Unable to register UDAFs using SessionContext's `register_udaf`

[emanueledomingo]

Describe the bug
During the update of Datafusion from 39 to 41, my script got broken because the register_udaf crashes witht he following error:

in SessionContext.register_udaf(self, udaf)
    829 def register_udaf(self, udaf: AggregateUDF) -> None:
    830     """Register a user-defined aggregation function (UDAF) with the context."""
--> 831     self.ctx.register_udaf(udaf._udaf)

AttributeError: 'AggregateUDF' object has no attribute '_udaf'

To Reproduce
Steps to reproduce the behavior:

import datafusion as df
import pyarrow
import pyarrow.compute as pc
from typing import List

class AverageAccumulator(df.Accumulator):
    def __init__(self):
        self._sum = 0
        self._count = 0

    def update(self, values: pyarrow.Array) -> None:
        self._sum += pc.sum(values).as_py()
        self._count += len(values)

    def merge(self, other) -> None:
        self._sum += other._sum
        self._count += other._count

    def state(self) -> pyarrow.Array:
        return pyarrow.array([self._sum, self._count])

    def evaluate(self) -> pyarrow.Scalar:
        return pyarrow.scalar(self._sum / self._count)

average_udaf = df.udaf(
    AverageAccumulator,
    pyarrow.float64(),
    pyarrow.float64(),
    [pyarrow.float64()],
    'stable'
)

ctx = df.SessionContext()

ctx.register_udaf(average_udaf)

Additional context
The bug is introduce in datafusion 40.1.0

[timsaucer]

Verified. I have a fix I will push up tonight or first thing in the morning. Thank you for the bug report!

In the mean time, are you able to use the udaf via dataframe APIs? I tested the below without the correction, following your code:

import pyarrow as pa
from datafusion import col
batch = pa.RecordBatch.from_arrays(
    [
        pa.array([0, 1, 2, 3, 4, 5, 6]),
    ],
    names=["a"],
)

df = ctx.create_dataframe([[batch]])

df.aggregate([], average_udaf(col("a")).alias("udaf")).show()

returns

DataFrame()
+------+
| udaf |
+------+
| 3.0  |
+------+

[emanueledomingo]

By executing you code:

...
df.aggregate([], [average_udaf(col("a")).alias("udaf")]).show()

I correctly see the same result as you!

DataFrame()
+------+
| udaf |
+------+
| 3.0  |
+------+