Python worker crashes with "Unmatched type" when a field value is a numpy scalar (np.int64 / np.bool_)

[eugenegujing]

What happened?

A Python operator that outputs a numpy scalar into an INTEGER/LONG or BOOLEAN field crashes the worker with a TypeError: Unmatched type ....

Idiomatic pandas code produces numpy scalars very naturally:

• df["x"].sum() / .max() / .count() return numpy.int64
• df["x"].any() or any numpy comparison returns numpy.bool_

On output, Tuple.finalize(schema) runs a strict isinstance(value, expected_python_type) check in validate_schema. Because numpy's integer and bool scalar types are not subclasses of Python int / bool (isinstance(np.int64(5), int) is False, isinstance(np.bool_(True), bool) is False), the check fails even though the value is semantically correct, and the operator crashes.

Observed errors:

• TypeError: Unmatched type for field 'total_age', expected AttributeType.INT, got <n> (<class 'numpy.int64'>)
• TypeError: Unmatched type for field 'has_senior', expected AttributeType.BOOL, got True (<class 'numpy.bool'>)

What I expected: the value should be accepted. np.int64(5) is exactly the integer 5 and the declared field is INTEGER; np.bool_(True) is the boolean True and the field is BOOLEAN. This is the same class of issue already fixed for integral floats in #6053 — that fix only covered np.float64 (which happens to subclass Python float); numpy integer/bool scalars are still rejected.

How to reproduce?

Minimal workflow: CSV File Scan (any dataset with an integer column) → Python UDF.

A) numpy.int64 into an INTEGER field — Python UDF code, add output column total_age : integer:

from pytexera import *

class ProcessTableOperator(UDFTableOperator):

    @overrides
    def process_table(self, table: Table, port: int) -> Iterator[Optional[TableLike]]:
        yield {"total_age": table["age"].sum()} 

B) numpy.bool_ into a BOOLEAN field — Python UDF code, add output column has_senior : boolean:

from pytexera import *

class ProcessTableOperator(UDFTableOperator):

    @overrides
    def process_table(self, table: Table, port: int) -> Iterator[Optional[TableLike]]:
        yield {"has_senior": (table["age"] > 60).any()} 

Run the workflow; the Python UDF fails immediately with the Unmatched type TypeError shown in the console (tuple:validate_schema).

The same crash can also be reproduced with the Python Table Reducer operator (Output columns: total_age / integer / table["age"].sum() and has_senior / boolean / (table["age"] > 60).any()), since numpy scalars are produced by any pandas-based Python operator.

Version/Branch

1.3.0-incubating-SNAPSHOT (main)

Commit Hash (Optional)

No response

What browsers are you seeing the problem on?

No response

Relevant log output

[eugenegujing]

/take