remove astype and isin changes

pandas-dev · Dr-Irv · Jan 23, 2021 · Jan 23, 2021 · Jan 31, 2021 · Jan 31, 2021
commit ad1ab3b8c381d6f3c36063f6c5cf1d6116730f77
diff --git a/pandas/_testing/asserters.py b/pandas/_testing/asserters.py
@@ -382,13 +382,9 @@ def _get_ilevel_values(index, level):
     # skip exact index checking when `check_categorical` is False
     if check_exact and check_categorical:
         if not left.equals(right):
-            #  error: Value of type variable "_Number" of "sum" cannot be
-            # "Union[ExtensionArray, ndarray, Any]"
-            thesum = np.sum(
-                (left._values != right._values).astype(int)
-            )  # type: ignore[type-var]
-            # error: Unsupported operand types for * ("ExtensionArray" and "float")
-            diff = thesum * 100.0 / len(left)  # type: ignore[operator]
+            diff = (
+                np.sum((left._values != right._values).astype(int)) * 100.0 / len(left)
+            )
             msg = f"{obj} values are different ({np.round(diff, 5)} %)"
             raise_assert_detail(obj, msg, left, right)
     else:

diff --git a/pandas/_typing.py b/pandas/_typing.py
@@ -76,13 +76,7 @@
 
 ArrayLike = Union["ExtensionArray", np.ndarray]
 AnyArrayLike = Union[ArrayLike, "Index", "Series"]
-AnySequenceLike = Union[
-    "ExtensionArray",
-    "Index",
-    "Series",
-    Sequence[Any],
-    np.ndarray,
-]
+
 # scalars
 
 PythonScalar = Union[str, int, float, bool]

diff --git a/pandas/core/algorithms.py b/pandas/core/algorithms.py
@@ -30,7 +30,6 @@
 )
 from pandas._typing import (
     AnyArrayLike,
-    AnySequenceLike,
     ArrayLike,
     DtypeObj,
     FrameOrSeriesUnion,
@@ -447,7 +446,7 @@ def unique(values):
 unique1d = unique
 
 
-def isin(comps: AnySequenceLike, values: AnySequenceLike) -> np.ndarray:
+def isin(comps: AnyArrayLike, values: AnyArrayLike) -> np.ndarray:
     """
     Compute the isin boolean array.
 

diff --git a/pandas/core/arrays/base.py b/pandas/core/arrays/base.py
@@ -525,15 +525,7 @@ def nbytes(self) -> int:
     # ------------------------------------------------------------------------
     # Additional Methods
     # ------------------------------------------------------------------------
-    @overload
-    def astype(self, dtype: Type[str], copy: bool = True) -> np.ndarray:
-        ...
-
-    @overload
-    def astype(self, dtype: Dtype, copy: bool = True) -> ArrayLike:
-        ...
-
-    def astype(self, dtype: Dtype, copy: bool = True) -> ArrayLike:
+    def astype(self, dtype: Dtype, copy: bool = True):
         """
         Cast to a NumPy array with 'dtype'.
 
@@ -933,7 +925,9 @@ def isin(self, values: Sequence[Any]) -> np.ndarray:
         -------
         np.ndarray[bool]
         """
-        return isin(self.astype(object), values)
+        # error: Argument 2 to "isin" has incompatible type "Sequence[Any]"; expected
+        # "Union[Union[ExtensionArray, ndarray], Index, Series]"
+        return isin(self.astype(object), values)  # type: ignore[arg-type]
 
     def _values_for_factorize(self) -> Tuple[np.ndarray, Any]:
         """

diff --git a/pandas/core/arrays/boolean.py b/pandas/core/arrays/boolean.py
@@ -8,7 +8,6 @@
     Tuple,
     Type,
     Union,
-    overload,
 )
 import warnings
 
@@ -381,14 +380,6 @@ def reconstruct(x):
     def _coerce_to_array(self, value) -> Tuple[np.ndarray, np.ndarray]:
         return coerce_to_array(value)
 
-    @overload
-    def astype(self, dtype: Type[str], copy: bool = True) -> np.ndarray:
-        ...
-
-    @overload
-    def astype(self, dtype: Dtype, copy: bool = True) -> ArrayLike:
-        ...
-
     def astype(self, dtype: Dtype, copy: bool = True) -> ArrayLike:
         """
         Cast to a NumPy array or ExtensionArray with 'dtype'.

diff --git a/pandas/core/arrays/categorical.py b/pandas/core/arrays/categorical.py
@@ -15,7 +15,6 @@
     TypeVar,
     Union,
     cast,
-    overload,
 )
 from warnings import warn
 
@@ -483,14 +482,6 @@ def _constructor(self) -> Type[Categorical]:
     def _from_sequence(cls, scalars, *, dtype: Optional[Dtype] = None, copy=False):
         return Categorical(scalars, dtype=dtype, copy=copy)
 
-    @overload
-    def astype(self, dtype: Type[str], copy: bool = True) -> np.ndarray:
-        ...
-
-    @overload
-    def astype(self, dtype: Dtype, copy: bool = True) -> ArrayLike:
-        ...
-
     def astype(self, dtype: Dtype, copy: bool = True) -> ArrayLike:
         """
         Coerce this type to another dtype
@@ -2453,7 +2444,11 @@ def _str_get_dummies(self, sep="|"):
         # sep may not be in categories. Just bail on this.
         from pandas.core.arrays import PandasArray
 
-        return PandasArray(self.astype(str))._str_get_dummies(sep)
+        # error: Argument 1 to "PandasArray" has incompatible type
+        # "ExtensionArray"; expected "Union[ndarray, PandasArray]"
+        return PandasArray(self.astype(str))._str_get_dummies(  # type: ignore[arg-type]
+            sep
+        )
 
 
 # The Series.cat accessor

diff --git a/pandas/core/arrays/floating.py b/pandas/core/arrays/floating.py
@@ -5,7 +5,6 @@
     Optional,
     Tuple,
     Type,
-    overload,
 )
 import warnings
 
@@ -279,14 +278,6 @@ def _from_sequence_of_strings(
     def _coerce_to_array(self, value) -> Tuple[np.ndarray, np.ndarray]:
         return coerce_to_array(value, dtype=self.dtype)
 
-    @overload
-    def astype(self, dtype: Type[str], copy: bool = True) -> np.ndarray:
-        ...
-
-    @overload
-    def astype(self, dtype: Dtype, copy: bool = True) -> ArrayLike:
-        ...
-
     def astype(self, dtype: Dtype, copy: bool = True) -> ArrayLike:
         """
         Cast to a NumPy array or ExtensionArray with 'dtype'.

diff --git a/pandas/core/arrays/integer.py b/pandas/core/arrays/integer.py
@@ -6,7 +6,6 @@
     Optional,
     Tuple,
     Type,
-    overload,
 )
 import warnings
 
@@ -343,14 +342,6 @@ def _from_sequence_of_strings(
     def _coerce_to_array(self, value) -> Tuple[np.ndarray, np.ndarray]:
         return coerce_to_array(value, dtype=self.dtype)
 
-    @overload
-    def astype(self, dtype: Type[str], copy: bool = True) -> np.ndarray:
-        ...
-
-    @overload
-    def astype(self, dtype: Dtype, copy: bool = True) -> ArrayLike:
-        ...
-
     def astype(self, dtype, copy: bool = True) -> ArrayLike:
         """
         Cast to a NumPy array or ExtensionArray with 'dtype'.

diff --git a/pandas/core/arrays/masked.py b/pandas/core/arrays/masked.py
@@ -10,7 +10,6 @@
     Type,
     TypeVar,
     Union,
-    overload,
 )
 
 import numpy as np
@@ -305,14 +304,6 @@ def to_numpy(
             data = self._data.astype(dtype, copy=copy)
         return data
 
-    @overload
-    def astype(self, dtype: Type[str], copy: bool = True) -> np.ndarray:
-        ...
-
-    @overload
-    def astype(self, dtype: Dtype, copy: bool = True) -> ArrayLike:
-        ...
-
     def astype(self, dtype: Dtype, copy: bool = True) -> ArrayLike:
         dtype = pandas_dtype(dtype)
 

diff --git a/pandas/core/dtypes/common.py b/pandas/core/dtypes/common.py
@@ -3,11 +3,9 @@
 """
 
 from typing import (
-    TYPE_CHECKING,
     Any,
     Callable,
     Union,
-    cast,
 )
 import warnings
 
@@ -60,9 +58,6 @@
     is_sequence,
 )
 
-if TYPE_CHECKING:
-    from pandas.core.arrays.base import ExtensionArray
-
 POSSIBLY_CAST_DTYPES = {
     np.dtype(t).name
     for t in [
@@ -160,18 +155,22 @@ def ensure_int_or_float(arr: ArrayLike, copy: bool = False) -> ArrayLike:
     will remain unchanged.
     """
     # TODO: GH27506 potential bug with ExtensionArrays
-    if is_extension_array_dtype(arr.dtype):
-        return cast("ExtensionArray", arr).to_numpy(dtype="float64", na_value=np.nan)
-    else:
-        assert isinstance(arr, np.ndarray)  # For typing
-        try:
-            return arr.astype("int64", copy=copy, casting="safe")
-        except TypeError:
-            pass
-        try:
-            return arr.astype("uint64", copy=copy, casting="safe")
-        except TypeError:
-            return arr.astype("float64", copy=copy)
+    try:
+        # error: Unexpected keyword argument "casting" for "astype"
+        return arr.astype("int64", copy=copy, casting="safe")  # type: ignore[call-arg]
+    except TypeError:
+        pass
+    try:
+        # error: Unexpected keyword argument "casting" for "astype"
+        return arr.astype("uint64", copy=copy, casting="safe")  # type: ignore[call-arg]
+    except TypeError:
+        if is_extension_array_dtype(arr.dtype):
+            # pandas/core/dtypes/common.py:168: error: Item "ndarray" of
+            # "Union[ExtensionArray, ndarray]" has no attribute "to_numpy"  [union-attr]
+            return arr.to_numpy(  # type: ignore[union-attr]
+                dtype="float64", na_value=np.nan
+            )
+        return arr.astype("float64", copy=copy)
 
 
 def ensure_python_int(value: Union[int, np.integer]) -> int:

diff --git a/pandas/core/internals/blocks.py b/pandas/core/internals/blocks.py
@@ -239,9 +239,7 @@ def get_values(self, dtype: Optional[DtypeObj] = None) -> np.ndarray:
         this is often overridden to handle to_dense like operations
         """
         if dtype == _dtype_obj:
-            # error: Incompatible return value type (got "Union[ndarray,
-            # ExtensionArray]", expected "ndarray")
-            return self.values.astype(_dtype_obj)  # type: ignore[return-value]
+            return self.values.astype(_dtype_obj)
         # error: Incompatible return value type (got "Union[ndarray, ExtensionArray]",
         # expected "ndarray")
         return self.values  # type: ignore[return-value]

diff --git a/pandas/core/tools/datetimes.py b/pandas/core/tools/datetimes.py
@@ -1075,7 +1075,9 @@ def calc_with_mask(carg, mask):
 
     # string with NaN-like
     try:
-        mask = ~algorithms.isin(arg, list(nat_strings))
+        # error: Argument 2 to "isin" has incompatible type "List[Any]"; expected
+        # "Union[Union[ExtensionArray, ndarray], Index, Series]"
+        mask = ~algorithms.isin(arg, list(nat_strings))  # type: ignore[arg-type]
         return calc_with_mask(arg, mask)
     except (ValueError, OverflowError, TypeError):
         pass

diff --git a/pandas/io/parsers/base_parser.py b/pandas/io/parsers/base_parser.py
@@ -531,7 +531,11 @@ def _convert_to_ndarrays(
                 try:
                     values = lib.map_infer(values, conv_f)
                 except ValueError:
-                    mask = algorithms.isin(values, list(na_values)).view(np.uint8)
+                    # error: Argument 2 to "isin" has incompatible type "List[Any]";
+                    # expected "Union[Union[ExtensionArray, ndarray], Index, Series]"
+                    mask = algorithms.isin(
+                        values, list(na_values)  # type: ignore[arg-type]
+                    ).view(np.uint8)
                     values = lib.map_infer_mask(values, conv_f, mask)
 
                 cvals, na_count = self._infer_types(
@@ -657,7 +661,9 @@ def _infer_types(self, values, na_values, try_num_bool=True):
         """
         na_count = 0
         if issubclass(values.dtype.type, (np.number, np.bool_)):
-            mask = algorithms.isin(values, list(na_values))
+            # error: Argument 2 to "isin" has incompatible type "List[Any]"; expected
+            # "Union[Union[ExtensionArray, ndarray], Index, Series]"
+            mask = algorithms.isin(values, list(na_values))  # type: ignore[arg-type]
             # error: Incompatible types in assignment (expression has type
             # "number[Any]", variable has type "int")
             na_count = mask.sum()  # type: ignore[assignment]