paleolimbot opened a new pull request, #425:
URL: https://github.com/apache/arrow-nanoarrow/pull/425
I experimented with a few different methods here...I think this one has a
good balance of speed and not messing with the global precision.
```python
import pyarrow as pa
import decimal
from nanoarrow.iterator import iter_py
items = [decimal.Decimal("12.3450"), None, decimal.Decimal("1234567.3456")]
array = pa.array(items, pa.decimal128(11, 4))
list(iter_py(array))
#> [Decimal('12.3450'), None, Decimal('1234567.3456')]
```
This seems to be vaguely on par with pyarrow convert:
```python
import pyarrow as pa
import decimal
import numpy as np
from nanoarrow.iterator import iter_py
floats = np.random.random(int(1e6))
items = [decimal.Decimal(item) for item in floats]
array = pa.array(items)
%timeit array.to_pylist()
#> 799 ms ± 6.24 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
%timeit list(iter_py(array))
#> 431 ms ± 8.65 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
```
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