feat: causal lab

backend/services/market_event_detector.py

@@ -3,7 +3,7 @@ Isolated cycle action: Check New Market Events.
 
 Scans 4 sources and creates market_events for significant findings:
   - news     : geopolitical/macro news (RSS feeds, rule-scored)
-  - eco      : FRED economic releases with high surprise z-score
+  - eco      : ff_calendar releases with high surprise % (toutes devises, USD inclus)
   - technical: configurable signal catalog driven by Technical Desk
   - reports  : institutional reports (COT, EIA) with high importance
 
@@ -347,7 +347,7 @@ def _check_ff_calendar_surprises(
 ) -> List[Dict]:
     """
     Detect surprising releases in ff_calendar for the given currencies.
-    Used when currencies other than USD are configured (FRED only covers USD).
+    Détecte les releases surprenantes dans ff_calendar pour toutes les devises données (USD inclus).
     """
     from services.database import get_conn
 
@@ -483,129 +483,20 @@ def _check_eco(desk_cfg: Dict[str, Any]) -> List[Dict[str, Any]]:
     existing = _existing_event_keys()
     created: List[Dict] = []
 
-    # ── Local economic_events table (replaces FRED API call) ─────────────────
+    # ── ff_calendar — source unique pour toutes les devises (USD inclus) ──────
-    if "USD" in currencies:
+    # Anciennement : USD → economic_events (FRED), autres → ff_calendar.
-        try:
+    # Désormais ff_calendar couvre toutes les devises avec forecast + actual,
-            conn = get_conn()
+    # donc on unifie sur une seule source cohérente.
-            rows = conn.execute(
+    created += _check_ff_calendar_surprises(
-                """SELECT * FROM economic_events
+        currencies=currencies,
-                   WHERE event_date >= ? AND event_date <= ?
+        min_impact=min_impact,
-                     AND ABS(COALESCE(surprise_zscore, 0)) >= ?
+        date_from=date_from,
-                   ORDER BY event_date DESC, ABS(COALESCE(surprise_zscore, 0)) DESC
+        date_to=date_to,
-                   LIMIT 50""",
+        min_surprise_pct=ff_surprise_min,
-                (date_from, date_to, z_threshold),
+        lookback_releases=lookback_releases,
-            ).fetchall()
+        create_evt=create_evt,
-            conn.close()
+        existing=existing,
-            releases = []
+    )
-            for r in rows:
-                d = dict(r)
-                try:
-                    d["assets_impacted"] = json.loads(d.get("assets_impacted") or "[]")
-                except Exception:
-                    d["assets_impacted"] = []
-                releases.append(d)
-        except Exception as e:
-            logger.warning(f"[check_events/eco] local query failed: {e}")
-            releases = []
-
-        for rel in releases:
-            s_id   = rel.get("series_id", "")
-            impact = _SERIES_IMPACT.get(s_id, "low")
-            if _IMPACT_RANKS.get(impact, 1) < min_rank:
-                continue
-
-            z            = abs(rel.get("surprise_zscore") or 0)
-            s_pct        = rel.get("surprise_pct") or 0
-            ev_date      = (rel.get("event_date") or "")[:10]
-            ev_name_base = rel.get("event_name", s_id)
-            direction    = rel.get("surprise_direction", "neutral")
-
-            sign    = "+" if s_pct >= 0 else ""
-            ev_name = f"{ev_name_base} — Surprise {sign}{s_pct:.1f}% ({ev_date[:7]})"
-
-            if _is_dup(ev_name, existing):
-                continue
-
-            # Lookback context from FRED history
-            context_str = ""
-            if lookback_releases > 0 and s_id:
-                try:
-                    conn = get_conn()
-                    hist = conn.execute(
-                        """SELECT event_date, actual_value, forecast_value
-                           FROM economic_events
-                           WHERE series_id = ? AND event_date < ?
-                           ORDER BY event_date DESC LIMIT ?""",
-                        (s_id, ev_date, lookback_releases),
-                    ).fetchall()
-                    conn.close()
-                    if hist:
-                        context_str = " Historique récent: " + ", ".join(
-                            f"{r[0][:7]}: réel={r[1]} consensus={r[2]}" for r in hist
-                        )
-                except Exception:
-                    pass
-
-            sub_type = SUBTYPE_FROM_SERIES.get(s_id, s_id[:10]) if s_id else ev_name_base[:10]
-            level    = "long" if z >= 3 else ("medium" if z >= 2 else "short")
-            assets   = rel.get("assets_impacted") or []
-            if isinstance(assets, str):
-                try:
-                    assets = json.loads(assets)
-                except Exception:
-                    assets = []
-
-            source_ref = {
-                "title":          f"FRED release: {ev_name_base} ({ev_date})",
-                "source":         "FRED",
-                "url":            f"https://fred.stlouisfed.org/series/{s_id}" if s_id else "",
-                "date":           ev_date,
-                "original_score": round(min(0.95, 0.35 + z * 0.15), 3),
-            }
-
-            ev = {
-                "name":            ev_name,
-                "start_date":      ev_date,
-                "level":           level,
-                "category":        "event_calendar",
-                "sub_type":        sub_type,
-                "description":     (
-                    f"Surprise {direction} {sign}{s_pct:.1f}% vs baseline "
-                    f"(z-score: {z:.1f}σ). "
-                    f"Réel: {rel.get('actual_value', '?')} {rel.get('actual_unit', '')} "
-                    f"/ Prévision: {rel.get('forecast_value', '?')}."
-                    + context_str
-                ),
-                "market_impact":   "",
-                "affected_assets": assets,
-                "impact_score":    min(0.95, 0.35 + z * 0.15),
-                "actual_value":    str(rel.get("actual_value", "")),
-                "expected_value":  str(rel.get("forecast_value", "")),
-                "surprise_pct":    float(s_pct),
-                "source_refs":     [source_ref],
-                "origin":          "detector_eco",
-            }
-            if create_evt:
-                result = _save_and_evaluate(ev, existing)
-                if result:
-                    result["source"] = "eco"
-                    created.append(result)
-            else:
-                logger.info(f"[check_events/eco] create_market_event=False — skipping: {ev_name}")
-
-    # ── ff_calendar path (non-USD currencies) ────────────────────────────────
-    non_usd = [c for c in currencies if c != "USD"]
-    if non_usd:
-        created += _check_ff_calendar_surprises(
-            currencies=non_usd,
-            min_impact=min_impact,
-            date_from=date_from,
-            date_to=date_to,
-            min_surprise_pct=ff_surprise_min,
-            lookback_releases=lookback_releases,
-            create_evt=create_evt,
-            existing=existing,
-        )
 
     return created