fix: guarantee shadow scan freshness, long-only, user-scoped setup list

Second review round on the shadow book; all three findings were real.

- Scan freshness is now proven, not assumed. Pipeline steps run and fail
  independently, so a disabled or failed scan step still let the shadow
  step run on the newest *stored* setups -- a prior session's picks at
  stale prices. scan_all_tickers now records a run boundary
  (last_scan_run_started_at / _completed_at) only on successful
  completion; the shadow book refuses to trade unless COMPLETED is fresh
  and selects only setups with detected_at >= the run start. Deduplication
  to the latest row per ticker now happens BEFORE qualification, so a newer
  unqualified row suppresses an older qualified one rather than the reverse.

- Shadow selection is hard long-only. setup_qualifies only enforces
  long-only when min_momentum_percentile > 0, but 0 is a legal admin
  setting, and the cash accounting assumes long positions -- so the
  constraint is enforced in shadow selection regardless of gate config.

- The personal setup list excludes only the caller's own open positions.
  get_trade_setups gained exclude_open_trade_user_id; the trades route
  passes the authenticated user, while the Telegram broadcast stays global
  since it has no single owner.

New tests cover stale/absent scan markers, prior-run exclusion, newer
unqualified suppressing older qualified, long-only under a disabled gate,
and both sides of the user-scoped exclusion.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
This commit is contained in:
2026-07-21 09:31:24 +02:00
co-authored by Claude Fable 5
parent 247a92a89f
commit 6a10c8ff09
5 changed files with 230 additions and 40 deletions
+2 -1
View File
@@ -25,7 +25,7 @@ async def list_trade_setups(
None,
description="Filter by action: LONG_HIGH, LONG_MODERATE, SHORT_HIGH, SHORT_MODERATE, NEUTRAL",
),
_user=Depends(require_access),
user=Depends(require_access),
db: AsyncSession = Depends(get_db),
) -> APIEnvelope:
"""Get latest trade setups with recommendation data."""
@@ -36,6 +36,7 @@ async def list_trade_setups(
recommended_action=recommended_action,
live_recommendation=True,
exclude_open_trade_tickers=True,
exclude_open_trade_user_id=user.id,
exclude_reentry_gate_locked_tickers=True,
)
+31 -1
View File
@@ -30,6 +30,7 @@ from app.services.indicator_service import _extract_ohlcv, compute_atr
from app.services.price_service import query_ohlcv
from app.services.qualification import setup_qualifies
from app.services.sr_service import detect_gate_target_ladder
from app.services import settings_store
from app.services.trade_policy import (
MANUAL_BOOK,
SHADOW_BOOK,
@@ -46,6 +47,13 @@ from app.services.recommendation_service import (
logger = logging.getLogger(__name__)
# Boundary of the most recent *successful* scan. Written only when
# scan_all_tickers completes, so a consumer can tell a scan actually ran this
# pipeline pass (freshness of COMPLETED) and which setups belong to it
# (detected_at >= STARTED). The shadow book relies on both.
KEY_LAST_SCAN_STARTED = "last_scan_run_started_at"
KEY_LAST_SCAN_COMPLETED = "last_scan_run_completed_at"
STRATEGY_VERSION = "residual_highvol_80_20_atr_trail3_v1"
# A setup counts as live only while the daily scan keeps re-emitting it. The
@@ -812,6 +820,19 @@ async def scan_all_tickers(
if progress_callback is not None and total:
progress_callback(total, total, "")
# Record the run boundary only now that the scan has completed. The shadow
# book refuses to trade unless COMPLETED is fresh (proving a scan ran in this
# pipeline pass, not a prior session) and selects only setups from this run
# (detected_at >= STARTED). Written after the loop so a hard failure above
# leaves the previous, now-stale, marker in place.
await settings_store.upsert_setting(
db, KEY_LAST_SCAN_STARTED, gate_observation_started_at.isoformat()
)
await settings_store.upsert_setting(
db, KEY_LAST_SCAN_COMPLETED, datetime.now(timezone.utc).isoformat()
)
await db.commit()
return all_setups
@@ -823,6 +844,7 @@ async def get_trade_setups(
symbol: str | None = None,
live_recommendation: bool = False,
exclude_open_trade_tickers: bool = False,
exclude_open_trade_user_id: int | None = None,
exclude_reentry_gate_locked_tickers: bool = False,
include_reentry_gate_lock: bool = False,
) -> list[dict]:
@@ -855,11 +877,19 @@ async def get_trade_setups(
# construction, so letting its positions hide setups would leave the
# discretionary list picking over leftovers — and would bias the very
# shadow-vs-manual comparison the shadow book exists to measure.
open_trade_result = await db.execute(
open_trade_stmt = (
select(PaperTrade.ticker_id)
.where(PaperTrade.status == "open", PaperTrade.book == MANUAL_BOOK)
.distinct()
)
# Scope to one user for the personal setup list (don't hide a name just
# because someone else holds it); leave it global for the Telegram
# broadcast, which has no single owner.
if exclude_open_trade_user_id is not None:
open_trade_stmt = open_trade_stmt.where(
PaperTrade.user_id == exclude_open_trade_user_id
)
open_trade_result = await db.execute(open_trade_stmt)
excluded_ticker_ids.update(
ticker_id for ticker_id, in open_trade_result.all()
)
+64 -21
View File
@@ -53,8 +53,11 @@ DEFAULT_START_EQUITY = 100_000.0
# equity — a leveraged trade the validated strategy would never have taken.
NOTIONAL_CAP = 0.20
# Setups older than this mean the scan did not run in this pipeline pass.
MAX_SETUP_AGE = timedelta(hours=6)
# If the last successful scan completed longer ago than this, no scan ran in the
# current pipeline pass (scans are daily, ~24h apart), so there is nothing fresh
# to trade. Comfortably longer than a scan's own duration, far shorter than the
# gap between scans.
MAX_SCAN_AGE = timedelta(hours=6)
async def get_config(db: AsyncSession) -> dict:
@@ -166,37 +169,77 @@ async def _shadow_user_id(db: AsyncSession) -> int | None:
return int(row[0]) if row else None
async def _last_scan_start(db: AsyncSession, *, now: datetime) -> datetime | None:
"""Start of the last successful scan, if it ran in this pipeline pass.
Returns None — meaning "no scan to act on" — unless the scanner's COMPLETED
marker is fresh. Pipeline steps fail independently, so a scan that was
disabled, errored, or produced nothing leaves a stale marker; trading on the
newest stored setups then would enter a previous session's picks at stale
prices. Freshness is proven by the marker, not by setup age.
"""
from app.services import rr_scanner_service as rr
started = _parse_dt(await settings_store.get_value(db, rr.KEY_LAST_SCAN_STARTED))
completed = _parse_dt(
await settings_store.get_value(db, rr.KEY_LAST_SCAN_COMPLETED)
)
if started is None or completed is None:
return None
if now - completed > MAX_SCAN_AGE:
return None
return started
def _parse_dt(raw: str | None) -> datetime | None:
if not raw:
return None
try:
return datetime.fromisoformat(raw)
except ValueError:
return None
async def _todays_qualified_setups(
db: AsyncSession, config: dict, *, now: datetime
) -> list[TradeSetup]:
"""Latest qualified setup per ticker from the scan that just ran.
"""Long-only qualified setups from the scan that just ran, best rank first.
Freshness is a hard requirement, not a nicety: pipeline steps are allowed to
fail independently, so if the scan is disabled or errors, the newest stored
setups belong to a previous session. Trading those would enter yesterday's
picks at yesterday's prices and quietly corrupt the record. Anything older
than ``MAX_SETUP_AGE`` is treated as "no scan happened".
Order matters here, and matches the review's requirement:
Ordered by ``strategy_rank`` descending — the ordering the backtest selects
on. Setups without a rank sort last; they cannot be compared to ranked ones.
1. Take only rows from the current run (``detected_at >= scan start``). The
previous run's setups sit ~24h earlier and are excluded, so a stale row
can never be traded even if it once qualified.
2. Keep long only. The validated strategy is long-only, but the gate permits
shorts when ``min_momentum_percentile`` is 0 (a legal admin setting), and
the cash accounting assumes longs — so this is enforced here, not left to
the gate.
3. Deduplicate to the latest row per ticker *before* qualifying, so a newer
unqualified row correctly suppresses an older qualified one rather than
the reverse.
4. Qualify, then rank by ``strategy_rank`` (unranked sort last).
"""
cutoff = now - MAX_SETUP_AGE
result = await db.execute(
select(TradeSetup).where(TradeSetup.detected_at >= cutoff)
)
qualified = [s for s in result.scalars() if setup_qualifies(s, config)]
run_start = await _last_scan_start(db, now=now)
if run_start is None:
return []
result = await db.execute(
select(TradeSetup).where(TradeSetup.detected_at >= run_start)
)
rows = [s for s in result.scalars() if (s.direction or "long") == "long"]
# One setup per ticker — the most recent wins. A ticker can have several
# rows in a scan (e.g. both directions); ranking over duplicates would let
# one name occupy more than its share of the ordering.
latest: dict[int, TradeSetup] = {}
for setup in qualified:
for setup in rows:
held = latest.get(setup.ticker_id)
if held is None or setup.detected_at > held.detected_at:
if held is None or (setup.detected_at, setup.id) > (
held.detected_at,
held.id,
):
latest[setup.ticker_id] = setup
qualified = [s for s in latest.values() if setup_qualifies(s, config)]
return sorted(
latest.values(),
qualified,
key=lambda s: (
s.strategy_rank if s.strategy_rank is not None else float("-inf")
),