feat(catalog): preserve and display dataset value scores
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@@ -37,7 +37,7 @@ class CatalogFilters(Scope):
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field_type: str | None = None
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coverage_min: float | None = Field(default=None, ge=0, le=1)
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sort: Literal[
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"id", "name", "category", "field_count", "coverage", "user_count", "alpha_count", "field_type"
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"id", "name", "category", "field_count", "coverage", "user_count", "alpha_count", "field_type", "value_score"
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] = "name"
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direction: Literal["asc", "desc"] = "asc"
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limit: int = Field(default=25, ge=1, le=100)
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@@ -80,6 +80,7 @@ class EntryOutput(BaseModel):
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category: str | None
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subcategory: str | None
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field_type: str | None
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value_score: float | None = None
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coverage: float | None
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user_count: int | None
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alpha_count: int | None
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@@ -55,6 +55,7 @@ def normalize(raw, dataset_id):
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subcategory=label(raw.get("subcategory")),
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field_type=label(raw.get("type")) if dataset_id else None,
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coverage=coverage,
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value_score=number(raw.get("valueScore")) if not dataset_id else None,
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user_count=number(raw.get("userCount"), True),
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alpha_count=number(raw.get("alphaCount"), True),
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field_count=number(raw.get("fieldCount"), True),
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@@ -357,6 +357,7 @@ class CatalogEntry(Base):
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subcategory: Mapped[str | None] = mapped_column(String(200))
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field_type: Mapped[str | None] = mapped_column(String(100))
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coverage: Mapped[float | None] = mapped_column(Float)
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value_score: Mapped[float | None] = mapped_column(Float)
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user_count: Mapped[int | None] = mapped_column(Integer)
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alpha_count: Mapped[int | None] = mapped_column(Integer)
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field_count: Mapped[int | None] = mapped_column(Integer)
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@@ -0,0 +1,17 @@
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"""Preserve the upstream dataset value score; old snapshots remain unknown."""
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import sqlalchemy as sa
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from alembic import op
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revision = "0009"
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down_revision = "0008"
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branch_labels = None
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depends_on = None
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def upgrade():
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op.add_column("catalog_entries", sa.Column("value_score", sa.Float(), nullable=True))
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def downgrade():
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op.drop_column("catalog_entries", "value_score")
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@@ -37,6 +37,7 @@ def catalog_response(request, fields=None):
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"category": {"name": "基本面"},
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"subcategory": {"name": "财务报表"},
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"fieldCount": 123,
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"valueScore": 2.0,
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"description": "合成数据,仅用于验收",
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},
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{
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@@ -45,6 +46,7 @@ def catalog_response(request, fields=None):
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"category": {"name": "新闻"},
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"subcategory": {"name": "情绪"},
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"fieldCount": 3,
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"valueScore": 0.0,
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},
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{"id": "TEST_UNKNOWN", "name": "TEST 未分类", "fieldCount": 0},
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]
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@@ -279,3 +279,17 @@ async def test_dynamic_platform_scopes_and_validation(catalog):
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runner.client.disconnect()
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assert (await client.get(BASE + "/scopes")).status_code == 409
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assert (await search(client))["total"] == 0
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async def test_dataset_value_score_survives_sync_and_sorts_null_last(catalog):
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client, _, _ = catalog
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assert (await sync(catalog))["status"] == "completed"
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rows = (await search(client, sort="value_score", direction="desc"))["items"]
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assert [(row["id"], row["value_score"]) for row in rows] == [
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("TEST_FIN", 2.0), ("TEST_NEWS", 0.0), ("TEST_UNKNOWN", None)
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]
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rows = (await search(client, sort="value_score", direction="asc"))["items"]
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assert [row["value_score"] for row in rows] == [0.0, 2.0, None]
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assert (await search(client, "/datasets/TEST_FIN"))["value_score"] == 2.0
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assert (await search(client, "/datasets/TEST_NEWS"))["value_score"] == 0.0
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assert (await search(client, "/datasets/TEST_UNKNOWN"))["value_score"] is None
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@@ -66,6 +66,7 @@ type Entry = {
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subcategory: string | null;
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field_type: string | null;
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coverage: number | null;
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value_score: number | null;
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user_count: number | null;
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alpha_count: number | null;
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field_count: number | null;
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@@ -732,6 +733,12 @@ export function DatasetPage({
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width: 120,
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render: (_, row) => row.complete_count ?? displayValue(row.field_count),
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},
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{
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title: sortTitle("价值评分", "value_score"),
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width: 120,
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render: (_, row) =>
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row.value_score == null ? "未提供" : row.value_score.toFixed(1),
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},
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{
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title: "同步状态",
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width: 120,
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@@ -1057,7 +1064,7 @@ export function DatasetPage({
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rowKey="id"
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size="small"
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pagination={false}
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scroll={{ x: 884, y: "100%" }}
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scroll={{ x: 1004, y: "100%" }}
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empty={
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<Empty
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description={
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@@ -1211,6 +1218,10 @@ export function DatasetPage({
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: {
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分类: displayValue(detailData.category),
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子分类: displayValue(detailData.subcategory),
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"价值评分 (Value Score)":
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detailData.value_score == null
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? "未提供"
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: detailData.value_score.toFixed(2),
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字段数:
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detailData.complete_count ??
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displayValue(detailData.field_count),
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