peacock-data-public-datasets-idc-cronscript
/
venv
/lib
/python3.10
/site-packages
/pandas
/tests
/test_aggregation.py
import numpy as np | |
import pytest | |
from pandas.core.apply import ( | |
_make_unique_kwarg_list, | |
maybe_mangle_lambdas, | |
) | |
def test_maybe_mangle_lambdas_passthrough(): | |
assert maybe_mangle_lambdas("mean") == "mean" | |
assert maybe_mangle_lambdas(lambda x: x).__name__ == "<lambda>" | |
# don't mangel single lambda. | |
assert maybe_mangle_lambdas([lambda x: x])[0].__name__ == "<lambda>" | |
def test_maybe_mangle_lambdas_listlike(): | |
aggfuncs = [lambda x: 1, lambda x: 2] | |
result = maybe_mangle_lambdas(aggfuncs) | |
assert result[0].__name__ == "<lambda_0>" | |
assert result[1].__name__ == "<lambda_1>" | |
assert aggfuncs[0](None) == result[0](None) | |
assert aggfuncs[1](None) == result[1](None) | |
def test_maybe_mangle_lambdas(): | |
func = {"A": [lambda x: 0, lambda x: 1]} | |
result = maybe_mangle_lambdas(func) | |
assert result["A"][0].__name__ == "<lambda_0>" | |
assert result["A"][1].__name__ == "<lambda_1>" | |
def test_maybe_mangle_lambdas_args(): | |
func = {"A": [lambda x, a, b=1: (0, a, b), lambda x: 1]} | |
result = maybe_mangle_lambdas(func) | |
assert result["A"][0].__name__ == "<lambda_0>" | |
assert result["A"][1].__name__ == "<lambda_1>" | |
assert func["A"][0](0, 1) == (0, 1, 1) | |
assert func["A"][0](0, 1, 2) == (0, 1, 2) | |
assert func["A"][0](0, 2, b=3) == (0, 2, 3) | |
def test_maybe_mangle_lambdas_named(): | |
func = {"C": np.mean, "D": {"foo": np.mean, "bar": np.mean}} | |
result = maybe_mangle_lambdas(func) | |
assert result == func | |
def test_make_unique(order, expected_reorder): | |
# GH 27519, test if make_unique function reorders correctly | |
result = _make_unique_kwarg_list(order) | |
assert result == expected_reorder | |