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REF: Remove Numba compat pre 0.50.1 #43266

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Merged
merged 4 commits into from
Aug 30, 2021
Merged

REF: Remove Numba compat pre 0.50.1 #43266

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e191667
CLN: Pre Numba 0.46.0 compat
mroeschke Aug 27, 2021
2ea6fff
Merge remote-tracking branch 'upstream/master' into clean/numba_pre_r…
mroeschke Aug 27, 2021
4fd940b
Merge remote-tracking branch 'upstream/master' into clean/numba_pre_r…
mroeschke Aug 29, 2021
8e531ef
Remove other unneeded min references
mroeschke Aug 29, 2021
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9 changes: 1 addition & 8 deletions pandas/core/util/numba_.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,8 +9,6 @@
from pandas.compat._optional import import_optional_dependency
from pandas.errors import NumbaUtilError

from pandas.util.version import Version

GLOBAL_USE_NUMBA: bool = False
NUMBA_FUNC_CACHE: dict[tuple[Callable, str], Callable] = {}

Expand Down Expand Up @@ -87,12 +85,7 @@ def jit_user_function(
"""
numba = import_optional_dependency("numba")

if Version(numba.__version__) >= Version("0.49.0"):
is_jitted = numba.extending.is_jitted(func)
else:
is_jitted = isinstance(func, numba.targets.registry.CPUDispatcher)

if is_jitted:
if numba.extending.is_jitted(func):
# Don't jit a user passed jitted function
numba_func = func
else:
Expand Down
2 changes: 1 addition & 1 deletion pandas/tests/frame/test_ufunc.py
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Expand Up @@ -251,7 +251,7 @@ def test_alignment_deprecation():
tm.assert_frame_equal(result, expected)


@td.skip_if_no("numba", "0.46.0")
@td.skip_if_no("numba")
def test_alignment_deprecation_many_inputs():
# https://github.com/pandas-dev/pandas/issues/39184
# test that the deprecation also works with > 2 inputs -> using a numba
Expand Down
16 changes: 8 additions & 8 deletions pandas/tests/groupby/aggregate/test_numba.py
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Expand Up @@ -15,7 +15,7 @@
from pandas.core.util.numba_ import NUMBA_FUNC_CACHE


@td.skip_if_no("numba", "0.46.0")
@td.skip_if_no("numba")
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prob could remove these individual skips and just skip the entire module if numba not installed?

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True. All */test_numba.py tests should require numba

def test_correct_function_signature():
def incorrect_function(x):
return sum(x) * 2.7
Expand All @@ -31,7 +31,7 @@ def incorrect_function(x):
data.groupby("key")["data"].agg(incorrect_function, engine="numba")


@td.skip_if_no("numba", "0.46.0")
@td.skip_if_no("numba")
def test_check_nopython_kwargs():
def incorrect_function(x, **kwargs):
return sum(x) * 2.7
Expand All @@ -47,7 +47,7 @@ def incorrect_function(x, **kwargs):
data.groupby("key")["data"].agg(incorrect_function, engine="numba", a=1)


@td.skip_if_no("numba", "0.46.0")
@td.skip_if_no("numba")
@pytest.mark.filterwarnings("ignore:\\nThe keyword argument")
# Filter warnings when parallel=True and the function can't be parallelized by Numba
@pytest.mark.parametrize("jit", [True, False])
Expand Down Expand Up @@ -76,7 +76,7 @@ def func_numba(values, index):
tm.assert_equal(result, expected)


@td.skip_if_no("numba", "0.46.0")
@td.skip_if_no("numba")
@pytest.mark.filterwarnings("ignore:\\nThe keyword argument")
# Filter warnings when parallel=True and the function can't be parallelized by Numba
@pytest.mark.parametrize("jit", [True, False])
Expand Down Expand Up @@ -121,7 +121,7 @@ def func_2(values, index):
tm.assert_equal(result, expected)


@td.skip_if_no("numba", "0.46.0")
@td.skip_if_no("numba")
def test_use_global_config():
def func_1(values, index):
return np.mean(values) - 3.4
Expand All @@ -136,7 +136,7 @@ def func_1(values, index):
tm.assert_frame_equal(expected, result)


@td.skip_if_no("numba", "0.46.0")
@td.skip_if_no("numba")
@pytest.mark.parametrize(
"agg_func",
[
Expand All @@ -158,7 +158,7 @@ def test_multifunc_notimplimented(agg_func):
grouped[1].agg(agg_func, engine="numba")


@td.skip_if_no("numba", "0.46.0")
@td.skip_if_no("numba")
def test_args_not_cached():
# GH 41647
def sum_last(values, index, n):
Expand All @@ -175,7 +175,7 @@ def sum_last(values, index, n):
tm.assert_series_equal(result, expected)


@td.skip_if_no("numba", "0.46.0")
@td.skip_if_no("numba")
def test_index_data_correctly_passed():
# GH 43133
def f(values, index):
Expand Down
16 changes: 8 additions & 8 deletions pandas/tests/groupby/transform/test_numba.py
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Expand Up @@ -12,7 +12,7 @@
from pandas.core.util.numba_ import NUMBA_FUNC_CACHE


@td.skip_if_no("numba", "0.46.0")
@td.skip_if_no("numba")
def test_correct_function_signature():
def incorrect_function(x):
return x + 1
Expand All @@ -28,7 +28,7 @@ def incorrect_function(x):
data.groupby("key")["data"].transform(incorrect_function, engine="numba")


@td.skip_if_no("numba", "0.46.0")
@td.skip_if_no("numba")
def test_check_nopython_kwargs():
def incorrect_function(x, **kwargs):
return x + 1
Expand All @@ -44,7 +44,7 @@ def incorrect_function(x, **kwargs):
data.groupby("key")["data"].transform(incorrect_function, engine="numba", a=1)


@td.skip_if_no("numba", "0.46.0")
@td.skip_if_no("numba")
@pytest.mark.filterwarnings("ignore:\\nThe keyword argument")
# Filter warnings when parallel=True and the function can't be parallelized by Numba
@pytest.mark.parametrize("jit", [True, False])
Expand Down Expand Up @@ -73,7 +73,7 @@ def func(values, index):
tm.assert_equal(result, expected)


@td.skip_if_no("numba", "0.46.0")
@td.skip_if_no("numba")
@pytest.mark.filterwarnings("ignore:\\nThe keyword argument")
# Filter warnings when parallel=True and the function can't be parallelized by Numba
@pytest.mark.parametrize("jit", [True, False])
Expand Down Expand Up @@ -118,7 +118,7 @@ def func_2(values, index):
tm.assert_equal(result, expected)


@td.skip_if_no("numba", "0.46.0")
@td.skip_if_no("numba")
def test_use_global_config():
def func_1(values, index):
return values + 1
Expand All @@ -133,7 +133,7 @@ def func_1(values, index):
tm.assert_frame_equal(expected, result)


@td.skip_if_no("numba", "0.46.0")
@td.skip_if_no("numba")
@pytest.mark.parametrize(
"agg_func", [["min", "max"], "min", {"B": ["min", "max"], "C": "sum"}]
)
Expand All @@ -149,7 +149,7 @@ def test_multifunc_notimplimented(agg_func):
grouped[1].transform(agg_func, engine="numba")


@td.skip_if_no("numba", "0.46.0")
@td.skip_if_no("numba")
def test_args_not_cached():
# GH 41647
def sum_last(values, index, n):
Expand All @@ -166,7 +166,7 @@ def sum_last(values, index, n):
tm.assert_series_equal(result, expected)


@td.skip_if_no("numba", "0.46.0")
@td.skip_if_no("numba")
def test_index_data_correctly_passed():
# GH 43133
def f(values, index):
Expand Down
6 changes: 2 additions & 4 deletions pandas/tests/window/conftest.py
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Expand Up @@ -124,17 +124,15 @@ def ignore_na(request):
return request.param


@pytest.fixture(
params=[pytest.param("numba", marks=td.skip_if_no("numba", "0.46.0")), "cython"]
)
@pytest.fixture(params=[pytest.param("numba", marks=td.skip_if_no("numba")), "cython"])
def engine(request):
"""engine keyword argument for rolling.apply"""
return request.param


@pytest.fixture(
params=[
pytest.param(("numba", True), marks=td.skip_if_no("numba", "0.46.0")),
pytest.param(("numba", True), marks=td.skip_if_no("numba")),
("cython", True),
("cython", False),
]
Expand Down
10 changes: 5 additions & 5 deletions pandas/tests/window/test_numba.py
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Expand Up @@ -14,7 +14,7 @@
from pandas.core.util.numba_ import NUMBA_FUNC_CACHE


@td.skip_if_no("numba", "0.46.0")
@td.skip_if_no("numba")
@pytest.mark.filterwarnings("ignore:\\nThe keyword argument")
# Filter warnings when parallel=True and the function can't be parallelized by Numba
class TestEngine:
Expand Down Expand Up @@ -150,7 +150,7 @@ def add(values, x):
tm.assert_frame_equal(result, expected)


@td.skip_if_no("numba", "0.46.0")
@td.skip_if_no("numba")
class TestEWMMean:
@pytest.mark.parametrize(
"grouper", [lambda x: x, lambda x: x.groupby("A")], ids=["None", "groupby"]
Expand Down Expand Up @@ -229,7 +229,7 @@ def test_cython_vs_numba_times(self, grouper, nogil, parallel, nopython, ignore_
tm.assert_frame_equal(result, expected)


@td.skip_if_no("numba", "0.46.0")
@td.skip_if_no("numba")
def test_use_global_config():
def f(x):
return np.mean(x) + 2
Expand All @@ -241,15 +241,15 @@ def f(x):
tm.assert_series_equal(expected, result)


@td.skip_if_no("numba", "0.46.0")
@td.skip_if_no("numba")
def test_invalid_kwargs_nopython():
with pytest.raises(NumbaUtilError, match="numba does not support kwargs with"):
Series(range(1)).rolling(1).apply(
lambda x: x, kwargs={"a": 1}, engine="numba", raw=True
)


@td.skip_if_no("numba", "0.46.0")
@td.skip_if_no("numba")
@pytest.mark.slow
@pytest.mark.filterwarnings("ignore:\\nThe keyword argument")
# Filter warnings when parallel=True and the function can't be parallelized by Numba
Expand Down
2 changes: 1 addition & 1 deletion pandas/tests/window/test_online.py
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Expand Up @@ -10,7 +10,7 @@
import pandas._testing as tm


@td.skip_if_no("numba", "0.46.0")
@td.skip_if_no("numba")
@pytest.mark.filterwarnings("ignore:\\nThe keyword argument")
class TestEWM:
def test_invalid_update(self):
Expand Down