DEPR: remove Index fastpath kwarg (#29725)

Author: jbrockmendel

doc/source/whatsnew/v1.0.0.rst

@@ -403,6 +403,7 @@ or ``matplotlib.Axes.plot``. See :ref:`plotting.formatters` for more.
 
 - Floordiv of integer-dtyped array by :class:`Timedelta` now raises ``TypeError`` (:issue:`21036`)
 - Removed the previously deprecated :meth:`Index.summary` (:issue:`18217`)
+- Removed the previously deprecated "fastpath" keyword from the :class:`Index` constructor (:issue:`23110`)
 - Removed the previously deprecated :meth:`Series.get_value`, :meth:`Series.set_value`, :meth:`DataFrame.get_value`, :meth:`DataFrame.set_value` (:issue:`17739`)
 - Changed the the default value of `inplace` in :meth:`DataFrame.set_index` and :meth:`Series.set_axis`. It now defaults to False (:issue:`27600`)
 - Removed support for nested renaming in :meth:`DataFrame.aggregate`, :meth:`Series.aggregate`, :meth:`DataFrameGroupBy.aggregate`, :meth:`SeriesGroupBy.aggregate`, :meth:`Rolling.aggregate` (:issue:`18529`)

pandas/conftest.py

@@ -868,3 +868,16 @@ def float_frame():
     [30 rows x 4 columns]
     """
     return DataFrame(tm.getSeriesData())
+
+
+@pytest.fixture(params=[pd.Index, pd.Series], ids=["index", "series"])
+def index_or_series(request):
+    """
+    Fixture to parametrize over Index and Series, made necessary by a mypy
+    bug, giving an error:
+
+    List item 0 has incompatible type "Type[Series]"; expected "Type[PandasObject]"
+
+    See GH#?????
+    """
+    return request.param

pandas/core/indexes/base.py

@@ -265,14 +265,7 @@ def _outer_indexer(self, left, right):
     # Constructors
 
     def __new__(
-        cls,
-        data=None,
-        dtype=None,
-        copy=False,
-        name=None,
-        fastpath=None,
-        tupleize_cols=True,
-        **kwargs,
+        cls, data=None, dtype=None, copy=False, name=None, tupleize_cols=True, **kwargs,
     ) -> "Index":
 
         from .range import RangeIndex
@@ -284,16 +277,6 @@ def __new__(
         if name is None and hasattr(data, "name"):
             name = data.name
 
-        if fastpath is not None:
-            warnings.warn(
-                "The 'fastpath' keyword is deprecated, and will be "
-                "removed in a future version.",
-                FutureWarning,
-                stacklevel=2,
-            )
-            if fastpath:
-                return cls._simple_new(data, name)
-
         if isinstance(data, ABCPandasArray):
             # ensure users don't accidentally put a PandasArray in an index.
             data = data.to_numpy()

pandas/core/indexes/category.py

@@ -1,6 +1,5 @@
 import operator
 from typing import Any
-import warnings
 
 import numpy as np
 
@@ -172,19 +171,8 @@ def __new__(
         dtype=None,
         copy=False,
         name=None,
-        fastpath=None,
     ):
 
-        if fastpath is not None:
-            warnings.warn(
-                "The 'fastpath' keyword is deprecated, and will be "
-                "removed in a future version.",
-                FutureWarning,
-                stacklevel=2,
-            )
-            if fastpath:
-                return cls._simple_new(data, name=name, dtype=dtype)
-
         dtype = CategoricalDtype._from_values_or_dtype(data, categories, ordered, dtype)
 
         if name is None and hasattr(data, "name"):

pandas/core/indexes/numeric.py

@@ -1,5 +1,3 @@
-import warnings
-
 import numpy as np
 
 from pandas._libs import index as libindex
@@ -47,17 +45,8 @@ class NumericIndex(Index):
 
     _is_numeric_dtype = True
 
-    def __new__(cls, data=None, dtype=None, copy=False, name=None, fastpath=None):
+    def __new__(cls, data=None, dtype=None, copy=False, name=None):
         cls._validate_dtype(dtype)
-        if fastpath is not None:
-            warnings.warn(
-                "The 'fastpath' keyword is deprecated, and will be "
-                "removed in a future version.",
-                FutureWarning,
-                stacklevel=2,
-            )
-            if fastpath:
-                return cls._simple_new(data, name=name)
 
         # Coerce to ndarray if not already ndarray or Index
         if not isinstance(data, (np.ndarray, Index)):

pandas/core/indexes/range.py

@@ -81,26 +81,9 @@ class RangeIndex(Int64Index):
     # Constructors
 
     def __new__(
-        cls,
-        start=None,
-        stop=None,
-        step=None,
-        dtype=None,
-        copy=False,
-        name=None,
-        fastpath=None,
+        cls, start=None, stop=None, step=None, dtype=None, copy=False, name=None,
     ):
 
-        if fastpath is not None:
-            warnings.warn(
-                "The 'fastpath' keyword is deprecated, and will be "
-                "removed in a future version.",
-                FutureWarning,
-                stacklevel=2,
-            )
-            if fastpath:
-                return cls._simple_new(range(start, stop, step), name=name)
-
         cls._validate_dtype(dtype)
 
         # RangeIndex

pandas/tests/arithmetic/test_numeric.py

@@ -5,6 +5,7 @@
 from decimal import Decimal
 from itertools import combinations
 import operator
+from typing import Any, List
 
 import numpy as np
 import pytest
@@ -30,6 +31,19 @@ def adjust_negative_zero(zero, expected):
     return expected
 
 
+# TODO: remove this kludge once mypy stops giving false positives here
+# List comprehension has incompatible type List[PandasObject]; expected List[RangeIndex]
+#  See GH#?????
+ser_or_index: List[Any] = [pd.Series, pd.Index]
+lefts: List[Any] = [pd.RangeIndex(10, 40, 10)]
+lefts.extend(
+    [
+        cls([10, 20, 30], dtype=dtype)
+        for dtype in ["i1", "i2", "i4", "i8", "u1", "u2", "u4", "u8", "f2", "f4", "f8"]
+        for cls in ser_or_index
+    ]
+)
+
 # ------------------------------------------------------------------
 # Comparisons
 
@@ -81,26 +95,7 @@ class TestNumericArraylikeArithmeticWithDatetimeLike:
     # TODO: also check name retentention
     @pytest.mark.parametrize("box_cls", [np.array, pd.Index, pd.Series])
     @pytest.mark.parametrize(
-        "left",
-        [pd.RangeIndex(10, 40, 10)]
-        + [
-            cls([10, 20, 30], dtype=dtype)
-            for dtype in [
-                "i1",
-                "i2",
-                "i4",
-                "i8",
-                "u1",
-                "u2",
-                "u4",
-                "u8",
-                "f2",
-                "f4",
-                "f8",
-            ]
-            for cls in [pd.Series, pd.Index]
-        ],
-        ids=lambda x: type(x).__name__ + str(x.dtype),
+        "left", lefts, ids=lambda x: type(x).__name__ + str(x.dtype),
     )
     def test_mul_td64arr(self, left, box_cls):
         # GH#22390
@@ -120,26 +115,7 @@ def test_mul_td64arr(self, left, box_cls):
     # TODO: also check name retentention
     @pytest.mark.parametrize("box_cls", [np.array, pd.Index, pd.Series])
     @pytest.mark.parametrize(
-        "left",
-        [pd.RangeIndex(10, 40, 10)]
-        + [
-            cls([10, 20, 30], dtype=dtype)
-            for dtype in [
-                "i1",
-                "i2",
-                "i4",
-                "i8",
-                "u1",
-                "u2",
-                "u4",
-                "u8",
-                "f2",
-                "f4",
-                "f8",
-            ]
-            for cls in [pd.Series, pd.Index]
-        ],
-        ids=lambda x: type(x).__name__ + str(x.dtype),
+        "left", lefts, ids=lambda x: type(x).__name__ + str(x.dtype),
     )
     def test_div_td64arr(self, left, box_cls):
         # GH#22390

pandas/tests/arrays/test_array.py

@@ -272,8 +272,9 @@ def _from_sequence(cls, scalars, dtype=None, copy=False):
         return super()._from_sequence(scalars, dtype=dtype, copy=copy)
 
 
-@pytest.mark.parametrize("box", [pd.Series, pd.Index])
-def test_array_unboxes(box):
+def test_array_unboxes(index_or_series):
+    box = index_or_series
+
     data = box([decimal.Decimal("1"), decimal.Decimal("2")])
     # make sure it works
     with pytest.raises(TypeError):

pandas/tests/dtypes/test_concat.py

@@ -2,7 +2,7 @@
 
 import pandas.core.dtypes.concat as _concat
 
-from pandas import DatetimeIndex, Index, Period, PeriodIndex, Series, TimedeltaIndex
+from pandas import DatetimeIndex, Period, PeriodIndex, Series, TimedeltaIndex
 
 
 @pytest.mark.parametrize(
@@ -40,9 +40,8 @@
         ),
     ],
 )
-@pytest.mark.parametrize("klass", [Index, Series])
-def test_get_dtype_kinds(klass, to_concat, expected):
-    to_concat_klass = [klass(c) for c in to_concat]
+def test_get_dtype_kinds(index_or_series, to_concat, expected):
+    to_concat_klass = [index_or_series(c) for c in to_concat]
     result = _concat.get_dtype_kinds(to_concat_klass)
     assert result == set(expected)
 

pandas/tests/indexes/test_base.py

@@ -2762,32 +2762,18 @@ def test_index_subclass_constructor_wrong_kwargs(index_maker):
 
 
 def test_deprecated_fastpath():
+    msg = "[Uu]nexpected keyword argument"
+    with pytest.raises(TypeError, match=msg):
+        pd.Index(np.array(["a", "b"], dtype=object), name="test", fastpath=True)
 
-    with tm.assert_produces_warning(FutureWarning):
-        idx = pd.Index(np.array(["a", "b"], dtype=object), name="test", fastpath=True)
+    with pytest.raises(TypeError, match=msg):
+        pd.Int64Index(np.array([1, 2, 3], dtype="int64"), name="test", fastpath=True)
 
-    expected = pd.Index(["a", "b"], name="test")
-    tm.assert_index_equal(idx, expected)
+    with pytest.raises(TypeError, match=msg):
+        pd.RangeIndex(0, 5, 2, name="test", fastpath=True)
 
-    with tm.assert_produces_warning(FutureWarning):
-        idx = pd.Int64Index(
-            np.array([1, 2, 3], dtype="int64"), name="test", fastpath=True
-        )
-
-    expected = pd.Index([1, 2, 3], name="test", dtype="int64")
-    tm.assert_index_equal(idx, expected)
-
-    with tm.assert_produces_warning(FutureWarning):
-        idx = pd.RangeIndex(0, 5, 2, name="test", fastpath=True)
-
-    expected = pd.RangeIndex(0, 5, 2, name="test")
-    tm.assert_index_equal(idx, expected)
-
-    with tm.assert_produces_warning(FutureWarning):
-        idx = pd.CategoricalIndex(["a", "b", "c"], name="test", fastpath=True)
-
-    expected = pd.CategoricalIndex(["a", "b", "c"], name="test")
-    tm.assert_index_equal(idx, expected)
+    with pytest.raises(TypeError, match=msg):
+        pd.CategoricalIndex(["a", "b", "c"], name="test", fastpath=True)
 
 
 def test_shape_of_invalid_index():