diff --git a/.scratch/alpha-list-columns/issues/01-implement.md b/.scratch/alpha-list-columns/issues/01-implement.md new file mode 100644 index 0000000..532229b --- /dev/null +++ b/.scratch/alpha-list-columns/issues/01-implement.md @@ -0,0 +1,17 @@ +# 补齐 Alpha 列表和标签入口 + +Type: task +Status: ready-for-agent +Implementation: completed + +范围与验收见 ../spec.md。 + +## Comments + +- 已确认失败分档使用 FAIL=1 / FAIL≥2，正在实现。 +- 已完成九个新增表头、指标范围筛选/排序/导出、检查结果分档筛选、单条自定义标签编辑与默认标签列。保留已有列偏好。 +- 验证：后端全量 269 项通过；Ruff、Prettier、前端构建及 diff 检查通过。 +- 浏览器全量首跑 20 项通过、2 项失败：一项 SQLite 锁冲突，单独复跑通过；另一项涉及标签改名和列设置过长，更新断言并修复限高滚动后，workspace 两项通过。 +- Playwright CLI 实测 FAIL≥2 包含失败 2/3 项、PPAC 标签保存与组合筛选、刷新保留、390px 无整页溢出、26 项列设置可滚动并关闭。 +- SQLite 和独立 PostgreSQL 17 数据库均验证 503 条历史快照回填、迁移回退/重新升级、模型一致及原研究标签/备注/版本保留。已删除本轮临时数据库。 +- 已包含 0011 迁移；没有部署、提交代码或操作真实平台。 diff --git a/.scratch/alpha-list-columns/spec.md b/.scratch/alpha-list-columns/spec.md new file mode 100644 index 0000000..51aaf51 --- /dev/null +++ b/.scratch/alpha-list-columns/spec.md @@ -0,0 +1,12 @@ +# Alpha 列表指标、检查筛选与自定义标签 + +用户已授权本地实现。失败分档已确认：FAIL=1、FAIL≥2。 + +- 补充检查结果、失败项、子股票池/稳健股票池/近两年 Sharpe、中性化、平台生产相关性、IS PnL、同步时间。 +- 默认显示检查结果、失败项和自定义标签；保留已有列偏好，其余字段可选。 +- 检查结果按平台快照计算，与平台状态、研究状态及本地自相关独立。没有完成的检查不得视为通过。 +- 指标支持范围筛选、排序及导出；检查筛选在数据库分页前执行。 +- 复用本地标签，提供列表单条编辑、批量编辑和筛选，支持 PPAC 等任意标签，平台同步不覆盖。 +- 历史快照通过增量迁移回填，不请求平台、不修改研究记录。 + +验证：API 失败 0/1/2/3 项及未知状态、组合筛选/分页/导出、零值与缺值、标签保存与同步保留；隔离迁移；前端构建及浏览器交互。 diff --git a/backend/app/alphas.py b/backend/app/alphas.py index 35bef44..cf52a8d 100644 --- a/backend/app/alphas.py +++ b/backend/app/alphas.py @@ -9,6 +9,55 @@ from sqlalchemy import or_, select, update from .models import Alpha, Research, ResearchTag, SelfCorrelation, now from .research.provenance import source_alpha_ids +METRIC_FIELDS = ( + "sharpe", "fitness", "returns", "turnover", "margin", "drawdown", + "sub_universe_sharpe", "robust_universe_sharpe", "two_year_sharpe", "prod_correlation", "pnl", +) + + +def failed_checks(checks): + """Return failed platform check names; local correlation never changes this list.""" + return [ + check.get("name") if isinstance(check.get("name"), str) else "未命名检查" + for check in checks if isinstance(check, dict) and check.get("result") == "FAIL" + ] if isinstance(checks, list) else [] + + +def snapshot_columns(settings, metrics, checks): + """Derive list fields from a platform snapshot, preserving missing metrics as null. + + Only explicit FAIL results count. Empty, malformed and unfinished checks are + pending; all known checks passing without PROD_CORRELATION is only a pre-check. + No submission eligibility or activity eligibility is inferred here. + """ + settings = settings if isinstance(settings, dict) else {} + metrics = metrics if isinstance(metrics, dict) else {} + checks = checks if isinstance(checks, list) else [] + valid = [check for check in checks if isinstance(check, dict)] + failures = len(failed_checks(checks)) + by_name = {check["name"]: check for check in valid if isinstance(check.get("name"), str)} + if failures: + check_type = "FAIL_1" if failures == 1 else "FAIL_2" + elif not checks or len(valid) != len(checks) or any(check.get("result") != "PASS" for check in valid): + check_type = "PENDING" + else: + check_type = "PASS" if "PROD_CORRELATION" in by_name else "PRE_CHECK" + neutralization = settings.get("neutralization") + return { + "check_type": check_type, + "neutralization": neutralization if isinstance(neutralization, str) else None, + "pnl": number(metrics.get("pnl")), + **{ + field: number(by_name.get(name, {}).get("value")) + for field, name in ( + ("sub_universe_sharpe", "LOW_SUB_UNIVERSE_SHARPE"), + ("robust_universe_sharpe", "LOW_ROBUST_UNIVERSE_SHARPE"), + ("two_year_sharpe", "LOW_2Y_SHARPE"), + ("prod_correlation", "PROD_CORRELATION"), + ) + }, + } + def submission_condition(submission): """Match the platform list contract; a missing status is never assumed submitted.""" @@ -106,6 +155,8 @@ async def upsert_alpha(db, raw: dict): item.settings, item.is_metrics = sanitize(settings), sanitize(metrics) item.os_metrics = sanitize(raw.get("os")) if isinstance(raw.get("os"), dict) else {} item.checks = sanitize(metrics.get("checks") or raw.get("checks") or []) + for key, value in snapshot_columns(item.settings, item.is_metrics, item.checks).items(): + setattr(item, key, value) for key in ("sharpe", "fitness", "returns", "turnover", "margin", "drawdown"): setattr(item, key, number(metrics.get(key))) item.date_created, item.date_submitted = date(raw.get("dateCreated")), date(raw.get("dateSubmitted")) @@ -134,7 +185,7 @@ def list_statement(filters): ) ) ) - for name in ("region", "universe", "alpha_type", "language", "status", "stage", "hidden"): + for name in ("region", "universe", "alpha_type", "language", "status", "stage", "hidden", "check_type", "neutralization"): value = getattr(filters, name) if value is not None: query = query.where(getattr(Alpha, name) == value) @@ -148,7 +199,7 @@ def list_statement(filters): query = query.where(Alpha.date_created >= filters.created_from) if filters.created_to: query = query.where(Alpha.date_created <= filters.created_to) - for name in ("sharpe", "fitness", "returns", "turnover", "margin", "drawdown"): + for name in METRIC_FIELDS: for suffix, compare in (("min", "ge"), ("max", "le")): value = getattr(filters, f"{name}_{suffix}") if value is not None: @@ -183,8 +234,16 @@ def summary(item: Alpha, research: Research): "date_created", "date_submitted", "synced_at", + "check_type", + "neutralization", + "sub_universe_sharpe", + "robust_universe_sharpe", + "two_year_sharpe", + "prod_correlation", + "pnl", ) result = {k: getattr(item, k) for k in keys} + result["failed_checks"] = failed_checks(item.checks) result["expression_preview"] = (item.expression or item.selection or "")[:240] result["research"] = { k: getattr(research, k) for k in ("note", "tags", "favorite", "state", "updated_at", "version") diff --git a/backend/app/main.py b/backend/app/main.py index e93ab8f..4bec0d2 100644 --- a/backend/app/main.py +++ b/backend/app/main.py @@ -16,7 +16,7 @@ from sqlalchemy import delete, select, text from .ai.routes import router as ai_router from .ai.runtime import AIRuntime -from .alphas import list_statement, sorted_statement +from .alphas import failed_checks, list_statement, sorted_statement from .backtests.routes import router as backtest_router from .business import Business, notify_job from .catalog.research_routes import router as research_catalog_router @@ -375,11 +375,18 @@ def create_app(settings=None, wq_client=None, ai_model_factory=None): "turnover", "margin", "drawdown", + "sub_universe_sharpe", + "robust_universe_sharpe", + "two_year_sharpe", + "prod_correlation", + "pnl", + "neutralization", + "check_type", "date_created", "date_submitted", "synced_at", ] - writer.writerow(columns + ["research_state", "favorite", "tags", "note"]) + writer.writerow(columns + ["failed_checks", "research_state", "favorite", "tags", "note"]) yield buffer.getvalue() buffer.seek(0) buffer.truncate(0) @@ -388,7 +395,7 @@ def create_app(settings=None, wq_client=None, ai_model_factory=None): async for a, r in rows: writer.writerow( [csv_cell(getattr(a, key)) for key in columns] - + [r.state, r.favorite, csv_cell(";".join(r.tags)), csv_cell(r.note)] + + [csv_cell(";".join(failed_checks(a.checks))), r.state, r.favorite, csv_cell(";".join(r.tags)), csv_cell(r.note)] ) yield buffer.getvalue() buffer.seek(0) diff --git a/backend/app/models.py b/backend/app/models.py index c54c87a..3b297b4 100644 --- a/backend/app/models.py +++ b/backend/app/models.py @@ -79,6 +79,13 @@ class Alpha(Base): turnover: Mapped[float | None] = mapped_column(Float) margin: Mapped[float | None] = mapped_column(Float) drawdown: Mapped[float | None] = mapped_column(Float) + sub_universe_sharpe: Mapped[float | None] = mapped_column(Float) + robust_universe_sharpe: Mapped[float | None] = mapped_column(Float) + two_year_sharpe: Mapped[float | None] = mapped_column(Float) + prod_correlation: Mapped[float | None] = mapped_column(Float) + pnl: Mapped[float | None] = mapped_column(Float) + neutralization: Mapped[str | None] = mapped_column(Text) + check_type: Mapped[str] = mapped_column(String(20), default="PENDING", server_default="PENDING", index=True) date_created: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), index=True) date_submitted: Mapped[datetime | None] = mapped_column(DateTime(timezone=True)) synced_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=now) diff --git a/backend/app/schemas.py b/backend/app/schemas.py index 685ba1e..22d98a6 100644 --- a/backend/app/schemas.py +++ b/backend/app/schemas.py @@ -9,6 +9,7 @@ from pydantic import BaseModel, ConfigDict, Field, field_validator, model_valida ResearchState = Literal["inbox", "candidate", "optimizing", "archived"] Submission = Literal["UNSUBMITTED", "SUBMITTED"] +CheckType = Literal["PENDING", "PRE_CHECK", "PASS", "FAIL_1", "FAIL_2"] SortField = Literal[ "id", "name", @@ -18,6 +19,11 @@ SortField = Literal[ "turnover", "margin", "drawdown", + "sub_universe_sharpe", + "robust_universe_sharpe", + "two_year_sharpe", + "prod_correlation", + "pnl", "date_created", "date_submitted", "synced_at", @@ -76,6 +82,8 @@ class AlphaFilters(Contract): status: str | None = None stage: str | None = None hidden: bool | None = None + check_type: CheckType | None = None + neutralization: str | None = None research_state: ResearchState | None = None favorite: bool | None = None tag: str | None = Field(default=None, max_length=60) @@ -93,6 +101,16 @@ class AlphaFilters(Contract): margin_max: float | None = None drawdown_min: float | None = None drawdown_max: float | None = None + sub_universe_sharpe_min: float | None = None + sub_universe_sharpe_max: float | None = None + robust_universe_sharpe_min: float | None = None + robust_universe_sharpe_max: float | None = None + two_year_sharpe_min: float | None = None + two_year_sharpe_max: float | None = None + prod_correlation_min: float | None = None + prod_correlation_max: float | None = None + pnl_min: float | None = None + pnl_max: float | None = None sort: SortField = "date_created" direction: Literal["asc", "desc"] = "desc" limit: int = Field(default=25, ge=1, le=100) @@ -105,7 +123,10 @@ class AlphaFilters(Contract): @model_validator(mode="after") def range_order(self): - for key in ("sharpe", "fitness", "returns", "turnover", "margin", "drawdown"): + for key in ( + "sharpe", "fitness", "returns", "turnover", "margin", "drawdown", + "sub_universe_sharpe", "robust_universe_sharpe", "two_year_sharpe", "prod_correlation", "pnl", + ): lo, hi = getattr(self, f"{key}_min"), getattr(self, f"{key}_max") if lo is not None and hi is not None and lo > hi: raise ValueError(f"{key} 最小值不能大于最大值") @@ -222,6 +243,14 @@ class AlphaSummary(BaseModel): date_created: datetime | None date_submitted: datetime | None synced_at: datetime + check_type: CheckType = "PENDING" + failed_checks: list[str] = Field(default_factory=list) + neutralization: str | None = None + sub_universe_sharpe: float | None = None + robust_universe_sharpe: float | None = None + two_year_sharpe: float | None = None + prod_correlation: float | None = None + pnl: float | None = None research: ResearchOutput local_correlation: dict | None = None source_kinds: list[str] = Field(default_factory=list) diff --git a/backend/migrations/versions/0011_alpha_list_checks_and_metrics.py b/backend/migrations/versions/0011_alpha_list_checks_and_metrics.py new file mode 100644 index 0000000..f689cf8 --- /dev/null +++ b/backend/migrations/versions/0011_alpha_list_checks_and_metrics.py @@ -0,0 +1,125 @@ +"""Index Alpha checks and metrics; backfill existing snapshots without upstream calls.""" + +import math + +import sqlalchemy as sa +from alembic import op + +revision = "0011" +down_revision = "0010" +branch_labels = None +depends_on = None + + +# Frozen normalization for historical snapshots; do not import mutable app code. +def number(value): + if value is None or isinstance(value, bool): + return None + try: + result = float(value) + return result if math.isfinite(result) else None + except (ValueError, TypeError): + return None + + +def failed_checks(checks): + """Return failed platform check names; local correlation never changes this list.""" + return ( + [ + check.get("name") if isinstance(check.get("name"), str) else "未命名检查" + for check in checks + if isinstance(check, dict) and check.get("result") == "FAIL" + ] + if isinstance(checks, list) + else [] + ) + + +def snapshot_columns(settings, metrics, checks): + """Derive list fields from a platform snapshot, preserving missing metrics as null. + + Only explicit FAIL results count. Empty, malformed and unfinished checks are + pending; all known checks passing without PROD_CORRELATION is only a pre-check. + No submission eligibility or activity eligibility is inferred here. + """ + settings = settings if isinstance(settings, dict) else {} + metrics = metrics if isinstance(metrics, dict) else {} + checks = checks if isinstance(checks, list) else [] + valid = [check for check in checks if isinstance(check, dict)] + failures = len(failed_checks(checks)) + by_name = {check["name"]: check for check in valid if isinstance(check.get("name"), str)} + if failures: + check_type = "FAIL_1" if failures == 1 else "FAIL_2" + elif not checks or len(valid) != len(checks) or any(check.get("result") != "PASS" for check in valid): + check_type = "PENDING" + else: + check_type = "PASS" if "PROD_CORRELATION" in by_name else "PRE_CHECK" + neutralization = settings.get("neutralization") + return { + "check_type": check_type, + "neutralization": neutralization if isinstance(neutralization, str) else None, + "pnl": number(metrics.get("pnl")), + **{ + field: number(by_name.get(name, {}).get("value")) + for field, name in ( + ("sub_universe_sharpe", "LOW_SUB_UNIVERSE_SHARPE"), + ("robust_universe_sharpe", "LOW_ROBUST_UNIVERSE_SHARPE"), + ("two_year_sharpe", "LOW_2Y_SHARPE"), + ("prod_correlation", "PROD_CORRELATION"), + ) + }, + } + + +METRICS = ("sub_universe_sharpe", "robust_universe_sharpe", "two_year_sharpe", "prod_correlation", "pnl") + + +def upgrade(): + columns = [sa.Column(name, sa.Float(), nullable=True) for name in METRICS] + columns += [ + sa.Column("neutralization", sa.Text(), nullable=True), + sa.Column("check_type", sa.String(20), nullable=False, server_default="PENDING"), + ] + for column in columns: + op.add_column("alphas", column) + op.create_index("ix_alphas_check_type", "alphas", ["check_type"]) + table = sa.table( + "alphas", + sa.column("id", sa.String()), + sa.column("settings", sa.JSON()), + sa.column("is_metrics", sa.JSON()), + sa.column("checks", sa.JSON()), + *(sa.column(column.name, column.type) for column in columns), + ) + connection = op.get_bind() + last_id = None + while True: + query = ( + sa.select(table.c.id, table.c.settings, table.c.is_metrics, table.c.checks) + .order_by(table.c.id) + .limit(500) + ) + if last_id is not None: + query = query.where(table.c.id > last_id) + rows = connection.execute(query).mappings().all() + if not rows: + break + connection.execute( + table.update() + .where(table.c.id == sa.bindparam("snapshot_id")) + .values({column.name: sa.bindparam(column.name) for column in columns}), + [ + { + "snapshot_id": row["id"], + **snapshot_columns(row["settings"], row["is_metrics"], row["checks"]), + } + for row in rows + ], + ) + last_id = rows[-1]["id"] + + +def downgrade(): + op.drop_index("ix_alphas_check_type", table_name="alphas") + for name in ("check_type", "neutralization", *reversed(METRICS)): + op.drop_column("alphas", name) diff --git a/backend/tests/test_alpha_list_fields.py b/backend/tests/test_alpha_list_fields.py new file mode 100644 index 0000000..09b72b0 --- /dev/null +++ b/backend/tests/test_alpha_list_fields.py @@ -0,0 +1,227 @@ +"""Alpha list filtering, snapshot extraction, local tags and historical migration.""" + +import csv +import io +from pathlib import Path + +import pytest +import sqlalchemy as sa +from alembic import command +from alembic.config import Config +from cryptography.fernet import Fernet + +from app.alphas import snapshot_columns, upsert_alpha +from tests.conftest import alpha + +PREFIX = "/api/v1/alphas" + + +def checks(failures): + return [ + {"name": name, "result": "FAIL" if index < failures else "PASS", "value": value} + for index, (name, value) in enumerate( + [ + ("LOW_SUB_UNIVERSE_SHARPE", 0), + ("LOW_ROBUST_UNIVERSE_SHARPE", 1.2), + ("LOW_2Y_SHARPE", 2.3), + ("PROD_CORRELATION", 0), + ] + ) + ] + + +@pytest.mark.parametrize( + "data, expected", + [ + ([], "PENDING"), + (None, "PENDING"), + ([None], "PENDING"), + ([{}], "PENDING"), + ([{"name": "LOW_SHARPE", "result": "WARNING"}], "PENDING"), + ([{"name": "LOW_SHARPE", "result": "PASS"}], "PRE_CHECK"), + ([{"name": "PROD_CORRELATION", "result": "PENDING"}], "PENDING"), + (checks(0), "PASS"), + (checks(1), "FAIL_1"), + (checks(2), "FAIL_2"), + (checks(3), "FAIL_2"), + ], +) +def test_check_classification_never_promotes_unknown_results(data, expected): + assert snapshot_columns({}, {}, data)["check_type"] == expected + + +async def test_checks_filter_before_pagination_and_share_export_scope(app, logged_in): + async with app.state.sessions.begin() as db: + for count in range(4): + await upsert_alpha(db, alpha(f"failed{count}", **{"is": {"pnl": 0, "checks": checks(count)}})) + await upsert_alpha(db, alpha("unknown", **{"is": {}})) + for check_type, expected in [ + ("FAIL_1", ["failed1"]), + ("FAIL_2", ["failed2", "failed3"]), + ("PASS", ["failed0"]), + ("PENDING", ["unknown"]), + ]: + response = await logged_in.get( + PREFIX, params={"check_type": check_type, "sort": "id", "direction": "asc"} + ) + assert response.status_code == 200 + assert [row["id"] for row in response.json()["items"]] == expected + query = "check_type=FAIL_2&submission=UNSUBMITTED®ion=USA&limit=1&offset=1&sort=id&direction=asc" + page = (await logged_in.get(f"{PREFIX}?{query}")).json() + assert page["total"] == 2 and [a["id"] for a in page["items"]] == ["failed3"] + row = page["items"][0] + assert row["failed_checks"] == ["LOW_SUB_UNIVERSE_SHARPE", "LOW_ROBUST_UNIVERSE_SHARPE", "LOW_2Y_SHARPE"] + assert row["prod_correlation"] == row["sub_universe_sharpe"] == row["pnl"] == 0 + exported = await logged_in.get(f"{PREFIX}/export?{query}") + rows = list(csv.DictReader(io.StringIO(exported.text.lstrip("\ufeff")))) + assert [r["id"] for r in rows] == ["failed2", "failed3"] + assert rows[0]["check_type"] == "FAIL_2" and rows[0]["pnl"] == "0.0" + assert rows[0]["failed_checks"] == "LOW_SUB_UNIVERSE_SHARPE;LOW_ROBUST_UNIVERSE_SHARPE" + assert (await logged_in.get(f"{PREFIX}?check_type=FAIL_GT_2")).status_code == 422 + + +async def test_extended_metrics_filter_sort_missing_values_and_snapshot_refresh(app, logged_in): + fields = ["sub_universe_sharpe", "robust_universe_sharpe", "two_year_sharpe", "prod_correlation", "pnl"] + async with app.state.sessions.begin() as db: + for name, value in [("zero", 0), ("positive", 2), ("negative", -1)]: + sample_checks = [{**c, "value": value} for c in checks(0)] + await upsert_alpha( + db, + alpha( + name, + settings={"neutralization": "INDUSTRY"}, + **{"is": {"pnl": value, "checks": sample_checks}}, + ), + ) + await upsert_alpha(db, alpha("missing", **{"is": {}})) + for field in fields: + result = (await logged_in.get(PREFIX, params={"sort": field, "direction": "asc"})).json() + assert [r["id"] for r in result["items"]] == ["negative", "zero", "positive", "missing"] + result = ( + await logged_in.get( + PREFIX, params={f"{field}_min": 0, f"{field}_max": 0, "neutralization": "INDUSTRY"} + ) + ).json() + assert [r["id"] for r in result["items"]] == ["zero"] + assert (await logged_in.get(PREFIX, params={f"{field}_min": 2, f"{field}_max": 1})).status_code == 422 + async with app.state.sessions.begin() as db: + await upsert_alpha(db, alpha("zero", settings={}, **{"is": {}})) + detail = (await logged_in.get(f"{PREFIX}/zero")).json() + assert all(detail[field] is None for field in fields) + assert detail["neutralization"] is None and detail["check_type"] == "PENDING" + malformed = snapshot_columns({}, {"pnl": "nan"}, [{**c, "value": True} for c in checks(0)]) + assert all(malformed[field] is None for field in fields) + + +async def test_ppac_tags_partial_edit_bulk_filter_and_sync_preservation(app, logged_in): + async with app.state.sessions.begin() as db: + for name in ("ppac", "other"): + await upsert_alpha(db, alpha(name, **{"is": {"checks": checks(1)}})) + assert ( + await logged_in.patch( + f"{PREFIX}/ppac/research", + json={ + "version": 1, + "note": "等活动轮到再提交", + "state": "candidate", + "favorite": True, + }, + ) + ).status_code == 200 + assert ( + await logged_in.patch( + f"{PREFIX}/ppac/research", + json={ + "version": 2, + "tags": [" PPAC ", "PPAC", "待活动提交"], + }, + ) + ).status_code == 200 + assert ( + await logged_in.patch(f"{PREFIX}/ppac/research", json={"version": 2, "tags": []}) + ).status_code == 409 + async with app.state.sessions.begin() as db: + await upsert_alpha(db, alpha("ppac", **{"is": {"checks": checks(2)}})) + result = (await logged_in.get(f"{PREFIX}?tag=PPAC&check_type=FAIL_2")).json() + assert result["total"] == 1 + research = result["items"][0]["research"] + assert ( + research["note"] == "等活动轮到再提交" and research["favorite"] and research["state"] == "candidate" + ) + assert research["tags"] == ["PPAC", "待活动提交"] and research["version"] == 3 + assert "PPAC" in (await logged_in.get(f"{PREFIX}/facets")).json()["tags"] + assert ( + await logged_in.patch( + f"{PREFIX}/research/bulk", + json={ + "alpha_ids": ["ppac", "other"], + "versions": {"ppac": 3, "other": 1}, + "add_tags": ["活动候选"], + "remove_tags": ["待活动提交"], + }, + ) + ).status_code == 200 + assert (await logged_in.get(f"{PREFIX}?tag=活动候选")).json()["total"] == 2 + assert (await logged_in.get(f"{PREFIX}?tag=待活动提交")).json()["total"] == 0 + + +def test_migration_backfills_multiple_batches_and_preserves_research(tmp_path, monkeypatch): + path = tmp_path / "migration.db" + monkeypatch.setenv("DATABASE_URL", f"sqlite+aiosqlite:///{path}") + monkeypatch.setenv("ADMIN_PASSWORD", "migration-test-only") + monkeypatch.setenv("ENCRYPTION_KEY", Fernet.generate_key().decode()) + monkeypatch.setenv("WQ_EMAIL", "") + monkeypatch.setenv("WQ_PASSWORD", "") + root = Path(__file__).resolve().parents[1] + config = Config(str(root / "alembic.ini")) + config.set_main_option("script_location", str(root / "migrations")) + command.upgrade(config, "0010") + engine = sa.create_engine(f"sqlite:///{path}") + metadata = sa.MetaData() + alphas = sa.Table("alphas", metadata, autoload_with=engine) + research = sa.Table("research", metadata, autoload_with=engine) + from app.models import now + + with engine.begin() as db: + db.execute( + alphas.insert(), + [ + { + "id": f"old{i:04}", + "hidden": False, + "settings": {"neutralization": "INDUSTRY"}, + "is_metrics": {"pnl": 0}, + "os_metrics": {}, + "checks": checks(i % 4), + "synced_at": now(), + "raw": {}, + } + for i in range(503) + ], + ) + db.execute( + research.insert(), + { + "alpha_id": "old0000", + "note": "keep", + "tags": ["PPAC"], + "favorite": True, + "state": "candidate", + "version": 7, + "updated_at": now(), + }, + ) + for _ in range(2): + command.upgrade(config, "head") + command.check(config) + alphas = sa.Table("alphas", sa.MetaData(), autoload_with=engine) + with engine.connect() as db: + rows = db.execute(sa.select(alphas).order_by(alphas.c.id)).mappings().all() + assert len(rows) == 503 + for i, row in enumerate(rows): + expected = snapshot_columns(row["settings"], row["is_metrics"], checks(i % 4)) + assert {key: row[key] for key in expected} == expected + record = db.execute(sa.select(research)).mappings().one() + assert record["tags"] == ["PPAC"] and record["note"] == "keep" and record["version"] == 7 + command.downgrade(config, "0010") + engine.dispose() diff --git a/frontend/src/components/AlphaDetail.tsx b/frontend/src/components/AlphaDetail.tsx index 1280b00..bc3b397 100644 --- a/frontend/src/components/AlphaDetail.tsx +++ b/frontend/src/components/AlphaDetail.tsx @@ -384,7 +384,7 @@ export function AlphaDetail({ />