signal_log: outcomes for every setup, event dedup, interned news; fix over-scan, dead outlook, panel OPPOSE bias

- seed an advisory outcome on every setup row; same-setup re-logs within 60 min
  are DUPLICATE rows (advisory_event_id); resolver rebuilds bar streams across gaps
- headlines/events interned into news_snapshots (DB 667 MB -> 262 MB); readers
  use signals_with_news / read_news and mode=ro (immutable=1 missed WAL rows)
- post-gate truth columns: gate_reason, actionable, cleaned_warnings, scan_kind,
  config_fingerprint; SELL-hour gates fail closed
- telegram: breach rescan reuses this bar's report; grade dropped from alert
  fingerprint (upgrade-only re-alert)
- market_outlook: hour-bucket dedup (old rule skipped alternate hours), skip heartbeats
- agent_panel: macro-anchored OPPOSE guard (opposed trades were +30R over 3 weeks)
- analyze_signal_log --stored-candles/--parity; backfill + news migration scripts
- tests: Module 25 (analyze_signal_log) + 27 (observability); 429 total

Claude-Session: https://claude.ai/code/session_01FC4s6VCURFte4dub4xKxYL
This commit is contained in:
Harwinder Sekhon
2026-09-03 20:47:33 -04:00
parent 83ffd290ca
commit b1e880be4f
13 changed files with 3120 additions and 121 deletions
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#!/usr/bin/env python3
"""
backfill_signal_outcomes.py — seed and advance advisory outcomes for every
logged trade setup (not only panel rows), one per advisory event.
Pass A (offline, no network): assign setup_key / advisory_event_id to all
legacy setup rows, mark same-setup re-logs within 60 min as DUPLICATE, and
seed a PENDING outcome on each canonical row that has none. Existing
(panel-seeded) outcomes are never overwritten.
Pass B: advance PENDING rows from the closed-candle streams already stored
in the DB (union across every snapshot of the timeframe — no provider).
Pass C (--reseed-unresolvable): bounded re-seed of continuity-broken rows,
then Pass B again.
Safe beside the live writers: short per-row transactions with a busy
timeout. Read-only preview with --dry-run.
python scripts/backfill_signal_outcomes.py --dry-run
python scripts/backfill_signal_outcomes.py
python scripts/backfill_signal_outcomes.py --reseed-unresolvable
"""
import argparse
import os
import sqlite3
import sys
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
import app_config # noqa: E402
from signal_log import SignalLogger # noqa: E402
def _status_counts(con: sqlite3.Connection) -> dict:
return dict(con.execute(
"SELECT COALESCE(advisory_outcome_status, 'NULL'), COUNT(*)"
" FROM signals WHERE setup_json IS NOT NULL AND setup_json != 'null'"
" GROUP BY 1").fetchall())
def main(argv=None) -> int:
ap = argparse.ArgumentParser(description=__doc__.splitlines()[1])
ap.add_argument("--db", default=None, help="defaults to signal_log.path")
ap.add_argument("--dry-run", action="store_true")
ap.add_argument("--reseed-unresolvable", action="store_true")
ap.add_argument("--symbol", default="XAU/USD")
args = ap.parse_args(argv)
path = args.db or app_config.signal_log_path()
if not os.path.exists(path):
print(f"no database at {path}")
return 1
if args.dry_run:
con = sqlite3.connect(f"file:{os.path.abspath(path)}?mode=ro", uri=True)
print("setup rows by outcome status:", _status_counts(con))
have = {r[1] for r in con.execute("PRAGMA table_info(signals)")}
if "setup_key" in have:
n_keyless = con.execute(
"SELECT COUNT(*) FROM signals WHERE setup_json IS NOT NULL"
" AND setup_json != 'null' AND setup_key IS NULL").fetchone()[0]
print(f"setup rows without setup_key: {n_keyless}")
else:
print("setup_key column not present yet (schema migrates on"
" the first non-dry run)")
con.close()
return 0
lg = SignalLogger(path)
try:
print("before:", _status_counts(lg._conn))
print("pass A (seed/dedup):", lg.backfill_seeds())
total = 0
for _ in range(50):
n = lg.resolve_from_store(args.symbol)
total += n
if n == 0:
break
print(f"pass B (advance from stored bars): {total} rows changed")
if args.reseed_unresolvable:
reseeded = lg.reseed_unresolvable()
print(f"pass C (re-seed): {len(reseeded)} rows re-seeded")
for _ in range(50):
if lg.resolve_from_store(args.symbol) == 0:
break
print("after:", _status_counts(lg._conn))
finally:
lg.close()
return 0
if __name__ == "__main__":
sys.exit(main())
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#!/usr/bin/env python3
"""
migrate_signal_log_news.py — move inline news blobs into news_snapshots.
Legacy rows store the full RSS headline list (~33 KB) and calendar events
(~1.2 KB) inline on EVERY scan row; the same blob repeats ~5× because the
news caches outlive a candle. This script interns each distinct blob once
(content hash), stamps `headlines_hash` / `events_hash` on the row and
NULLs the inline columns. Readers use the `signals_with_news` view or
`signal_log.read_news`.
Idempotent and resumable (batched transactions). Run --vacuum with BOTH
live writers (telegram bot, dashboard publisher) stopped — VACUUM needs
exclusive access and ~1× the final size of free disk.
python scripts/migrate_signal_log_news.py --dry-run
python scripts/migrate_signal_log_news.py
python scripts/migrate_signal_log_news.py --vacuum # bots stopped
"""
import argparse
import hashlib
import os
import sqlite3
import sys
from datetime import datetime, timezone
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
import app_config # noqa: E402
from signal_log import SignalLogger # noqa: E402
def _hash(text: str) -> str:
return hashlib.sha256(text.encode("utf-8")).hexdigest()
def migrate(con: sqlite3.Connection, batch: int = 500) -> dict:
"""Intern legacy inline blobs; returns counters. Caller owns the
connection (schema must already exist — open a SignalLogger once)."""
stats = {"rows": 0, "headlines_interned": 0, "events_interned": 0}
now = datetime.now(timezone.utc).isoformat()
while True:
rows = con.execute(
"SELECT id, headlines_json, events_json FROM signals"
" WHERE (headlines_json IS NOT NULL AND headlines_hash IS NULL)"
" OR (events_json IS NOT NULL AND events_hash IS NULL)"
" ORDER BY id LIMIT ?", (batch,)).fetchall()
if not rows:
break
con.execute("BEGIN IMMEDIATE")
try:
for rowid, headlines, events in rows:
sets, params = [], []
if headlines is not None:
h = _hash(headlines)
cur = con.execute(
"INSERT OR IGNORE INTO news_snapshots"
" (hash, kind, body, first_seen, last_seen)"
" VALUES (?, 'headlines', ?, ?, ?)",
(h, headlines, now, now))
stats["headlines_interned"] += cur.rowcount
sets += ["headlines_hash=?", "headlines_json=NULL"]
params.append(h)
if events is not None:
h = _hash(events)
cur = con.execute(
"INSERT OR IGNORE INTO news_snapshots"
" (hash, kind, body, first_seen, last_seen)"
" VALUES (?, 'events', ?, ?, ?)",
(h, events, now, now))
stats["events_interned"] += cur.rowcount
sets += ["events_hash=?", "events_json=NULL"]
params.append(h)
params.append(rowid)
con.execute(
f"UPDATE signals SET {', '.join(sets)} WHERE id=?",
params)
stats["rows"] += 1
con.commit()
except Exception:
con.rollback()
raise
return stats
def prune_orphans(con: sqlite3.Connection) -> int:
cur = con.execute(
"DELETE FROM news_snapshots WHERE hash NOT IN"
" (SELECT headlines_hash FROM signals WHERE headlines_hash IS NOT NULL"
" UNION SELECT events_hash FROM signals WHERE events_hash IS NOT NULL)")
con.commit()
return cur.rowcount
def prune_news_older_than(con: sqlite3.Connection, days: int) -> int:
"""Drop the news reference (not the row) from rows older than N days,
then delete snapshots nothing references any more."""
cur = con.execute(
"UPDATE signals SET headlines_hash=NULL, events_hash=NULL"
" WHERE logged_at < datetime('now', ?)", (f"-{int(days)} days",))
con.commit()
prune_orphans(con)
return cur.rowcount
def main(argv=None) -> int:
ap = argparse.ArgumentParser(description=__doc__.splitlines()[1])
ap.add_argument("--db", default=None)
ap.add_argument("--dry-run", action="store_true")
ap.add_argument("--batch", type=int, default=500)
ap.add_argument("--prune-news-older-than", type=int, default=None,
metavar="DAYS")
ap.add_argument("--prune-orphans", action="store_true")
ap.add_argument("--vacuum", action="store_true",
help="checkpoint + VACUUM (all writers must be stopped)")
ap.add_argument("--no-backup", action="store_true")
args = ap.parse_args(argv)
path = args.db or app_config.signal_log_path()
if not os.path.exists(path):
print(f"no database at {path}")
return 1
size0 = os.path.getsize(path)
if args.dry_run:
con = sqlite3.connect(f"file:{os.path.abspath(path)}?mode=ro", uri=True)
n = con.execute(
"SELECT COUNT(*) FROM signals WHERE headlines_json IS NOT NULL"
" OR events_json IS NOT NULL").fetchone()[0]
d = con.execute(
"SELECT COUNT(DISTINCT headlines_json) FROM signals"
" WHERE headlines_json IS NOT NULL").fetchone()[0]
print(f"{n} rows carry inline news blobs ({d} distinct headline "
f"blobs); file size {size0 / 1e6:.1f} MB")
con.close()
return 0
if not args.no_backup:
backup = f"{path}.pre-news-{datetime.now(timezone.utc):%Y%m%d}"
if not os.path.exists(backup):
src = sqlite3.connect(path)
dst = sqlite3.connect(backup)
src.backup(dst)
dst.close()
src.close()
print(f"backup written: {backup}")
lg = SignalLogger(path) # applies the additive schema
lg.close()
con = sqlite3.connect(path)
con.execute("PRAGMA busy_timeout=10000")
try:
print("migrate:", migrate(con, batch=args.batch))
if args.prune_news_older_than is not None:
print("rows de-referenced:",
prune_news_older_than(con, args.prune_news_older_than))
if args.prune_orphans:
print("orphan snapshots removed:", prune_orphans(con))
if args.vacuum:
try:
con.execute("PRAGMA wal_checkpoint(TRUNCATE)")
con.execute("VACUUM")
except sqlite3.OperationalError as exc:
print(f"VACUUM failed ({exc}) — stop the bot and dashboard "
"publisher first, then re-run with --vacuum")
return 2
finally:
con.close()
print(f"size {size0 / 1e6:.1f} MB -> {os.path.getsize(path) / 1e6:.1f} MB"
+ ("" if args.vacuum else " (run --vacuum to reclaim space)"))
return 0
if __name__ == "__main__":
sys.exit(main())