MidasBot: bot trading crypto IA + stratégies Ichimoku validées

- Infra: Freqtrade (futures dry-run) + Redis + dashboard + Docker Compose
- Couche IA: ai_analyzer (Claude via abonnement, MCP TradingView, backfill biais)
- Stratégies: SampleStrategy, AiBiasStrategy, IchimokuLS (long/short, validée
  train/test + données vierges + walk-forward), MTFIchimoku, variantes hyperopt
- Arbitrage CEX (dry-run), backtesting, walk-forward, volatility targeting
- IchimokuLS en dry-run live (config_live.json)

Claude-Session: https://claude.ai/code/session_01VHETcFacdnDhQzthLpdYFR

ai_analyzer/market_data.py

@@ -0,0 +1,92 @@
+"""Construction d'un instantané de marché compact à fournir à Claude.
+
+On reste volontairement léger : prix courant, variation, et quelques statistiques
+dérivées des dernières bougies (pas de dépendance lourde type talib). Claude raisonne
+sur ce résumé ; le MCP TradingView (optionnel) peut enrichir l'analyse côté Claude.
+"""
+from __future__ import annotations
+
+from dataclasses import dataclass, asdict
+from typing import Optional
+
+import ccxt
+
+
+@dataclass
+class PairSnapshot:
+    pair: str
+    timeframe: str
+    last_price: float
+    change_pct_window: float  # variation % sur la fenêtre observée
+    high_window: float
+    low_window: float
+    sma_fast: float
+    sma_slow: float
+    n_candles: int
+
+    def to_dict(self) -> dict:
+        return asdict(self)
+
+
+def _sma(values: list[float], period: int) -> Optional[float]:
+    if len(values) < period:
+        return None
+    return sum(values[-period:]) / period
+
+
+def snapshot_from_candles(
+    pair: str,
+    timeframe: str,
+    ohlcv: list,
+    fast: int = 9,
+    slow: int = 21,
+) -> Optional[PairSnapshot]:
+    """Calcule un résumé à partir d'une liste de bougies OHLCV (live OU historique)."""
+    if not ohlcv:
+        return None
+    closes = [c[4] for c in ohlcv]
+    highs = [c[2] for c in ohlcv]
+    lows = [c[3] for c in ohlcv]
+    last = closes[-1]
+    first = closes[0]
+    return PairSnapshot(
+        pair=pair,
+        timeframe=timeframe,
+        last_price=round(last, 6),
+        change_pct_window=round((last - first) / first * 100, 2) if first else 0.0,
+        high_window=round(max(highs), 6),
+        low_window=round(min(lows), 6),
+        sma_fast=round(_sma(closes, fast) or last, 6),
+        sma_slow=round(_sma(closes, slow) or last, 6),
+        n_candles=len(closes),
+    )
+
+
+def build_snapshot(
+    exchange_name: str,
+    pair: str,
+    timeframe: str = "1h",
+    limit: int = 100,
+    fast: int = 9,
+    slow: int = 21,
+) -> Optional[PairSnapshot]:
+    """Récupère les dernières bougies via ccxt et calcule un résumé."""
+    exchange_cls = getattr(ccxt, exchange_name)
+    exchange = exchange_cls({"enableRateLimit": True})
+    try:
+        ohlcv = exchange.fetch_ohlcv(pair, timeframe=timeframe, limit=limit)
+    except Exception as exc:  # noqa: BLE001 — on journalise et on ignore la paire
+        print(f"[market_data] échec fetch {pair}: {exc}")
+        return None
+    return snapshot_from_candles(pair, timeframe, ohlcv, fast=fast, slow=slow)
+
+
+def build_snapshots(
+    exchange_name: str, pairs: list[str], timeframe: str = "1h", limit: int = 100
+) -> list[PairSnapshot]:
+    out = []
+    for pair in pairs:
+        snap = build_snapshot(exchange_name, pair, timeframe=timeframe, limit=limit)
+        if snap:
+            out.append(snap)
+    return out