REF: consolidate paths for astype

pandas/core/arrays/datetimelike.py

@@ -60,6 +60,7 @@
     Substitution,
     cache_readonly,
 )
+from pandas.util._exceptions import find_stack_level
 
 from pandas.core.dtypes.common import (
     is_categorical_dtype,
@@ -397,12 +398,13 @@ def astype(self, dtype, copy=True):
         elif is_integer_dtype(dtype):
             # we deliberately ignore int32 vs. int64 here.
             # See https://github.com/pandas-dev/pandas/issues/24381 for more.
+            level = find_stack_level()
             warnings.warn(
                 f"casting {self.dtype} values to int64 with .astype(...) is "
                 "deprecated and will raise in a future version. "
                 "Use .view(...) instead.",
                 FutureWarning,
-                stacklevel=3,
+                stacklevel=level,
             )
 
             values = self.asi8

pandas/core/arrays/datetimes.py

@@ -616,6 +616,10 @@ def astype(self, dtype, copy=True):
         elif is_datetime64_ns_dtype(dtype):
             return astype_dt64_to_dt64tz(self, dtype, copy, via_utc=False)
 
+        elif self.tz is None and is_datetime64_dtype(dtype) and dtype != self.dtype:
+            # unit conversion e.g. datetime64[s]
+            return self._data.astype(dtype)
+
         elif is_period_dtype(dtype):
             return self.to_period(freq=dtype.freq)
         return dtl.DatetimeLikeArrayMixin.astype(self, dtype, copy)

pandas/core/indexes/extension.py

@@ -309,6 +309,10 @@ def astype(self, dtype, copy=True):
                 return self
             return self.copy()
 
+        if isinstance(dtype, np.dtype) and dtype.kind == "M" and dtype != "M8[ns]":
+            # For now Datetime supports this by unwrapping ndarray, but DTI doesn't
+            raise TypeError(f"Cannot cast {type(self._data).__name__} to dtype")
+
         new_values = self._data.astype(dtype, copy=copy)
 
         # pass copy=False because any copying will be done in the

pandas/core/internals/blocks.py

@@ -673,6 +673,18 @@ def astype(self, dtype, copy: bool = False, errors: str = "raise"):
 
     def _astype(self, dtype: DtypeObj, copy: bool) -> ArrayLike:
         values = self.values
+        if values.dtype.kind in ["m", "M"]:
+            values = self.array_values()
+
+        if (
+            values.dtype.kind in ["m", "M"]
+            and dtype.kind in ["i", "u"]
+            and isinstance(dtype, np.dtype)
+            and dtype.itemsize != 8
+        ):
+            # TODO(2.0) remove special case once deprecation on DTA/TDA is enforced
+            msg = rf"cannot astype a datetimelike from [{values.dtype}] to [{dtype}]"
+            raise TypeError(msg)
 
         if is_datetime64tz_dtype(dtype) and is_datetime64_dtype(values.dtype):
             return astype_dt64_to_dt64tz(values, dtype, copy, via_utc=True)

pandas/tests/frame/methods/test_astype.py

@@ -432,19 +432,11 @@ def test_astype_to_incorrect_datetimelike(self, unit):
         other = f"m8[{unit}]"
 
         df = DataFrame(np.array([[1, 2, 3]], dtype=dtype))
-        msg = (
-            fr"cannot astype a datetimelike from \[datetime64\[ns\]\] to "
-            fr"\[timedelta64\[{unit}\]\]"
-            fr"|(Cannot cast DatetimeArray to dtype timedelta64\[{unit}\])"
-        )
+        msg = fr"Cannot cast DatetimeArray to dtype timedelta64\[{unit}\]"
         with pytest.raises(TypeError, match=msg):
             df.astype(other)
 
-        msg = (
-            fr"cannot astype a timedelta from \[timedelta64\[ns\]\] to "
-            fr"\[datetime64\[{unit}\]\]"
-            fr"|(Cannot cast TimedeltaArray to dtype datetime64\[{unit}\])"
-        )
+        msg = fr"Cannot cast TimedeltaArray to dtype datetime64\[{unit}\]"
         df = DataFrame(np.array([[1, 2, 3]], dtype=other))
         with pytest.raises(TypeError, match=msg):
             df.astype(dtype)

pandas/tests/indexes/datetimes/methods/test_astype.py

@@ -29,7 +29,7 @@ def test_astype(self):
         )
         tm.assert_index_equal(result, expected)
 
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+        with tm.assert_produces_warning(FutureWarning):
             result = idx.astype(int)
         expected = Int64Index(
             [1463356800000000000] + [-9223372036854775808] * 3,
@@ -39,7 +39,7 @@ def test_astype(self):
         tm.assert_index_equal(result, expected)
 
         rng = date_range("1/1/2000", periods=10, name="idx")
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+        with tm.assert_produces_warning(FutureWarning):
             result = rng.astype("i8")
         tm.assert_index_equal(result, Index(rng.asi8, name="idx"))
         tm.assert_numpy_array_equal(result.values, rng.asi8)
@@ -50,7 +50,7 @@ def test_astype_uint(self):
             np.array([946684800000000000, 946771200000000000], dtype="uint64"),
             name="idx",
         )
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+        with tm.assert_produces_warning(FutureWarning):
             tm.assert_index_equal(arr.astype("uint64"), expected)
             tm.assert_index_equal(arr.astype("uint32"), expected)
 

pandas/tests/indexes/period/methods/test_astype.py

@@ -37,7 +37,7 @@ def test_astype_conversion(self):
         )
         tm.assert_index_equal(result, expected)
 
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+        with tm.assert_produces_warning(FutureWarning):
             result = idx.astype(np.int64)
         expected = Int64Index(
             [16937] + [-9223372036854775808] * 3, dtype=np.int64, name="idx"
@@ -49,15 +49,15 @@ def test_astype_conversion(self):
         tm.assert_index_equal(result, expected)
 
         idx = period_range("1990", "2009", freq="A", name="idx")
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+        with tm.assert_produces_warning(FutureWarning):
             result = idx.astype("i8")
         tm.assert_index_equal(result, Index(idx.asi8, name="idx"))
         tm.assert_numpy_array_equal(result.values, idx.asi8)
 
     def test_astype_uint(self):
         arr = period_range("2000", periods=2, name="idx")
         expected = UInt64Index(np.array([10957, 10958], dtype="uint64"), name="idx")
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+        with tm.assert_produces_warning(FutureWarning):
             tm.assert_index_equal(arr.astype("uint64"), expected)
             tm.assert_index_equal(arr.astype("uint32"), expected)
 

pandas/tests/indexes/timedeltas/methods/test_astype.py

@@ -55,7 +55,7 @@ def test_astype(self):
         )
         tm.assert_index_equal(result, expected)
 
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+        with tm.assert_produces_warning(FutureWarning):
             result = idx.astype(int)
         expected = Int64Index(
             [100000000000000] + [-9223372036854775808] * 3, dtype=np.int64, name="idx"
@@ -67,7 +67,7 @@ def test_astype(self):
         tm.assert_index_equal(result, expected)
 
         rng = timedelta_range("1 days", periods=10)
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+        with tm.assert_produces_warning(FutureWarning):
             result = rng.astype("i8")
         tm.assert_index_equal(result, Index(rng.asi8))
         tm.assert_numpy_array_equal(rng.asi8, result.values)
@@ -77,7 +77,7 @@ def test_astype_uint(self):
         expected = pd.UInt64Index(
             np.array([3600000000000, 90000000000000], dtype="uint64")
         )
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+        with tm.assert_produces_warning(FutureWarning):
             tm.assert_index_equal(arr.astype("uint64"), expected)
             tm.assert_index_equal(arr.astype("uint32"), expected)
 

pandas/tests/series/test_constructors.py

@@ -1318,7 +1318,7 @@ def test_constructor_dtype_timedelta64(self):
             td.astype("int64")
 
         # invalid casting
-        msg = r"cannot astype a timedelta from \[timedelta64\[ns\]\] to \[int32\]"
+        msg = r"cannot astype a datetimelike from \[timedelta64\[ns\]\] to \[int32\]"
         with pytest.raises(TypeError, match=msg):
             td.astype("int32")