l1t1 opened a new issue, #1190:
URL: https://github.com/apache/datafusion-python/issues/1190
**Describe the bug**
when I run it, it raise an error as following, both `assert
result_df.to_pydict()["a"] == [1, 3]` and `print(result_df)` are faild
```python
C:\d>python udaf.py
Traceback (most recent call last):
File "C:\d\udaf.py", line 68, in <module>
assert result_df.to_pydict()["a"] == [1, 3]
~~~~~~~~~~~~~~~~~~~^^
File
"C:\Users\lt\AppData\Local\Programs\Python\Python313\Lib\site-packages\datafusion\dataframe.py",
line 1060, in to_pydict
return self.df.to_pydict()
~~~~~~~~~~~~~~~~~^^
Exception: DataFusion error: Execution("ArrowInvalid: Could not convert
<pyarrow.lib.DoubleArray object at 0x0000022AFC1A6620>\n[\n 9\n] with type
pyarrow.lib.DoubleArray: did not recognize Python value type when inferring an
Arrow data type")
C:\d>python udaf.py
Traceback (most recent call last):
File "C:\d\udaf.py", line 70, in <module>
print(result_df)
~~~~~^^^^^^^^^^^
File
"C:\Users\lt\AppData\Local\Programs\Python\Python313\Lib\site-packages\datafusion\dataframe.py",
line 324, in __repr__
return self.df.__repr__()
~~~~~~~~~~~~~~~~^^
Exception: DataFusion error: Execution("ArrowInvalid: Could not convert
<pyarrow.lib.DoubleArray object at 0x0000021F129D6620>\n[\n 9\n] with type
pyarrow.lib.DoubleArray: did not recognize Python value type when inferring an
Arrow data type")
```
**To Reproduce**
edit the udaf.py as following (copied from the source code tree)
```python
import pyarrow as pa
from datafusion import Accumulator, SessionContext, udaf
# Define a user-defined aggregation function (UDAF)
class MyAccumulator(Accumulator):
"""
Interface of a user-defined accumulation.
"""
def __init__(self) -> None:
self._sum = pa.scalar(0.0)
def update(self, values: pa.Array) -> None:
# not nice since pyarrow scalars can't be summed yet. This breaks on
`None`
self._sum = pa.scalar(self._sum.as_py() +
pa.compute.sum(values).as_py())
def merge(self, states: pa.Array) -> None:
# not nice since pyarrow scalars can't be summed yet. This breaks on
`None`
self._sum = pa.scalar(self._sum.as_py() +
pa.compute.sum(states).as_py())
def state(self) -> pa.Array:
return pa.array([self._sum.as_py()])
def evaluate(self) -> pa.Scalar:
return self._sum
my_udaf = udaf(
MyAccumulator,
pa.float64(),
pa.float64(),
[pa.float64()],
"stable",
# This will be the name of the UDAF in SQL
# If not specified it will by default the same as accumulator class name
name="my_accumulator",
)
# Create a context
ctx = SessionContext()
# Create a datafusion DataFrame from a Python dictionary
source_df = ctx.from_pydict({"a": [1, 1, 3], "b": [4, 5, 6]}, name="t")
# Dataframe:
# +---+---+
# | a | b |
# +---+---+
# | 1 | 4 |
# | 1 | 5 |
# | 3 | 6 |
# +---+---+
# Register UDF for use in SQL
ctx.register_udaf(my_udaf)
# Query the DataFrame using SQL
result_df = ctx.sql(
"select a, my_accumulator(b) as b_aggregated from t group by a order by
a"
)
# Dataframe:
# +---+--------------+
# | a | b_aggregated |
# +---+--------------+
# | 1 | 9 |
# | 3 | 6 |
# +---+--------------+
#assert result_df.to_pydict()["a"] == [1, 3]
#assert result_df.to_pydict()["b_aggregated"] == [9, 6]
print(result_df)
```
**Expected behavior**
it prints
```python
# +---+--------------+
# | a | b_aggregated |
# +---+--------------+
# | 1 | 9 |
# | 3 | 6 |
# +---+--------------+
```
**Additional context**
Add any other context about the problem here.
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