TST/REF: arithmetic tests for BooleanArray + consolidate with integer masked tests #34623
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jorisvandenbossche
added
Bug
Testing
| with pytest.raises(TypeError): | ||
| ops(pd.Timestamp("20180101")) | ||
| @pytest.fixture | ||
| def b(): |
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would it be burdensome to give a and b more informative names?
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Do you have a suggestion what you would find clearer?
Basically, before moving it to a fixture, I had:
def test_..():
a = pd.array([True] * 3 + [False] * 3 + [None] * 3, dtype="boolean")
b = pd.array([True, False, None] * 3, dtype="boolean")
result = op(a, b)
in each test, and I would think in such a context you would be fine with those names?
And although I like defining those variables inside the test as more explicit, it was also a bit repetitive, so I moved it to a fixture.
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i would call these left_array, right_array
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small comment; LGTM |
pandas/_testing.py
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| def get_op_from_name(op_name): | |||
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can you type op_name and return type
| with pytest.raises(TypeError): | ||
| ops(pd.Timestamp("20180101")) | ||
| @pytest.fixture | ||
| def b(): |
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i would call these left_array, right_array
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| "mod", | ||
| pytest.param( | ||
| "pow", marks=pytest.mark.xfail(reason="TODO follow int8 behaviour?") |
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Not yet, will open one.
| tm.assert_extension_array_equal(result, expected) | ||
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| # Test generic charachteristics / errors |
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Does "sp" point to the typo in this title? Or did you mean something else?
| tm.assert_series_equal(result, expected) | ||
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| # Test generic charachteristics / errors |
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| @@ -2758,3 +2759,28 @@ def get_cython_table_params(ndframe, func_names_and_expected): | |||
| if name == func_name | |||
| ] | |||
| return results | |||
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| def get_op_from_name(op_name: str) -> Callable: | |||
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IIRC we have something similiar in internals, maybe we should consolidate (just a thought) and certainly. in a followon
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thanks @jorisvandenbossche |
Follow-up on #34454
integer/test_arithmetic.pytomasked/test_arithmetic.pyso those can be shared with boolean (and once merged I can add float as well in the FloatingArray PR)boolean/test_arithmetic.pyto follow the same pattern as we have ininteger/test_arithmetic.py.pd.NAscalar as other operand.