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.venv/Lib/site-packages/pandas/tests/groupby/conftest.py

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+import numpy as np
+import pytest
+
+from pandas import DataFrame
+import pandas._testing as tm
+from pandas.core.groupby.base import (
+    reduction_kernels,
+    transformation_kernels,
+)
+
+
+@pytest.fixture(params=[True, False])
+def sort(request):
+    return request.param
+
+
+@pytest.fixture(params=[True, False])
+def as_index(request):
+    return request.param
+
+
+@pytest.fixture
+def mframe(multiindex_dataframe_random_data):
+    return multiindex_dataframe_random_data
+
+
+@pytest.fixture
+def df():
+    return DataFrame(
+        {
+            "A": ["foo", "bar", "foo", "bar", "foo", "bar", "foo", "foo"],
+            "B": ["one", "one", "two", "three", "two", "two", "one", "three"],
+            "C": np.random.randn(8),
+            "D": np.random.randn(8),
+        }
+    )
+
+
+@pytest.fixture
+def ts():
+    return tm.makeTimeSeries()
+
+
+@pytest.fixture
+def tsd():
+    return tm.getTimeSeriesData()
+
+
+@pytest.fixture
+def tsframe(tsd):
+    return DataFrame(tsd)
+
+
+@pytest.fixture
+def df_mixed_floats():
+    return DataFrame(
+        {
+            "A": ["foo", "bar", "foo", "bar", "foo", "bar", "foo", "foo"],
+            "B": ["one", "one", "two", "three", "two", "two", "one", "three"],
+            "C": np.random.randn(8),
+            "D": np.array(np.random.randn(8), dtype="float32"),
+        }
+    )
+
+
+@pytest.fixture
+def three_group():
+    return DataFrame(
+        {
+            "A": [
+                "foo",
+                "foo",
+                "foo",
+                "foo",
+                "bar",
+                "bar",
+                "bar",
+                "bar",
+                "foo",
+                "foo",
+                "foo",
+            ],
+            "B": [
+                "one",
+                "one",
+                "one",
+                "two",
+                "one",
+                "one",
+                "one",
+                "two",
+                "two",
+                "two",
+                "one",
+            ],
+            "C": [
+                "dull",
+                "dull",
+                "shiny",
+                "dull",
+                "dull",
+                "shiny",
+                "shiny",
+                "dull",
+                "shiny",
+                "shiny",
+                "shiny",
+            ],
+            "D": np.random.randn(11),
+            "E": np.random.randn(11),
+            "F": np.random.randn(11),
+        }
+    )
+
+
+@pytest.fixture()
+def slice_test_df():
+    data = [
+        [0, "a", "a0_at_0"],
+        [1, "b", "b0_at_1"],
+        [2, "a", "a1_at_2"],
+        [3, "b", "b1_at_3"],
+        [4, "c", "c0_at_4"],
+        [5, "a", "a2_at_5"],
+        [6, "a", "a3_at_6"],
+        [7, "a", "a4_at_7"],
+    ]
+    df = DataFrame(data, columns=["Index", "Group", "Value"])
+    return df.set_index("Index")
+
+
+@pytest.fixture()
+def slice_test_grouped(slice_test_df):
+    return slice_test_df.groupby("Group", as_index=False)
+
+
+@pytest.fixture(params=sorted(reduction_kernels))
+def reduction_func(request):
+    """
+    yields the string names of all groupby reduction functions, one at a time.
+    """
+    return request.param
+
+
+@pytest.fixture(params=sorted(transformation_kernels))
+def transformation_func(request):
+    """yields the string names of all groupby transformation functions."""
+    return request.param
+
+
+@pytest.fixture(params=sorted(reduction_kernels) + sorted(transformation_kernels))
+def groupby_func(request):
+    """yields both aggregation and transformation functions."""
+    return request.param
+
+
+@pytest.fixture(params=[True, False])
+def parallel(request):
+    """parallel keyword argument for numba.jit"""
+    return request.param
+
+
+# Can parameterize nogil & nopython over True | False, but limiting per
+# https://github.com/pandas-dev/pandas/pull/41971#issuecomment-860607472
+
+
+@pytest.fixture(params=[False])
+def nogil(request):
+    """nogil keyword argument for numba.jit"""
+    return request.param
+
+
+@pytest.fixture(params=[True])
+def nopython(request):
+    """nopython keyword argument for numba.jit"""
+    return request.param
+
+
+@pytest.fixture(
+    params=[
+        ("mean", {}),
+        ("var", {"ddof": 1}),
+        ("var", {"ddof": 0}),
+        ("std", {"ddof": 1}),
+        ("std", {"ddof": 0}),
+        ("sum", {}),
+    ]
+)
+def numba_supported_reductions(request):
+    """reductions supported with engine='numba'"""
+    return request.param