REF: simplify maybe_convert_objects (#53021)

Author: jbrockmendel

pandas/_libs/lib.pyi

@@ -70,45 +70,25 @@ def map_infer(
     convert: bool = ...,
     ignore_na: bool = ...,
 ) -> np.ndarray: ...
-@overload  # all convert_foo False -> only convert numeric
+@overload
 def maybe_convert_objects(
     objects: npt.NDArray[np.object_],
     *,
     try_float: bool = ...,
     safe: bool = ...,
     convert_numeric: bool = ...,
-    convert_datetime: Literal[False] = ...,
-    convert_timedelta: Literal[False] = ...,
-    convert_period: Literal[False] = ...,
-    convert_interval: Literal[False] = ...,
+    convert_non_numeric: Literal[False] = ...,
     convert_to_nullable_dtype: Literal[False] = ...,
     dtype_if_all_nat: DtypeObj | None = ...,
 ) -> npt.NDArray[np.object_ | np.number]: ...
-@overload  # both convert_datetime and convert_to_nullable_integer False -> np.ndarray
-def maybe_convert_objects(
-    objects: npt.NDArray[np.object_],
-    *,
-    try_float: bool = ...,
-    safe: bool = ...,
-    convert_numeric: bool = ...,
-    convert_datetime: Literal[False] = ...,
-    convert_timedelta: bool = ...,
-    convert_period: Literal[False] = ...,
-    convert_interval: Literal[False] = ...,
-    convert_to_nullable_dtype: Literal[False] = ...,
-    dtype_if_all_nat: DtypeObj | None = ...,
-) -> np.ndarray: ...
 @overload
 def maybe_convert_objects(
     objects: npt.NDArray[np.object_],
     *,
     try_float: bool = ...,
     safe: bool = ...,
     convert_numeric: bool = ...,
-    convert_datetime: bool = ...,
-    convert_timedelta: bool = ...,
-    convert_period: bool = ...,
-    convert_interval: bool = ...,
+    convert_non_numeric: bool = ...,
     convert_to_nullable_dtype: Literal[True] = ...,
     dtype_if_all_nat: DtypeObj | None = ...,
 ) -> ArrayLike: ...
@@ -119,38 +99,7 @@ def maybe_convert_objects(
     try_float: bool = ...,
     safe: bool = ...,
     convert_numeric: bool = ...,
-    convert_datetime: Literal[True] = ...,
-    convert_timedelta: bool = ...,
-    convert_period: bool = ...,
-    convert_interval: bool = ...,
-    convert_to_nullable_dtype: bool = ...,
-    dtype_if_all_nat: DtypeObj | None = ...,
-) -> ArrayLike: ...
-@overload
-def maybe_convert_objects(
-    objects: npt.NDArray[np.object_],
-    *,
-    try_float: bool = ...,
-    safe: bool = ...,
-    convert_numeric: bool = ...,
-    convert_datetime: bool = ...,
-    convert_timedelta: bool = ...,
-    convert_period: Literal[True] = ...,
-    convert_interval: bool = ...,
-    convert_to_nullable_dtype: bool = ...,
-    dtype_if_all_nat: DtypeObj | None = ...,
-) -> ArrayLike: ...
-@overload
-def maybe_convert_objects(
-    objects: npt.NDArray[np.object_],
-    *,
-    try_float: bool = ...,
-    safe: bool = ...,
-    convert_numeric: bool = ...,
-    convert_datetime: bool = ...,
-    convert_timedelta: bool = ...,
-    convert_period: bool = ...,
-    convert_interval: bool = ...,
+    convert_non_numeric: bool = ...,
     convert_to_nullable_dtype: bool = ...,
     dtype_if_all_nat: DtypeObj | None = ...,
 ) -> ArrayLike: ...

pandas/_libs/lib.pyx

@@ -2396,11 +2396,8 @@ def maybe_convert_objects(ndarray[object] objects,
                           bint try_float=False,
                           bint safe=False,
                           bint convert_numeric=True,  # NB: different default!
-                          bint convert_datetime=False,
-                          bint convert_timedelta=False,
-                          bint convert_period=False,
-                          bint convert_interval=False,
                           bint convert_to_nullable_dtype=False,
+                          bint convert_non_numeric=False,
                           object dtype_if_all_nat=None) -> "ArrayLike":
     """
     Type inference function-- convert object array to proper dtype
@@ -2417,21 +2414,11 @@ def maybe_convert_objects(ndarray[object] objects,
         True, no upcasting will be performed.
     convert_numeric : bool, default True
         Whether to convert numeric entries.
-    convert_datetime : bool, default False
-        If an array-like object contains only datetime values or NaT is
-        encountered, whether to convert and return an array of M8[ns] dtype.
-    convert_timedelta : bool, default False
-        If an array-like object contains only timedelta values or NaT is
-        encountered, whether to convert and return an array of m8[ns] dtype.
-    convert_period : bool, default False
-        If an array-like object contains only (homogeneous-freq) Period values
-        or NaT, whether to convert and return a PeriodArray.
-    convert_interval : bool, default False
-        If an array-like object contains only Interval objects (with matching
-        dtypes and closedness) or NaN, whether to convert to IntervalArray.
     convert_to_nullable_dtype : bool, default False
         If an array-like object contains only integer or boolean values (and NaN) is
         encountered, whether to convert and return an Boolean/IntegerArray.
+    convert_non_numeric : bool, default False
+        Whether to convert datetime, timedelta, period, interval types.
     dtype_if_all_nat : np.dtype, ExtensionDtype, or None, default None
         Dtype to cast to if we have all-NaT.
 
@@ -2454,12 +2441,11 @@ def maybe_convert_objects(ndarray[object] objects,
 
     if dtype_if_all_nat is not None:
         # in practice we don't expect to ever pass dtype_if_all_nat
-        #  without both convert_datetime and convert_timedelta, so disallow
+        #  without both convert_non_numeric, so disallow
         #  it to avoid needing to handle it below.
-        if not convert_datetime or not convert_timedelta:
+        if not convert_non_numeric:
             raise ValueError(
-                "Cannot specify 'dtype_if_all_nat' without convert_datetime=True "
-                "and convert_timedelta=True"
+                "Cannot specify 'dtype_if_all_nat' without convert_non_numeric=True"
             )
 
     n = len(objects)
@@ -2484,7 +2470,7 @@ def maybe_convert_objects(ndarray[object] objects,
             mask[i] = True
         elif val is NaT:
             seen.nat_ = True
-            if not (convert_datetime or convert_timedelta or convert_period):
+            if not convert_non_numeric:
                 seen.object_ = True
                 break
         elif util.is_nan(val):
@@ -2502,7 +2488,7 @@ def maybe_convert_objects(ndarray[object] objects,
             if not convert_numeric:
                 break
         elif is_timedelta(val):
-            if convert_timedelta:
+            if convert_non_numeric:
                 seen.timedelta_ = True
                 try:
                     convert_to_timedelta64(val, "ns")
@@ -2543,7 +2529,7 @@ def maybe_convert_objects(ndarray[object] objects,
         elif PyDateTime_Check(val) or util.is_datetime64_object(val):
 
             # if we have an tz's attached then return the objects
-            if convert_datetime:
+            if convert_non_numeric:
                 if getattr(val, "tzinfo", None) is not None:
                     seen.datetimetz_ = True
                     break
@@ -2559,7 +2545,7 @@ def maybe_convert_objects(ndarray[object] objects,
                 seen.object_ = True
                 break
         elif is_period_object(val):
-            if convert_period:
+            if convert_non_numeric:
                 seen.period_ = True
                 break
             else:
@@ -2575,7 +2561,7 @@ def maybe_convert_objects(ndarray[object] objects,
                 seen.object_ = True
                 break
         elif is_interval(val):
-            if convert_interval:
+            if convert_non_numeric:
                 seen.interval_ = True
                 break
             else:
@@ -2661,18 +2647,8 @@ def maybe_convert_objects(ndarray[object] objects,
             elif dtype is not None:
                 # EA, we don't expect to get here, but _could_ implement
                 raise NotImplementedError(dtype)
-            elif convert_datetime and convert_timedelta:
-                # we don't guess
-                seen.object_ = True
-            elif convert_datetime:
-                res = np.empty((<object>objects).shape, dtype="M8[ns]")
-                res[:] = NPY_NAT
-                return res
-            elif convert_timedelta:
-                res = np.empty((<object>objects).shape, dtype="m8[ns]")
-                res[:] = NPY_NAT
-                return res
             else:
+                # we don't guess
                 seen.object_ = True
         else:
             seen.object_ = True

pandas/core/dtypes/cast.py

@@ -1171,10 +1171,7 @@ def maybe_infer_to_datetimelike(
         # Here we do not convert numeric dtypes, as if we wanted that,
         #  numpy would have done it for us.
         convert_numeric=False,
-        convert_period=True,
-        convert_interval=True,
-        convert_timedelta=True,
-        convert_datetime=True,
+        convert_non_numeric=True,
         dtype_if_all_nat=np.dtype("M8[ns]"),
     )
 

pandas/core/indexes/base.py

@@ -6754,10 +6754,7 @@ def infer_objects(self, copy: bool = True) -> Index:
         values = cast("npt.NDArray[np.object_]", values)
         res_values = lib.maybe_convert_objects(
             values,
-            convert_datetime=True,
-            convert_timedelta=True,
-            convert_period=True,
-            convert_interval=True,
+            convert_non_numeric=True,
         )
         if copy and res_values is values:
             return self.copy()

pandas/core/internals/array_manager.py

@@ -390,10 +390,7 @@ def _convert(arr):
                 arr = np.asarray(arr)
                 result = lib.maybe_convert_objects(
                     arr,
-                    convert_datetime=True,
-                    convert_timedelta=True,
-                    convert_period=True,
-                    convert_interval=True,
+                    convert_non_numeric=True,
                 )
                 if result is arr and copy:
                     return arr.copy()

pandas/core/internals/blocks.py

@@ -2284,10 +2284,7 @@ def convert(
 
         res_values = lib.maybe_convert_objects(
             values,
-            convert_datetime=True,
-            convert_timedelta=True,
-            convert_period=True,
-            convert_interval=True,
+            convert_non_numeric=True,
         )
         refs = None
         if copy and res_values is values:

pandas/core/internals/construction.py

@@ -1017,8 +1017,8 @@ def convert(arr):
             # 1) we DO get here when arr is all Timestamps and dtype=None
             # 2) disabling this doesn't break the world, so this must be
             #    getting caught at a higher level
-            # 3) passing convert_datetime to maybe_convert_objects get this right
-            # 4) convert_timedelta?
+            # 3) passing convert_non_numeric to maybe_convert_objects get this right
+            # 4) convert_non_numeric?
 
             if dtype is None:
                 if arr.dtype == np.dtype("O"):

pandas/tests/dtypes/test_inference.py

@@ -727,17 +727,15 @@ def test_maybe_convert_objects_nat_inference(self, val, dtype):
         vals = np.array([pd.NaT, val], dtype=object)
         result = lib.maybe_convert_objects(
             vals,
-            convert_datetime=True,
-            convert_timedelta=True,
+            convert_non_numeric=True,
             dtype_if_all_nat=dtype,
         )
         assert result.dtype == dtype
         assert np.isnat(result).all()
 
         result = lib.maybe_convert_objects(
             vals[::-1],
-            convert_datetime=True,
-            convert_timedelta=True,
+            convert_non_numeric=True,
             dtype_if_all_nat=dtype,
         )
         assert result.dtype == dtype
@@ -777,47 +775,37 @@ def test_maybe_convert_objects_datetime(self):
             [np.datetime64("2000-01-01"), np.timedelta64(1, "s")], dtype=object
         )
         exp = arr.copy()
-        out = lib.maybe_convert_objects(
-            arr, convert_datetime=True, convert_timedelta=True
-        )
+        out = lib.maybe_convert_objects(arr, convert_non_numeric=True)
         tm.assert_numpy_array_equal(out, exp)
 
         arr = np.array([pd.NaT, np.timedelta64(1, "s")], dtype=object)
         exp = np.array([np.timedelta64("NaT"), np.timedelta64(1, "s")], dtype="m8[ns]")
-        out = lib.maybe_convert_objects(
-            arr, convert_datetime=True, convert_timedelta=True
-        )
+        out = lib.maybe_convert_objects(arr, convert_non_numeric=True)
         tm.assert_numpy_array_equal(out, exp)
 
-        # with convert_timedelta=True, the nan is a valid NA value for td64
+        # with convert_non_numeric=True, the nan is a valid NA value for td64
         arr = np.array([np.timedelta64(1, "s"), np.nan], dtype=object)
         exp = exp[::-1]
-        out = lib.maybe_convert_objects(
-            arr, convert_datetime=True, convert_timedelta=True
-        )
+        out = lib.maybe_convert_objects(arr, convert_non_numeric=True)
         tm.assert_numpy_array_equal(out, exp)
 
     def test_maybe_convert_objects_dtype_if_all_nat(self):
         arr = np.array([pd.NaT, pd.NaT], dtype=object)
-        out = lib.maybe_convert_objects(
-            arr, convert_datetime=True, convert_timedelta=True
-        )
+        out = lib.maybe_convert_objects(arr, convert_non_numeric=True)
         # no dtype_if_all_nat passed -> we dont guess
         tm.assert_numpy_array_equal(out, arr)
 
         out = lib.maybe_convert_objects(
             arr,
-            convert_datetime=True,
-            convert_timedelta=True,
+            convert_non_numeric=True,
             dtype_if_all_nat=np.dtype("timedelta64[ns]"),
         )
         exp = np.array(["NaT", "NaT"], dtype="timedelta64[ns]")
         tm.assert_numpy_array_equal(out, exp)
 
         out = lib.maybe_convert_objects(
             arr,
-            convert_datetime=True,
-            convert_timedelta=True,
+            convert_non_numeric=True,
             dtype_if_all_nat=np.dtype("datetime64[ns]"),
         )
         exp = np.array(["NaT", "NaT"], dtype="datetime64[ns]")
@@ -830,8 +818,7 @@ def test_maybe_convert_objects_dtype_if_all_nat_invalid(self):
         with pytest.raises(ValueError, match="int64"):
             lib.maybe_convert_objects(
                 arr,
-                convert_datetime=True,
-                convert_timedelta=True,
+                convert_non_numeric=True,
                 dtype_if_all_nat=np.dtype("int64"),
             )
 
@@ -842,9 +829,7 @@ def test_maybe_convert_objects_datetime_overflow_safe(self, dtype):
             stamp = stamp - datetime(1970, 1, 1)
         arr = np.array([stamp], dtype=object)
 
-        out = lib.maybe_convert_objects(
-            arr, convert_datetime=True, convert_timedelta=True
-        )
+        out = lib.maybe_convert_objects(arr, convert_non_numeric=True)
         # no OutOfBoundsDatetime/OutOfBoundsTimedeltas
         tm.assert_numpy_array_equal(out, arr)
 
@@ -855,15 +840,15 @@ def test_maybe_convert_objects_mixed_datetimes(self):
         for data in itertools.permutations(vals):
             data = np.array(list(data), dtype=object)
             expected = DatetimeIndex(data)._data._ndarray
-            result = lib.maybe_convert_objects(data, convert_datetime=True)
+            result = lib.maybe_convert_objects(data, convert_non_numeric=True)
             tm.assert_numpy_array_equal(result, expected)
 
     def test_maybe_convert_objects_timedelta64_nat(self):
         obj = np.timedelta64("NaT", "ns")
         arr = np.array([obj], dtype=object)
         assert arr[0] is obj
 
-        result = lib.maybe_convert_objects(arr, convert_timedelta=True)
+        result = lib.maybe_convert_objects(arr, convert_non_numeric=True)
 
         expected = np.array([obj], dtype="m8[ns]")
         tm.assert_numpy_array_equal(result, expected)
@@ -1037,7 +1022,7 @@ def test_maybe_convert_objects_itemsize(self, data0, data1):
     def test_mixed_dtypes_remain_object_array(self):
         # GH14956
         arr = np.array([datetime(2015, 1, 1, tzinfo=pytz.utc), 1], dtype=object)
-        result = lib.maybe_convert_objects(arr, convert_datetime=True)
+        result = lib.maybe_convert_objects(arr, convert_non_numeric=True)
         tm.assert_numpy_array_equal(result, arr)
 
     @pytest.mark.parametrize(
@@ -1050,8 +1035,7 @@ def test_mixed_dtypes_remain_object_array(self):
     def test_maybe_convert_objects_ea(self, idx):
         result = lib.maybe_convert_objects(
             np.array(idx, dtype=object),
-            convert_period=True,
-            convert_interval=True,
+            convert_non_numeric=True,
         )
         tm.assert_extension_array_equal(result, idx._data)