to_str

pandas/tests/extension/base/io.py

@@ -35,4 +35,3 @@ def test_EA_types(self, engine, data):
         result = pd.read_csv(StringIO(data), dtype={'Int': str(data.dtype)},
                              engine=engine)
         assert result is not None
-

pandas/tests/extension/test_common.py

@@ -7,6 +7,27 @@
 import pandas as pd
 from pandas.core.arrays import ExtensionArray
 import pandas.util.testing as tm
+from pandas.compat import StringIO
+from pandas.core.arrays.integer import (
+    Int8Dtype, Int16Dtype, Int32Dtype, Int64Dtype, UInt8Dtype, UInt16Dtype,
+    UInt32Dtype, UInt64Dtype, integer_array,
+)
+
+
+def make_data():
+    return (list(range(1, 9)) + [np.nan] + list(range(10, 98))
+            + [np.nan] + [99, 100])
+
+
+@pytest.fixture(params=[Int8Dtype, Int16Dtype, Int32Dtype, Int64Dtype,
+                        UInt8Dtype, UInt16Dtype, UInt32Dtype, UInt64Dtype])
+def dtype(request):
+    return request.param()
+
+
+@pytest.fixture
+def data(dtype):
+    return integer_array(make_data(), dtype=dtype)
 
 
 class DummyDtype(dtypes.ExtensionDtype):
@@ -92,3 +113,22 @@ def test_is_not_extension_array_dtype(dtype):
 def test_is_extension_array_dtype(dtype):
     assert isinstance(dtype, dtypes.ExtensionDtype)
     assert is_extension_array_dtype(dtype)
+
+
+@pytest.mark.parametrize('engine', ['c', 'python'])
+def test_EA_types(engine):
+    df = pd.DataFrame({'Int': pd.Series([1, 2, 3], dtype='Int64'),
+                       'A': [1, 2, 1]})
+    data = df.to_csv(index=False)
+    result = pd.read_csv(StringIO(data), dtype={'Int': Int64Dtype},
+                         engine=engine)
+    assert result is not None
+    tm.assert_frame_equal(result, df)
+
+    df = pd.DataFrame({'Int': pd.Series([1, 2, 3], dtype='Int8'),
+                       'A': [1, 2, 1]})
+    data = df.to_csv(index=False)
+    result = pd.read_csv(StringIO(data), dtype={'Int': 'Int8'},
+                         engine=engine)
+    assert result is not None
+    tm.assert_frame_equal(result, df)