Commit Graph

6 Commits

Author SHA1 Message Date
Kunthawat Greethong
14b2aeff7c feat(scheduler): per-source cadence + source-health log with failure diagnosis + UI copy 2026-08-28 11:41:48 +07:00
Kunthawat Greethong
1fb1e1a027 feat(scheduler): auto-collect PIT factor + Siamchart vintages on each refresh (deploy-safe) 2026-08-28 11:26:33 +07:00
Kunthawat Greethong
03195dc55d [verified] Auto-refresh dated dividend ledger in the data scheduler
Automatically keep the real dated dividend ledger fresh inside the app's own
refresh loop (this app runs on its own server, independent of Hermes):

- backend/app/scheduler.py: AppDataScheduler gained a cooldown-gated
  _maybe_refresh_dated_dividends() that fetches real dated dividend history
  (siamchart /stock-info) into data/dividends/ledger.json at most once per
  dividend_cooldown_seconds (default 6h) — dividend history changes only a
  few times a year, so we never hammer the source every refresh tick. The
  fetch is non-fatal: a network failure leaves the previous ledger intact.
- backend/app/__init__.py: passes DIVIDEND_REFRESH_COOLDOWN_SECONDS to the
  scheduler (default 21600s).
- tests: cooldown fires once then skips, and refetches after it elapses (2)
  — full backend 294 passed.
2026-08-27 12:51:49 +07:00
Kunthawat Greethong
d87a1ada39 [verified] Cross-theme surprise normalization + historical factor store (P4 enabler)
A. Cross-theme comparability:
- compute_theme_surprises now weight-normalizes by total |weight| (weighted
  average), so every theme surprise on same [-1,1] scale regardless of factor
  count/weight (retail 0.189->0.145; auto_credit 1.0->0.64).

B. Historical factor store (enables learning macro/demographic factors):
- New factor_history.py: append-only per-factor JSONL, dedupes unchanged
  values, rejects non-finite, records every FACTORS value each scheduler run.
- scheduler.py: jobs carry fetch_module; refresh_all records factor history
  (non-fatal); added bank_npl job.
- GET /api/v1/learning/factors?min_points= reports n_points/learnable per
  factor so users see when P4 learning unlocks (validated query parsing).
- weight_learning: generic learn_factor_series() aggregator (momentum reuses).

Independent review deleg_5dd358e3 passed=true (empty security/logic arrays);
its two robustness suggestions applied (finite guard in record(), clean 400 on
bad min_points). 234 tests pass; Vite build passes.
2026-08-27 07:32:16 +07:00
Kunthawat Greethong
bfa9b08af6 [verified] Scheduler refreshes once on boot (no 1h wait for first pull) 2026-08-25 21:03:52 +07:00
Kunthawat Greethong
abc06af3a1 [verified] Add in-app automatic data scheduler (runs on its own server, no Hermes)
- scheduler.py: daemon thread inside Flask refreshes all real Thai collectors on interval (default 60min, REFRESH_INTERVAL_SECONDS) via shared daily cache + writes timestamped marker
- create_app starts scheduler (skipped in TESTING); shared daily_cache now an extension
- GET /api/v1/data/last-refresh: automation status + last refresh (every N hours)
- Live verified: refresh_all pulls 5/5 real sources (tourism/auto/NPL/energy/macro)
- 2 tests; full suite 197 OK
2026-08-25 21:00:13 +07:00