GitHub user kz930 added a comment to the discussion: Scaling verification of
workflow to Python translation — looking for input
Update since the design discussion above.
**Auto-config — the direction held up.** An operator's config is derived from
what it already declares:
- Four rules: min/max from `@JsonSchemaInject`; numbers by a priority ladder
(declared default → midpoint of
range → row-count); enums swept over every value; booleans swept true/false.
- Column-name fields are filled from the shared canonical fixture: explicit
`@SampleColumn` pick → first unused
type-matching column → fallback.
- These rules produce a valid config for **136 of the 140** non-source
operators. The 4 exceptions are a generic
`HyperParameters[T]` field whose type is erased at runtime.
- Sources are handled separately — one small shared dataset encoded into
whatever format each source declares
(CSV / JSONL / Arrow), plus two hand-written cases.
**End-to-end verification**
- **53 operators** now run both paths and match, in ~8s locally; wired into
CI as its own integration-test job.
- Verification surfaced **10 real bugs** in existing operators; 8 are already
fixed upstream.
GitHub link:
https://github.com/apache/texera/discussions/6072#discussioncomment-17802826
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