fix: restore stage-based Alpha check classification
This commit is contained in:
@@ -9,3 +9,9 @@ Status: ready-for-agent
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## 完成记录
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已实现并完成本地验证:后端 471 项全量测试通过;最终调整后 23 项专项测试通过;Ruff 与 git diff --check 通过;前端构建通过;Alpha 管理和工作空间 3 项浏览器回归通过。迁移 0018 在隔离 SQLite 中验证 503 条记录的升级、降级、再升级和原始证据保留。尚未部署或对业务数据库执行迁移;Docker 后端部署启动时按既有流程执行 alembic upgrade head。
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## Comments
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用户后续确认恢复旧项目阶段语义:同步非空有效检查无 FAIL 为 PRE_CHECK,主动 /check 完成无 FAIL 为 PASS,PENDING/WARNING 不算失败;异常、空结果保留待定。同步刷新采用新的同步快照重新分类,不沿用旧检查阶段。MCP/HTTP 使用数据库派生状态;迁移 0019 使用晚于 synced_at 的已保存 checked 检查点识别历史主动检查,其余归同步阶段。保留 0018 历史迁移和所有原始 checks。
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阶段逻辑调整已完成:后端 499 项测试通过,含同步→主动检查→再同步、MCP PENDING/WARNING 返回和 503 条历史记录迁移;Ruff、git diff --check、前端构建通过。预检通过使用蓝色 Tag。未部署,未迁移实际业务数据库。
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+11
-9
@@ -7,7 +7,7 @@ from datetime import datetime
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from sqlalchemy import or_, select, update
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from .models import Alpha, Research, ResearchTag, SelfCorrelation, now
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from .platform_checks import split_checks, submission_limits
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from .platform_checks import check_result, split_checks, submission_limits
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from .research.provenance import source_alpha_ids
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METRIC_FIELDS = (
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@@ -20,16 +20,17 @@ def failed_checks(checks):
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"""Return failed Alpha check names, excluding submission limits and local correlation."""
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return [
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check.get("name") if isinstance(check.get("name"), str) else "未命名检查"
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for check in split_checks(checks)[0] if isinstance(check, dict) and check.get("result") == "FAIL"
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for check in split_checks(checks)[0] if isinstance(check, dict) and check_result(check) == "FAIL"
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] if isinstance(checks, list) else []
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def snapshot_columns(settings, metrics, checks):
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def snapshot_columns(settings, metrics, checks, *, checked=False):
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"""Derive list fields from a platform snapshot, preserving missing metrics as null.
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Submission limits are excluded. Only explicit Alpha FAIL results count.
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Empty, malformed and unfinished Alpha checks are
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pending; all known checks passing without PROD_CORRELATION is only a pre-check.
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Sync snapshots with no failures are PRE_CHECK; a completed explicit /check
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with no failures is PASS. WARNING/PENDING do not count as failures, matching
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the legacy workflow. Empty, malformed or unknown results remain PENDING.
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No submission eligibility or activity eligibility is inferred here.
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"""
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settings = settings if isinstance(settings, dict) else {}
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@@ -40,10 +41,10 @@ def snapshot_columns(settings, metrics, checks):
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by_name = {check["name"]: check for check in valid if isinstance(check.get("name"), str)}
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if failures:
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check_type = "FAIL_1" if failures == 1 else "FAIL_2"
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elif not checks or len(valid) != len(checks) or any(check.get("result") != "PASS" for check in valid):
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elif not checks or len(valid) != len(checks) or any(check_result(check) not in ("PASS", "WARNING", "PENDING") for check in valid):
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check_type = "PENDING"
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else:
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check_type = "PASS" if "PROD_CORRELATION" in by_name else "PRE_CHECK"
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check_type = "PASS" if checked else "PRE_CHECK"
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# /check values are freshest; submitted snapshots also expose a scalar in IS.
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prod_correlation = number(by_name.get("PROD_CORRELATION", {}).get("value"))
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if prod_correlation is None:
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@@ -66,12 +67,13 @@ def snapshot_columns(settings, metrics, checks):
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}
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def check_summary(checks):
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def check_summary(checks, *, check_type):
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"""Separate cached Alpha findings from submission limits; infer no live eligibility."""
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return {
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"check_type": snapshot_columns({}, {}, checks)["check_type"],
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"check_type": check_type,
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"failed_checks": failed_checks(checks),
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"submission_limits": submission_limits(checks),
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"meaning": "PRE_CHECK 为同步无失败项;PASS 为主动检查完成且无失败项。PENDING/WARNING 不算失败,不代表全部检查项 PASS 或当前可提交",
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}
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@@ -1,6 +1,12 @@
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"""Classify platform evidence without discarding unknown checks or inferring eligibility."""
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def check_result(check):
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"""Normalize known upstream result casing without rewriting the raw evidence."""
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value = check.get("result") if isinstance(check, dict) else None
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return value.upper() if isinstance(value, str) else None
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def is_submission_limit(check):
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"""Recognize only the confirmed account-limit check; unknown names remain Alpha checks."""
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return isinstance(check, dict) and check.get("name") == "REGULAR_SUBMISSION"
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@@ -16,8 +22,8 @@ def split_checks(checks):
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def submission_limits(checks):
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"""Summarize the observed limit, never the account's current allowance or reset time."""
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_, limits = split_checks(checks)
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status = "blocked" if any(c.get("result") == "FAIL" for c in limits) else (
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"not_blocked" if limits and all(c.get("result") == "PASS" for c in limits) else "unknown"
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status = "blocked" if any(check_result(c) == "FAIL" for c in limits) else (
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"not_blocked" if limits and all(check_result(c) == "PASS" for c in limits) else "unknown"
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)
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return {"status": status, "checks": limits,
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"meaning": "仅反映缓存观测时的提交限制,不代表当前额度或正式提交资格"}
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@@ -222,7 +222,7 @@ class ResearchAccess:
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return {"alpha_id": args.alpha_id, "snapshot": submission_fingerprint(context),
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**context, "descriptions": {key: item["description"] for key, item in context["sections"].items()},
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"can_check": alpha.status == "UNSUBMITTED" and await correlation_allows_check(self.db, args.alpha_id),
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"checks": alpha.checks, "check_summary": check_summary(alpha.checks), "source": "local_cache", "production_submission": False,
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"checks": alpha.checks, "check_summary": check_summary(alpha.checks, check_type=alpha.check_type), "source": "local_cache", "production_submission": False,
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"job_id": job.id if job else None, "job_status": job.status if job else None,
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"checked_at": job.checkpoint.get("checked_at") if job else None}
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@@ -207,7 +207,7 @@ def router(runner, ai):
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return {
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"snapshot": fingerprint(context),
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"checks": alpha.checks,
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"check_summary": check_summary(alpha.checks),
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"check_summary": check_summary(alpha.checks, check_type=alpha.check_type),
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"sections": context["sections"],
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"descriptions": {key: item["description"] for key, item in context["sections"].items()},
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"model": config.description_model,
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@@ -355,7 +355,7 @@ async def run_check(runner, job_id, payload):
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alpha.checks = sanitize(checks)
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alpha.is_metrics = {**alpha.is_metrics, "checks": alpha.checks}
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alpha.raw = {**alpha.raw, "is": {**(alpha.raw.get("is") or {}), "checks": alpha.checks}}
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for key, value in snapshot_columns(alpha.settings, alpha.is_metrics, alpha.checks).items():
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for key, value in snapshot_columns(alpha.settings, alpha.is_metrics, alpha.checks, checked=True).items():
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setattr(alpha, key, value)
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db.add(JobItem(job_id=job_id, alpha_id=alpha_id))
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job.processed = 1
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@@ -0,0 +1,91 @@
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"""Restore stage-based check classification, preserving raw platform snapshots."""
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from datetime import datetime, timezone
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import sqlalchemy as sa
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from alembic import op
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revision = "0019"
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down_revision = "0018"
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branch_labels = None
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depends_on = None
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def timestamp(value):
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"""Read historical timestamps; missing or invalid evidence cannot prove a /check."""
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try:
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value = datetime.fromisoformat(value) if isinstance(value, str) else value
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return value.replace(tzinfo=timezone.utc) if value.tzinfo is None else value
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except (ValueError, TypeError, AttributeError):
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return None
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def classify(checks, checked, legacy):
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"""Frozen migration rules; legacy means the pre-0019 correlation-presence rule."""
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checks = checks if isinstance(checks, list) else []
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checks = [c for c in checks if not (isinstance(c, dict) and c.get("name") == "REGULAR_SUBMISSION")]
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valid = [c for c in checks if isinstance(c, dict)]
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results = [c.get("result") for c in valid]
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if not legacy:
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results = [v.upper() if isinstance(v, str) else None for v in results]
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failures = sum(v == "FAIL" for v in results)
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if failures:
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return "FAIL_1" if failures == 1 else "FAIL_2"
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allowed = ("PASS",) if legacy else ("PASS", "PENDING", "WARNING")
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if not checks or len(valid) != len(checks) or any(v not in allowed for v in results):
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return "PENDING"
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passed = any(c.get("name") == "PROD_CORRELATION" for c in valid) if legacy else checked
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return "PASS" if passed else "PRE_CHECK"
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def reclassify(legacy=False):
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"""Recompute in batches; only a check checkpoint newer than the sync proves its stage.
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A prior PASS is not evidence because the old rule inferred it from a check name.
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A subsequent sync replaces the snapshot and is classified as pre-check again.
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"""
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alphas = sa.table("alphas", sa.column("id", sa.String()), sa.column("checks", sa.JSON()),
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sa.column("synced_at", sa.DateTime(timezone=True)), sa.column("check_type", sa.String()))
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jobs = sa.table("sync_jobs", sa.column("kind", sa.String()), sa.column("payload", sa.JSON()),
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sa.column("checkpoint", sa.JSON()))
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connection = op.get_bind()
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last_id = None
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while True:
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query = sa.select(alphas.c.id, alphas.c.checks, alphas.c.synced_at).order_by(alphas.c.id).limit(500)
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if last_id is not None:
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query = query.where(alphas.c.id > last_id)
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rows = connection.execute(query).mappings().all()
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if not rows:
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break
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checked_at = {}
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if not legacy:
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observations = connection.execute(sa.select(jobs.c.checkpoint).where(
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jobs.c.kind == "submission_check",
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jobs.c.payload["alpha_ids"][0].as_string().in_([r["id"] for r in rows]),
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)).scalars()
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for checkpoint in observations:
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if not isinstance(checkpoint, dict) or checkpoint.get("phase") != "checked":
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continue
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alpha_id = checkpoint.get("alpha_id")
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observed = timestamp(checkpoint.get("checked_at"))
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if isinstance(alpha_id, str) and observed and (
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alpha_id not in checked_at or observed > checked_at[alpha_id]
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):
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checked_at[alpha_id] = observed
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updates = []
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for row in rows:
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synced = timestamp(row["synced_at"])
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observed = checked_at.get(row["id"])
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updates.append({"snapshot_id": row["id"], "classification": classify(
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row["checks"], bool(synced and observed and observed > synced), legacy)})
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connection.execute(alphas.update().where(alphas.c.id == sa.bindparam("snapshot_id"))
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.values(check_type=sa.bindparam("classification")), updates)
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last_id = rows[-1]["id"]
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def upgrade():
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reclassify()
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def downgrade():
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reclassify(legacy=True)
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@@ -37,10 +37,10 @@ def checks(failures):
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(None, "PENDING"),
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([None], "PENDING"),
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([{}], "PENDING"),
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([{"name": "LOW_SHARPE", "result": "WARNING"}], "PENDING"),
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([{"name": "LOW_SHARPE", "result": "WARNING"}], "PRE_CHECK"),
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([{"name": "LOW_SHARPE", "result": "PASS"}], "PRE_CHECK"),
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([{"name": "PROD_CORRELATION", "result": "PENDING"}], "PENDING"),
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(checks(0), "PASS"),
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([{"name": "PROD_CORRELATION", "result": "PENDING"}], "PRE_CHECK"),
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(checks(0), "PRE_CHECK"),
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(checks(1), "FAIL_1"),
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(checks(2), "FAIL_2"),
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(checks(3), "FAIL_2"),
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@@ -58,7 +58,7 @@ async def test_checks_filter_before_pagination_and_share_export_scope(app, logge
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for check_type, expected in [
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("FAIL_1", ["failed1"]),
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("FAIL_2", ["failed2", "failed3"]),
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("PASS", ["failed0"]),
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("PRE_CHECK", ["failed0"]),
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("PENDING", ["unknown"]),
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]:
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response = await logged_in.get(
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@@ -218,7 +218,7 @@ def test_migration_backfills_multiple_batches_and_preserves_research(tmp_path, m
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rows = db.execute(sa.select(alphas).order_by(alphas.c.id)).mappings().all()
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assert len(rows) == 503
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for i, row in enumerate(rows):
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expected = snapshot_columns(row["settings"], row["is_metrics"], checks(i % 4))
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expected = snapshot_columns(row["settings"], row["is_metrics"], checks(i % 4), checked=True)
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assert {key: row[key] for key in expected} == expected
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record = db.execute(sa.select(research)).mappings().one()
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assert record["tags"] == ["PPAC"] and record["note"] == "keep" and record["version"] == 7
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@@ -0,0 +1,64 @@
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"""Historical stage recovery requires a persisted /check newer than the latest sync."""
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from datetime import datetime, timezone
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from pathlib import Path
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import sqlalchemy as sa
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from alembic import command
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from alembic.config import Config
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from cryptography.fernet import Fernet
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def test_stage_backfill_preserves_evidence_and_uses_checkpoints(tmp_path, monkeypatch):
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path = tmp_path / "stages.db"
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monkeypatch.setenv("DATABASE_URL", f"sqlite+aiosqlite:///{path}")
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monkeypatch.setenv("ADMIN_PASSWORD", "migration-test-only")
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monkeypatch.setenv("ENCRYPTION_KEY", Fernet.generate_key().decode())
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monkeypatch.setenv("WQ_EMAIL", "")
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monkeypatch.setenv("WQ_PASSWORD", "")
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root = Path(__file__).resolve().parents[1]
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config = Config(str(root / "alembic.ini"))
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config.set_main_option("script_location", str(root / "migrations"))
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command.upgrade(config, "0018")
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engine = sa.create_engine(f"sqlite:///{path}")
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alphas = sa.Table("alphas", sa.MetaData(), autoload_with=engine)
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jobs = sa.Table("sync_jobs", sa.MetaData(), autoload_with=engine)
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synced = datetime(2026, 9, 12, 0, tzinfo=timezone.utc)
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pending = [{"name": "PROD_CORRELATION", "result": "PENDING"},
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{"name": "REGULAR_SUBMISSION", "result": "FAIL"}]
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passed = [{"name": "PROD_CORRELATION", "result": "PASS"}]
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patterns = [
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(pending, "PENDING", "PRE_CHECK", None),
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(pending, "PENDING", "PASS", {"phase": "checked", "checked_at": "2026-09-12T01:00:00+00:00"}),
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(pending, "PENDING", "PRE_CHECK", {"phase": "checked", "checked_at": "2026-09-11T23:00:00+00:00"}),
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(pending, "PENDING", "PRE_CHECK", {"phase": "check"}),
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(passed, "PASS", "PRE_CHECK", None),
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([{"name": "LOW_SHARPE", "result": "FAIL"}], "FAIL_1", "FAIL_1", None),
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([{}], "PENDING", "PENDING", {"phase": "checked", "checked_at": "2026-09-12T01:00:00Z"}),
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]
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with engine.begin() as db:
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db.execute(alphas.insert(), [
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{"id": f"stage{i:04}", "hidden": False, "settings": {}, "os_metrics": {},
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"is_metrics": {"checks": patterns[i % 7][0]}, "checks": patterns[i % 7][0],
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"check_type": patterns[i % 7][1], "synced_at": synced,
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"raw": {"is": {"checks": patterns[i % 7][0]}}}
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for i in range(503)
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])
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db.execute(jobs.insert(), [
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{"id": f"job{i}", "kind": "submission_check", "status": "completed",
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"payload": {"alpha_ids": [f"stage{i:04}"]},
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"checkpoint": {**patterns[i % 7][3], "alpha_id": f"stage{i:04}"},
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"processed": 1, "failed": 0, "total": 1, "cancel_requested": False,
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"created_at": synced, "updated_at": synced}
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for i in range(503) if patterns[i % 7][3]
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])
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for target, expected_index in [("0019", 2), ("0018", 1), ("0019", 2)]:
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(command.upgrade if target == "0019" else command.downgrade)(config, target)
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with engine.connect() as db:
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rows = db.execute(sa.select(alphas).order_by(alphas.c.id)).mappings().all()
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assert len(rows) == 503
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for i, row in enumerate(rows):
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assert row["check_type"] == patterns[i % 7][expected_index]
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assert row["checks"] == row["raw"]["is"]["checks"] == row["is_metrics"]["checks"] == patterns[i % 7][0]
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command.check(config)
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engine.dispose()
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@@ -0,0 +1,56 @@
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"""The same checks have different meanings at sync and explicit /check stages."""
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import pytest
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from app.alphas import snapshot_columns
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@pytest.mark.parametrize("checks", [
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[{"name": "LOW_SHARPE", "result": "PASS"}],
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[{"name": "PROD_CORRELATION", "result": "PASS"}],
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[{"name": "PROD_CORRELATION", "result": "PENDING"}],
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[{"name": "MATCHES_THEMES", "result": "WARNING"}],
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])
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def test_stage_not_correlation_presence_decides_pass(checks):
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assert snapshot_columns({}, {}, checks)["check_type"] == "PRE_CHECK"
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assert snapshot_columns({}, {}, checks, checked=True)["check_type"] == "PASS"
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@pytest.mark.parametrize("checked", [False, True])
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@pytest.mark.parametrize("checks,expected", [
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([], "PENDING"),
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([None], "PENDING"),
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([{}], "PENDING"),
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([{"name": "UNKNOWN", "result": "OTHER"}], "PENDING"),
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([{"name": "REGULAR_SUBMISSION", "result": "FAIL"}], "PENDING"),
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([{"name": "LOW_SHARPE", "result": "fail"}, {"name": "REGULAR_SUBMISSION", "result": "FAIL"}], "FAIL_1"),
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([{"name": "LOW_SHARPE", "result": "FAIL"}, {"name": "LOW_FITNESS", "result": "Fail"}], "FAIL_2"),
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])
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||||
def test_stage_preserves_failures_and_missing_evidence(checked, checks, expected):
|
||||
assert snapshot_columns({}, {}, checks, checked=checked)["check_type"] == expected
|
||||
|
||||
|
||||
async def test_sync_check_and_resync_use_distinct_stages(app, logged_in, monkeypatch):
|
||||
from app.alphas import upsert_alpha
|
||||
from tests import test_submission
|
||||
from tests.conftest import alpha
|
||||
|
||||
checks = [{"name": "LOW_SHARPE", "result": "PASS"},
|
||||
{"name": "PROD_CORRELATION", "result": "PENDING"},
|
||||
{"name": "MATCHES_THEMES", "result": "WARNING"},
|
||||
{"name": "REGULAR_SUBMISSION", "result": "FAIL"}]
|
||||
monkeypatch.setattr(test_submission, "CHECKS", checks)
|
||||
await test_submission.setup(app, alpha(**{"is": {"checks": checks}}))
|
||||
endpoint = "/api/v1/alphas/alpha1/submission"
|
||||
assert (await logged_in.get(endpoint)).json()["check_summary"]["check_type"] == "PRE_CHECK"
|
||||
response = await test_submission.enqueue(logged_in)
|
||||
assert response.status_code == 202
|
||||
await app.state.runner.execute(response.json()["id"])
|
||||
state = (await logged_in.get(endpoint)).json()
|
||||
assert state["job"]["status"] == "completed"
|
||||
assert state["check_summary"]["check_type"] == "PASS"
|
||||
assert state["check_summary"]["submission_limits"]["status"] == "blocked"
|
||||
assert (await logged_in.get("/api/v1/alphas/alpha1")).json()["check_type"] == "PASS"
|
||||
async with app.state.sessions.begin() as db:
|
||||
await upsert_alpha(db, alpha(**{"is": {"checks": checks}}))
|
||||
assert (await logged_in.get(endpoint)).json()["check_summary"]["check_type"] == "PRE_CHECK"
|
||||
@@ -11,7 +11,7 @@ from tests.test_submission import FIELDS, Description, setup
|
||||
|
||||
|
||||
@pytest.mark.parametrize("kind", ["REGULAR", "SUPER"])
|
||||
@pytest.mark.parametrize("result", ["PASS", "FAIL"])
|
||||
@pytest.mark.parametrize("result", ["PASS", "FAIL", "PENDING", "WARNING"])
|
||||
@pytest.mark.parametrize("limited", [False, True])
|
||||
async def test_mcp_check_never_submits(mcp_app, kind, result, limited, monkeypatch):
|
||||
from tests import test_submission
|
||||
@@ -38,7 +38,7 @@ async def test_mcp_check_never_submits(mcp_app, kind, result, limited, monkeypat
|
||||
assert job["status"] == "completed", job
|
||||
data = await invoke(mcp_app, principal, "get_submission_check", {"alpha_id": "alpha1"})
|
||||
assert data["checks"] == checks and data["checked_at"]
|
||||
assert data["check_summary"]["check_type"] == ("PASS" if result == "PASS" else "FAIL_1")
|
||||
assert data["check_summary"]["check_type"] == ("FAIL_1" if result == "FAIL" else "PASS")
|
||||
assert data["check_summary"]["submission_limits"]["status"] == ("blocked" if limited else "unknown")
|
||||
assert data["production_submission"] is False
|
||||
assert platform.patches == [{s: {"description": args["descriptions"][s]} for s in sections}]
|
||||
|
||||
@@ -47,5 +47,6 @@ def test_limit_migration_is_reversible_and_preserves_snapshots(tmp_path, monkeyp
|
||||
for i, row in enumerate(rows):
|
||||
assert row["check_type"] == patterns[i % 5][position]
|
||||
assert row["checks"] == row["is_metrics"]["checks"] == row["raw"]["is"]["checks"] == patterns[i % 5][0]
|
||||
command.upgrade(config, "head")
|
||||
command.check(config)
|
||||
engine.dispose()
|
||||
|
||||
@@ -8,13 +8,13 @@ LIMIT = {"name": "REGULAR_SUBMISSION", "result": "FAIL", "value": 4, "limit": 4}
|
||||
|
||||
|
||||
@pytest.mark.parametrize("checks,expected", [
|
||||
([{"name": "PROD_CORRELATION", "result": "PASS"}], "PASS"),
|
||||
([{"name": "PROD_CORRELATION", "result": "PASS"}], "PRE_CHECK"),
|
||||
([{"name": "LOW_SHARPE", "result": "PASS"}], "PRE_CHECK"),
|
||||
([{"name": "LOW_SHARPE", "result": "FAIL"}], "FAIL_1"),
|
||||
([], "PENDING"),
|
||||
([None], "PENDING"),
|
||||
([{"name": "UNKNOWN_CHECK", "result": "FAIL"}], "FAIL_1"),
|
||||
([{"name": "PROD_CORRELATION", "result": "PENDING"}], "PENDING"),
|
||||
([{"name": "PROD_CORRELATION", "result": "PENDING"}], "PRE_CHECK"),
|
||||
])
|
||||
def test_limit_does_not_change_alpha_verdict(checks, expected):
|
||||
original = [*checks, LIMIT]
|
||||
@@ -28,7 +28,7 @@ def test_all_limit_states_are_separate(result):
|
||||
from app.alphas import check_summary
|
||||
|
||||
checks = [{"name": "PROD_CORRELATION", "result": "PASS"}, {**LIMIT, "result": result}]
|
||||
summary = check_summary(checks)
|
||||
summary = check_summary(checks, check_type="PASS")
|
||||
assert summary["check_type"] == "PASS"
|
||||
assert summary["submission_limits"]["status"] == ("not_blocked" if result == "PASS" else "unknown")
|
||||
|
||||
|
||||
@@ -523,7 +523,9 @@ export function AlphaPage({
|
||||
? "red"
|
||||
: row!.check_type === "PASS"
|
||||
? "green"
|
||||
: "grey"
|
||||
: row!.check_type === "PRE_CHECK"
|
||||
? "blue"
|
||||
: "grey"
|
||||
}
|
||||
>
|
||||
{checkLabels[row!.check_type] || "待检查"}
|
||||
|
||||
Reference in New Issue
Block a user