Class FlattenRoundTripTests

tests/knowledge/test_roundtrip.py:38–91

def _ext() -> ExtractionRef:
    return ExtractionRef(flow="test_flow", model="gpt-4o", extracted_at=_now())


class FlattenRoundTripTests(unittest.TestCase):
    def test_news(self):
        n = News(
            as_of=_now(),
            source=_src("rss"),
            extraction=_ext(),
            headline="Fed holds rates",
            event_type="monetary_policy",
            timestamp=_now(),
            entities=["FOMC"],
        )
        revived = News.model_validate_json(n.model_dump_json())
        self.assertEqual(n, revived)

    def test_earnings(self):
        e = Earnings(
            as_of=_now(),
            source=_src("http"),
            ticker="AAPL",
            period="2026Q1",
            revenue=120.0,
            eps=1.55,
            surprise_flags=["eps_beat"],
        )
        revived = Earnings.model_validate_json(e.model_dump_json())
        self.assertEqual(e, revived)

    def test_factor(self):
        f = Factor(
            as_of=_now(),
            source=_src(),
            factor_name="value",
            universe="us_equities",
        )
        revived = Factor.model_validate_json(f.model_dump_json())
        self.assertEqual(f, revived)

    def test_thesis(self):
        t = Thesis(as_of=_now(), source=_src(), claim="USD softens")
        revived = Thesis.model_validate_json(t.model_dump_json())
        self.assertEqual(t, revived)


class TreeRoundTripTests(unittest.TestCase):
    def _build_paper(self) -> LegacyPaper:
        leaf_id = uuid4()
        root_id = uuid4()
        leaf = TreeNode(
            node_id=leaf_id,
            parent_id=root_id,
            position=0,
            title="Methodology",
            summary="cross-sectional momentum signal",
            content="We rank stocks by 12-1 month returns ...",
        )