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- from hypothesis import (
- assume,
- example,
- given,
- strategies as st,
- )
- import numpy as np
- import pytest
- import pandas._testing as tm
- from pandas.io.sas._byteswap import (
- read_double_with_byteswap,
- read_float_with_byteswap,
- read_uint16_with_byteswap,
- read_uint32_with_byteswap,
- read_uint64_with_byteswap,
- )
- @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().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)
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