fallintoplace opened a new issue, #3404:
URL: https://github.com/apache/iceberg-python/issues/3404
## Summary
Large integral string values lose precision in two runtime conversion paths
because they round-trip through `float` before converting to `int`.
This causes valid 64-bit values to be corrupted, including `LongType.max`.
## Affected paths
- `StringLiteral.to(LongType)` in `pyiceberg/expressions/literals.py`
- `partition_to_py` for `LongType`, `TimestampType`, `TimestampNanoType`,
`TimestamptzType`, and `TimestamptzNanoType` in `pyiceberg/conversions.py`
## Minimal repro
```python
from pyiceberg.expressions.literals import literal
from pyiceberg.conversions import partition_to_py
from pyiceberg.types import LongType, TimestampNanoType
print(literal(str(LongType.max)).to(LongType()))
print(literal("9007199254740993").to(LongType()).value)
print(partition_to_py(LongType(), "9007199254740993"))
print(partition_to_py(TimestampNanoType(), "9007199254740993"))
```
## Actual
```python
LongAboveMax
9007199254740992
9007199254740992
9007199254740992
```
## Expected
```python
LongLiteral(9223372036854775807)
9007199254740993
9007199254740993
9007199254740993
```
## Why this happens
Both code paths currently do `int(float(...))`, which loses precision for
large integer values above the IEEE-754 exact integer range.
In particular, this makes `literal(str(LongType.max)).to(LongType())` return
`LongAboveMax` even though `LongType.max` is valid by definition.
## Notes
This looks like one underlying bug rather than two separate issues, since
both paths have the same precision-loss mechanism.
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