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BUG: compute.use_numexpr option not respected #42668

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Merged
merged 5 commits into from
Jul 28, 2021
Merged

BUG: compute.use_numexpr option not respected #42668

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c494dec
use use_numexpr for engine
Jul 22, 2021
fdb1ed6
BUG: compute.use_numexpr option not respected
Jul 22, 2021
46f19af
parametrized True False for numexpr
Jul 25, 2021
2c3b292
added user perspective test for numexpr option respected
Jul 25, 2021
a6cdd73
reduced logic in test by parametrizing expected result
Jul 26, 2021
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2 changes: 1 addition & 1 deletion doc/source/whatsnew/v1.4.0.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -201,7 +201,7 @@ Numeric
^^^^^^^
- Bug in :meth:`DataFrame.rank` raising ``ValueError`` with ``object`` columns and ``method="first"`` (:issue:`41931`)
- Bug in :meth:`DataFrame.rank` treating missing values and extreme values as equal (for example ``np.nan`` and ``np.inf``), causing incorrect results when ``na_option="bottom"`` or ``na_option="top`` used (:issue:`41931`)
-
- Bug in ``numexpr`` engine still being used when the option ``compute.use_numexpr`` is set to ``False`` (:issue:`32556`)

Conversion
^^^^^^^^^^
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3 changes: 2 additions & 1 deletion pandas/core/computation/eval.py
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Expand Up @@ -43,9 +43,10 @@ def _check_engine(engine: str | None) -> str:
Engine name.
"""
from pandas.core.computation.check import NUMEXPR_INSTALLED
from pandas.core.computation.expressions import USE_NUMEXPR

if engine is None:
engine = "numexpr" if NUMEXPR_INSTALLED else "python"
engine = "numexpr" if USE_NUMEXPR else "python"

if engine not in ENGINES:
valid_engines = list(ENGINES.keys())
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26 changes: 26 additions & 0 deletions pandas/tests/computation/test_eval.py
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Expand Up @@ -1865,6 +1865,32 @@ def test_invalid_engine():
pd.eval("x + y", local_dict={"x": 1, "y": 2}, engine="asdf")


@td.skip_if_no_ne
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can you parameterize and text for both True/False here.

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added

@pytest.mark.parametrize("use_numexpr", [True, False])
def test_numexpr_option_respected(use_numexpr):
# GH 32556
from pandas.core.computation.eval import _check_engine

with pd.option_context("compute.use_numexpr", use_numexpr):
result = _check_engine(None)
if use_numexpr:
assert result == "numexpr"
else:
assert result == "python"
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logic (e.g. if/else statements) in tests aren't ideal (https://testing.googleblog.com/2014/07/testing-on-toilet-dont-put-logic-in.html), how about something like

@pytest.mark.parametrize(
    ("use_numexpr", "expected"),
    (
          (True, "numexpr"),
          (False, "python"),
    )
)
def test_numexpr_option_respected(use_numexpr, expected):

and then, in the body, just assert result == expected?

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This is good to know! Thank you for linking the resource. Added!



@td.skip_if_no_ne
def test_numexpr_option_incompatible_op():
# GH 32556
with pd.option_context("compute.use_numexpr", False):
df = DataFrame(
{"A": [True, False, True, False, None, None], "B": [1, 2, 3, 4, 5, 6]}
)
result = df.query("A.isnull()")
expected = DataFrame({"A": [None, None], "B": [5, 6]}, index=[4, 5])
tm.assert_frame_equal(result, expected)


@td.skip_if_no_ne
def test_invalid_parser():
msg = "Invalid parser 'asdf' passed"
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