codeant-ai-for-open-source[bot] commented on code in PR #42752:
URL: https://github.com/apache/superset/pull/42752#discussion_r3718093918
##########
superset/models/helpers.py:
##########
@@ -4096,6 +4096,17 @@ def get_sqla_query( # pylint:
disable=too-many-arguments,too-many-locals,too-ma
else:
cond = is_null_cond
else:
+ # Normalize mixed int/float values before binding,
since
+ # SQLAlchemy may infer the bind parameter type from the
+ # first element and silently truncate other values
+ # (see #33206)
+ if target_generic_type ==
utils.GenericDataType.NUMERIC and any(
+ isinstance(v, float) for v in eq
+ ):
+ eq = [
+ float(v) if isinstance(v, (int, float)) else v
+ for v in eq
+ ]
Review Comment:
Agreed—the current conversion can corrupt integers above `2**53`, so this
should not be fixed by converting the original values to `float`.
A safer approach is to avoid mixing bind types altogether: keep integer
values in one `IN` predicate and floating-point values in another, then combine
them with `OR`:
```python
if (
target_generic_type == utils.GenericDataType.NUMERIC
and any(type(v) is float for v in eq)
and any(type(v) is int for v in eq)
):
integer_values = [v for v in eq if type(v) is int]
float_values = [v for v in eq if type(v) is float]
cond = or_(
sqla_col.in_(integer_values),
sqla_col.in_(float_values),
)
else:
cond = sqla_col.in_(eq)
```
This preserves values such as `9007199254740993` as integers while ensuring
the decimal values are bound as floats. The regression test should also include
a large integer mixed with a fractional value to verify that exact integer
precision is retained.
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