examples/datafusion-ffi-example/python/tests/_test_window_udf.py

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from __future__ import annotations

import pyarrow as pa
from datafusion import SessionContext, col, udwf
from datafusion_ffi_example import MyRankUDF


def setup_context_with_table():
    ctx = SessionContext()

    # Pick numbers here so we get the same value in both groups
    # since we cannot be certain of the output order of batches
    batch = pa.RecordBatch.from_arrays(
        [
            pa.array([40, 10, 30, 20], type=pa.int64()),
        ],
        names=["a"],
    )
    ctx.register_record_batches("test_table", [[batch]])
    return ctx


def test_ffi_window_register():
    ctx = setup_context_with_table()
    my_udwf = udwf(MyRankUDF())
    ctx.register_udwf(my_udwf)

    result = ctx.sql(
        "select a, my_custom_rank() over (order by a) from test_table"
    ).collect()
    assert len(result) == 1
    assert result[0].num_columns == 2

    results = [
        (result[0][0][idx].as_py(), result[0][1][idx].as_py()) for idx in range(4)
    ]
    results.sort()

    expected = [
        (10, 1),
        (20, 2),
        (30, 3),
        (40, 4),
    ]
    assert results == expected


def test_ffi_window_call_directly():
    ctx = setup_context_with_table()
    my_udwf = udwf(MyRankUDF())

    result = (
        ctx.table("test_table")
        .select(col("a"), my_udwf().order_by(col("a")).build())
        .collect()
    )

    assert len(result) == 1
    assert result[0].num_columns == 2

    results = [
        (result[0][0][idx].as_py(), result[0][1][idx].as_py()) for idx in range(4)
    ]
    results.sort()

    expected = [
        (10, 1),
        (20, 2),
        (30, 3),
        (40, 4),
    ]
    assert results == expected


def test_ffi_window_from_bare_capsule():
    ctx = setup_context_with_table()
    my_udwf = udwf(MyRankUDF().__datafusion_window_udf__())

    result = (
        ctx.table("test_table")
        .select(col("a"), my_udwf().order_by(col("a")).build().alias("r"))
        .sort(col("a"))
    )
    assert result.collect_column("r").to_pylist() == [1, 2, 3, 4]