Merge branch 'main' into bug-decimal

Author: jbrockmendel

doc/source/whatsnew/v3.0.0.rst

@@ -716,6 +716,7 @@ Other Deprecations
 - Deprecated using ``epoch`` date format in :meth:`DataFrame.to_json` and :meth:`Series.to_json`, use ``iso`` instead. (:issue:`57063`)
 - Deprecated allowing ``fill_value`` that cannot be held in the original dtype (excepting NA values for integer and bool dtypes) in :meth:`Series.unstack` and :meth:`DataFrame.unstack` (:issue:`12189`, :issue:`53868`)
 - Deprecated allowing ``fill_value`` that cannot be held in the original dtype (excepting NA values for integer and bool dtypes) in :meth:`Series.shift` and :meth:`DataFrame.shift` (:issue:`53802`)
+- Deprecated option "future.no_silent_downcasting", as it is no longer used. In a future version accessing this option will raise (:issue:`59502`)
 - Deprecated slicing on a :class:`Series` or :class:`DataFrame` with a :class:`DatetimeIndex` using a ``datetime.date`` object, explicitly cast to :class:`Timestamp` instead (:issue:`35830`)
 
 .. ---------------------------------------------------------------------------
@@ -1016,8 +1017,8 @@ Strings
 Interval
 ^^^^^^^^
 - :meth:`Index.is_monotonic_decreasing`, :meth:`Index.is_monotonic_increasing`, and :meth:`Index.is_unique` could incorrectly be ``False`` for an ``Index`` created from a slice of another ``Index``. (:issue:`57911`)
+- Bug in :class:`Index`, :class:`Series`, :class:`DataFrame` constructors when given a sequence of :class:`Interval` subclass objects casting them to :class:`Interval` (:issue:`46945`)
 - Bug in :func:`interval_range` where start and end numeric types were always cast to 64 bit (:issue:`57268`)
--
 
 Indexing
 ^^^^^^^^

pandas/_libs/lib.pyx

@@ -2255,7 +2255,8 @@ cpdef bint is_interval_array(ndarray values):
     for i in range(n):
         val = values[i]
 
-        if isinstance(val, Interval):
+        if type(val) is Interval:
+            # GH#46945 catch Interval exactly, excluding subclasses
             if closed is None:
                 closed = val.closed
                 numeric = (

pandas/core/config_init.py

@@ -28,6 +28,8 @@
     is_text,
 )
 
+from pandas.errors import Pandas4Warning
+
 # compute
 
 use_bottleneck_doc = """
@@ -899,10 +901,10 @@ def register_converter_cb(key: str) -> None:
     cf.register_option(
         "no_silent_downcasting",
         False,
-        "Whether to opt-in to the future behavior which will *not* silently "
-        "downcast results from Series and DataFrame `where`, `mask`, and `clip` "
-        "methods. "
-        "Silent downcasting will be removed in pandas 3.0 "
-        "(at which point this option will be deprecated).",
+        "This option is deprecated and will be removed in a future version. "
+        "It has no effect.",
         validator=is_one_of_factory([True, False]),
     )
+
+# GH#59502
+cf.deprecate_option("future.no_silent_downcasting", Pandas4Warning)

pandas/tests/config/test_config.py

@@ -3,6 +3,8 @@
 from pandas._config import config as cf
 from pandas._config.config import OptionError
 
+from pandas.errors import Pandas4Warning
+
 import pandas as pd
 import pandas._testing as tm
 
@@ -481,3 +483,11 @@ def test_dictwrapper_getattr(self):
         with pytest.raises(OptionError, match="No such option"):
             options.bananas
         assert not hasattr(options, "bananas")
+
+
+def test_no_silent_downcasting_deprecated():
+    # GH#59502
+    with tm.assert_produces_warning(Pandas4Warning, match="is deprecated"):
+        cf.get_option("future.no_silent_downcasting")
+    with tm.assert_produces_warning(Pandas4Warning, match="is deprecated"):
+        cf.set_option("future.no_silent_downcasting", True)

pandas/tests/dtypes/test_inference.py

@@ -1605,6 +1605,24 @@ def test_is_string_array(self):
         )
         assert not lib.is_string_array(np.array([1, 2]))
 
+    def test_is_interval_array_subclass(self):
+        # GH#46945
+
+        class TimestampsInterval(Interval):
+            def __init__(self, left: str, right: str, closed="both") -> None:
+                super().__init__(Timestamp(left), Timestamp(right), closed)
+
+            @property
+            def seconds(self) -> float:
+                return self.length.seconds
+
+        item = TimestampsInterval("1970-01-01 00:00:00", "1970-01-01 00:00:01")
+        arr = np.array([item], dtype=object)
+        assert not lib.is_interval_array(arr)
+        assert lib.infer_dtype(arr) != "interval"
+        out = Series([item])[0]
+        assert isinstance(out, TimestampsInterval)
+
     @pytest.mark.parametrize(
         "func",
         [

pandas/tests/io/excel/test_writers.py

@@ -1409,8 +1409,7 @@ def test_render_as_column_name(self, tmp_excel):
     def test_true_and_false_value_options(self, tmp_excel):
         # see gh-13347
         df = DataFrame([["foo", "bar"]], columns=["col1", "col2"], dtype=object)
-        with option_context("future.no_silent_downcasting", True):
-            expected = df.replace({"foo": True, "bar": False}).astype("bool")
+        expected = df.replace({"foo": True, "bar": False}).astype("bool")
 
         df.to_excel(tmp_excel)
         read_frame = pd.read_excel(

pandas/tests/io/test_parquet.py

@@ -198,6 +198,8 @@ def check_round_trip(
     repeat: int, optional
         How many times to repeat the test
     """
+    if not isinstance(temp_file, pathlib.Path):
+        raise ValueError("temp_file must be a pathlib.Path")
     write_kwargs = write_kwargs or {"compression": None}
     read_kwargs = read_kwargs or {}
 
@@ -396,9 +398,11 @@ def test_columns_dtypes(self, engine, temp_file):
         check_round_trip(df, temp_file, engine)
 
     @pytest.mark.parametrize("compression", [None, "gzip", "snappy", "brotli"])
-    def test_compression(self, engine, compression):
+    def test_compression(self, engine, compression, temp_file):
         df = pd.DataFrame({"A": [1, 2, 3]})
-        check_round_trip(df, engine, write_kwargs={"compression": compression})
+        check_round_trip(
+            df, temp_file, engine, write_kwargs={"compression": compression}
+        )
 
     def test_read_columns(self, engine, temp_file):
         # GH18154
@@ -424,8 +428,8 @@ def test_read_filters(self, engine, tmp_path):
         expected = pd.DataFrame({"int": [0, 1]})
         check_round_trip(
             df,
+            tmp_path,
             engine,
-            path=tmp_path,
             expected=expected,
             write_kwargs={"partition_cols": ["part"]},
             read_kwargs={"filters": [("part", "==", "a")], "columns": ["int"]},

pandas/tests/strings/test_api.py

@@ -10,7 +10,6 @@
     MultiIndex,
     Series,
     _testing as tm,
-    option_context,
 )
 from pandas.core.strings.accessor import StringMethods
 
@@ -181,8 +180,7 @@ def test_api_per_method(
 
     if inferred_dtype in allowed_types:
         # xref GH 23555, GH 23556
-        with option_context("future.no_silent_downcasting", True):
-            method(*args, **kwargs)  # works!
+        method(*args, **kwargs)  # works!
     else:
         # GH 23011, GH 23163
         msg = (

pandas/tests/strings/test_string_array.py

@@ -8,7 +8,6 @@
     DataFrame,
     Series,
     _testing as tm,
-    option_context,
 )
 
 
@@ -56,8 +55,7 @@ def test_string_array(nullable_string_dtype, any_string_method):
         columns = expected.select_dtypes(include="object").columns
         assert all(result[columns].dtypes == nullable_string_dtype)
         result[columns] = result[columns].astype(object)
-        with option_context("future.no_silent_downcasting", True):
-            expected[columns] = expected[columns].fillna(NA)  # GH#18463
+        expected[columns] = expected[columns].fillna(NA)  # GH#18463
 
     tm.assert_equal(result, expected)