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from hypothesis import (
assume,
example,
given,
strategies as st,
)
import numpy as np
import pytest
from pandas._libs.byteswap import (
read_double_with_byteswap,
read_float_with_byteswap,
read_uint16_with_byteswap,
read_uint32_with_byteswap,
read_uint64_with_byteswap,
)
import pandas._testing as tm
@given(read_offset=st.integers(0, 11), number=st.integers(min_value=0))
@example(number=2**16, read_offset=0)
@example(number=2**32, read_offset=0)
@example(number=2**64, read_offset=0)
@pytest.mark.parametrize("int_type", [np.uint16, np.uint32, np.uint64])
@pytest.mark.parametrize("should_byteswap", [True, False])
def test_int_byteswap(read_offset, number, int_type, should_byteswap):
assume(number < 2 ** (8 * int_type(0).itemsize))
_test(number, int_type, read_offset, should_byteswap)
@pytest.mark.filterwarnings("ignore:overflow encountered:RuntimeWarning")
@given(read_offset=st.integers(0, 11), number=st.floats())
@pytest.mark.parametrize("float_type", [np.float32, np.float64])
@pytest.mark.parametrize("should_byteswap", [True, False])
def test_float_byteswap(read_offset, number, float_type, should_byteswap):
_test(number, float_type, read_offset, should_byteswap)
def _test(number, number_type, read_offset, should_byteswap):
number = number_type(number)
data = np.random.default_rng(2).integers(0, 256, size=20, dtype="uint8")
data[read_offset : read_offset + number.itemsize] = number[None].view("uint8")
swap_func = {
np.float32: read_float_with_byteswap,
np.float64: read_double_with_byteswap,
np.uint16: read_uint16_with_byteswap,
np.uint32: read_uint32_with_byteswap,
np.uint64: read_uint64_with_byteswap,
}[type(number)]
output_number = number_type(swap_func(bytes(data), read_offset, should_byteswap))
if should_byteswap:
tm.assert_equal(output_number, number.byteswap())
else:
tm.assert_equal(output_number, number)