Ajout type contrat

venv/lib/python3.12/site-packages/pandas/tests/extension/test_interval.py

@@ -0,0 +1,147 @@
+"""
+This file contains a minimal set of tests for compliance with the extension
+array interface test suite, and should contain no other tests.
+The test suite for the full functionality of the array is located in
+`pandas/tests/arrays/`.
+
+The tests in this file are inherited from the BaseExtensionTests, and only
+minimal tweaks should be applied to get the tests passing (by overwriting a
+parent method).
+
+Additional tests should either be added to one of the BaseExtensionTests
+classes (if they are relevant for the extension interface for all dtypes), or
+be added to the array-specific tests in `pandas/tests/arrays/`.
+
+"""
+
+from __future__ import annotations
+
+from typing import TYPE_CHECKING
+
+import numpy as np
+import pytest
+
+from pandas.core.dtypes.dtypes import IntervalDtype
+
+from pandas import Interval
+from pandas.core.arrays import IntervalArray
+from pandas.tests.extension import base
+
+if TYPE_CHECKING:
+    import pandas as pd
+
+
+def make_data(n: int):
+    left_array = np.random.default_rng(2).uniform(size=n).cumsum()
+    right_array = left_array + np.random.default_rng(2).uniform(size=n)
+    return [
+        Interval(left, right)
+        for left, right in zip(left_array, right_array, strict=True)
+    ]
+
+
+@pytest.fixture
+def dtype():
+    return IntervalDtype()
+
+
+@pytest.fixture
+def data():
+    """Length-10 IntervalArray for semantics test."""
+    return IntervalArray(make_data(10))
+
+
+@pytest.fixture
+def data_missing():
+    """Length 2 array with [NA, Valid]"""
+    return IntervalArray.from_tuples([None, (0, 1)])
+
+
+@pytest.fixture
+def data_for_twos():
+    pytest.skip("Interval is not a numeric dtype")
+
+
+@pytest.fixture
+def data_for_sorting():
+    return IntervalArray.from_tuples([(1, 2), (2, 3), (0, 1)])
+
+
+@pytest.fixture
+def data_missing_for_sorting():
+    return IntervalArray.from_tuples([(1, 2), None, (0, 1)])
+
+
+@pytest.fixture
+def data_for_grouping():
+    a = (0, 1)
+    b = (1, 2)
+    c = (2, 3)
+    return IntervalArray.from_tuples([b, b, None, None, a, a, b, c])
+
+
+class TestIntervalArray(base.ExtensionTests):
+    divmod_exc = TypeError
+
+    def _supports_reduction(self, ser: pd.Series, op_name: str) -> bool:
+        return op_name in ["min", "max"]
+
+    def test_fillna_limit_frame(self, data_missing):
+        # GH#58001
+        with pytest.raises(ValueError, match="limit must be None"):
+            super().test_fillna_limit_frame(data_missing)
+
+    def test_fillna_limit_series(self, data_missing):
+        # GH#58001
+        with pytest.raises(ValueError, match="limit must be None"):
+            super().test_fillna_limit_frame(data_missing)
+
+    @pytest.mark.xfail(
+        reason="Raises with incorrect message bc it disallows *all* listlikes "
+        "instead of just wrong-length listlikes"
+    )
+    def test_fillna_length_mismatch(self, data_missing):
+        super().test_fillna_length_mismatch(data_missing)
+
+    @pytest.mark.xfail(reason="copy=False is not Implemented")
+    def test_fillna_readonly(self, data_missing):
+        super().test_fillna_readonly(data_missing)
+
+    @pytest.mark.filterwarnings(
+        "ignore:invalid value encountered in cast:RuntimeWarning"
+    )
+    def test_hash_pandas_object(self, data):
+        super().test_hash_pandas_object(data)
+
+    @pytest.mark.filterwarnings(
+        "ignore:invalid value encountered in cast:RuntimeWarning"
+    )
+    def test_hash_pandas_object_works(self, data, as_frame):
+        super().test_hash_pandas_object_works(data, as_frame)
+
+    @pytest.mark.filterwarnings(
+        "ignore:invalid value encountered in cast:RuntimeWarning"
+    )
+    @pytest.mark.parametrize("engine", ["c", "python"])
+    def test_EA_types(self, engine, data, request):
+        super().test_EA_types(engine, data, request)
+
+    @pytest.mark.filterwarnings(
+        "ignore:invalid value encountered in cast:RuntimeWarning"
+    )
+    def test_astype_str(self, data):
+        super().test_astype_str(data)
+
+    @pytest.mark.xfail(
+        reason="Test is invalid for IntervalDtype, needs to be adapted for "
+        "this dtype with an index with index._index_as_unique."
+    )
+    def test_loc_setitem_with_expansion_preserves_ea_index_dtype(self, data):
+        super().test_loc_setitem_with_expansion_preserves_ea_index_dtype(data)
+
+
+# TODO: either belongs in tests.arrays.interval or move into base tests.
+def test_fillna_non_scalar_raises(data_missing):
+    msg = "can only insert Interval objects and NA into an IntervalArray"
+    with pytest.raises(TypeError, match=msg):
+        data_missing.fillna([1, 1])