Initial commit: Oil Trading Bot (MT5, WTI)

Headless FastAPI-Backend (server.py + core/engine.py) mit Mobile-PWA (web/),
Strategie-/Backtest-Suite und Doku. Secrets, DB, Logs und Laufzeit-State sind
via .gitignore ausgeschlossen; Config-Vorlage: oil_widget_config.ini.example.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
This commit is contained in:
Axel Hocks
2026-07-24 08:29:23 +02:00
co-authored by Claude Opus 4.8
commit 75d28827e8
104 changed files with 21059 additions and 0 deletions
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"""
core/analysis/ict.py — ICT / SMC Konzepte
BOS, FVG, Asia Levels, Liquidity Sweep, Order Block, Ichimoku
"""
from __future__ import annotations
def calc_bos(highs: list, lows: list, closes: list,
lookback: int = 30, pivot_win: int = 3) -> dict:
"""
Break of Structure (ICT/SMC).
Rückgabe: {'bos': 'bullish'|'bearish'|None, 'bos_level': float|None, 'bars_ago': int|None}
"""
n = len(closes)
if n < lookback + pivot_win + 3:
return {"bos": None, "bos_level": None, "bars_ago": None}
w = pivot_win
search_end = n - 1
last_swing_high = last_swing_low = None
for i in range(search_end - w - 1, max(w, search_end - lookback - 1), -1):
lo = max(0, i - w); hi_r = min(n - 1, i + w)
if last_swing_high is None and highs[i] == max(highs[lo : hi_r + 1]):
last_swing_high = highs[i]
if last_swing_low is None and lows[i] == min(lows[lo : hi_r + 1]):
last_swing_low = lows[i]
if last_swing_high is not None and last_swing_low is not None:
break
if last_swing_high is None or last_swing_low is None:
return {"bos": None, "bos_level": None, "bars_ago": None}
for ago in range(1, 6):
if n - ago - 1 < 1:
break
c_now = closes[n - ago]
c_prev = closes[n - ago - 1]
if c_now < last_swing_low <= c_prev:
return {"bos": "bearish", "bos_level": last_swing_low, "bars_ago": ago}
if c_now > last_swing_high >= c_prev:
return {"bos": "bullish", "bos_level": last_swing_high, "bars_ago": ago}
return {"bos": None, "bos_level": None, "bars_ago": None}
def calc_fvg(highs: list, lows: list, closes: list, lookback: int = 20) -> dict:
"""
Fair Value Gap / Imbalance (ICT-Definition).
Rückgabe: {'type': 'bullish'|'bearish'|None, 'top', 'bottom', 'mid', 'filled_pct', 'bars_ago'}
"""
n = len(closes)
if n < 4:
return {"type": None}
cur = closes[-1]
for i in range(n - 3, max(1, n - lookback - 2), -1):
if i + 2 >= n:
continue
h_before = highs[i - 1]; l_before = lows[i - 1]
h_after = highs[i + 1]; l_after = lows[i + 1]
if h_before < l_after:
bottom, top = h_before, l_after
if top <= bottom:
continue
filled_pct = max(0.0, min(100.0, (cur - bottom) / (top - bottom) * 100))
if filled_pct < 100.0:
return {"type": "bullish", "top": top, "bottom": bottom,
"mid": (top + bottom) / 2,
"filled_pct": round(filled_pct, 0), "bars_ago": n - 2 - i}
elif l_before > h_after:
bottom, top = h_after, l_before
if top <= bottom:
continue
filled_pct = max(0.0, min(100.0, (top - cur) / (top - bottom) * 100))
if filled_pct < 100.0:
return {"type": "bearish", "top": top, "bottom": bottom,
"mid": (top + bottom) / 2,
"filled_pct": round(filled_pct, 0), "bars_ago": n - 2 - i}
return {"type": None}
def calc_asia_levels(bars: list) -> dict | None:
"""
Asien-Session Hoch/Tief (00:0008:00 UTC) aus M15-Bars.
Rückgabe: {'high': float, 'low': float, 'n': int} oder None.
"""
if not bars:
return None
import time as _time
from datetime import datetime, timezone as _tz
now_ts = _time.time()
today_utc = datetime.fromtimestamp(now_ts, tz=_tz.utc).replace(
hour=0, minute=0, second=0, microsecond=0)
today_ts = today_utc.timestamp()
asia_end_ts = today_ts + 8 * 3600
asia_bars = [b for b in bars
if today_ts <= int(b["time"]) < asia_end_ts]
if not asia_bars:
return None
return {
"high": max(float(b["high"]) for b in asia_bars),
"low": min(float(b["low"]) for b in asia_bars),
"n": len(asia_bars),
}
def calc_liquidity_sweep(highs: list, lows: list, closes: list, opens: list,
lookback: int = 25, pivot_win: int = 3) -> dict:
"""
Liquidity Sweep (ICT): Wick über Swing-High/-Low, Schluss zurück.
Rückgabe: {'sweep': 'bearish'|'bullish'|None, 'level': float|None, 'bars_ago': int|None}
"""
n = len(closes)
if n < lookback + pivot_win + 3:
return {"sweep": None, "level": None, "bars_ago": None}
w = pivot_win
search_end = n - 1
swing_highs = []
swing_lows = []
for i in range(max(w, search_end - lookback), search_end - w):
lo = max(0, i - w); hi_r = min(n - 1, i + w)
if highs[i] == max(highs[lo : hi_r + 1]):
swing_highs.append(highs[i])
if lows[i] == min(lows[lo : hi_r + 1]):
swing_lows.append(lows[i])
if not swing_highs or not swing_lows:
return {"sweep": None, "level": None, "bars_ago": None}
pivot_high = max(swing_highs)
pivot_low = min(swing_lows)
for ago in range(1, 4):
idx = n - ago - 1
if idx < 1:
break
h = highs[idx]; l = lows[idx]; c = closes[idx]
if h > pivot_high and c < pivot_high:
return {"sweep": "bearish", "level": pivot_high, "bars_ago": ago}
if l < pivot_low and c > pivot_low:
return {"sweep": "bullish", "level": pivot_low, "bars_ago": ago}
return {"sweep": None, "level": None, "bars_ago": None}
def calc_order_block(highs: list, lows: list, closes: list, opens: list,
lookback: int = 40, min_impulse_bars: int = 3,
atr: float | None = None) -> dict:
"""
Order Block (ICT/SMC).
Bullish OB: letzter Bear-Candle vor starkem Aufwärts-Impuls → Support-Zone
Bearish OB: letzter Bull-Candle vor starkem Abwärts-Impuls → Resistance-Zone
Rückgabe: {'type': 'bullish'|'bearish'|None, 'high', 'low', 'mid', 'bars_ago', 'mitigated'}
"""
n = len(closes)
if n < lookback + min_impulse_bars + 2:
return {"type": None}
atr_eff = atr if atr and atr > 0 else 0.5
min_move = 1.5 * atr_eff
for end in range(n - min_impulse_bars - 1, max(1, n - lookback - 1), -1):
if end + min_impulse_bars >= n:
continue
bull_move = closes[end + min_impulse_bars] - closes[end]
bear_move = closes[end] - closes[end + min_impulse_bars]
if bull_move > min_move:
for ob_i in range(end, max(0, end - 6), -1):
if closes[ob_i] < opens[ob_i]:
ob_h = highs[ob_i]; ob_l = lows[ob_i]
mit = any(lows[j] < ob_h and highs[j] > ob_l
for j in range(ob_i + 1, n))
return {"type": "bullish", "high": ob_h, "low": ob_l,
"mid": (ob_h + ob_l) / 2,
"bars_ago": n - 1 - ob_i, "mitigated": mit}
elif bear_move > min_move:
for ob_i in range(end, max(0, end - 6), -1):
if closes[ob_i] > opens[ob_i]:
ob_h = highs[ob_i]; ob_l = lows[ob_i]
mit = any(highs[j] > ob_l and lows[j] < ob_h
for j in range(ob_i + 1, n))
return {"type": "bearish", "high": ob_h, "low": ob_l,
"mid": (ob_h + ob_l) / 2,
"bars_ago": n - 1 - ob_i, "mitigated": mit}
return {"type": None}
def calc_coc(highs: list, lows: list, closes: list,
lookback: int = 50, pivot_win: int = 3) -> dict:
"""
Change of Character (CoC / CHOCH) — ICT/SMC Trendumkehrsignal.
Algorithmus:
1. Finde das jüngste Swing-High UND das jüngste Swing-Low im Lookback.
2. Welches Extrem ist jünger bestimmt den vorherigen Bias:
• SH jünger → Uptrend → suche das letzte Swing-Low VOR dem SH (= Higher Low)
Wenn Close unter dieses HL bricht → bearischer CoC
• SL jünger → Downtrend → suche das letzte Swing-High VOR dem SL (= Lower High)
Wenn Close über dieses LH bricht → bullischer CoC
Unterschied zu BOS:
BOS = Strukturbruch IN Trendrichtung (Fortsetzung)
CoC = Strukturbruch GEGEN den Trend (Umkehrsignal, stärker)
Rückgabe:
coc: 'bearish' | 'bullish' | None
coc_level: gebrochenes Strukturniveau (Higher Low / Lower High)
swing_extreme: letztes Swing-Extrem (SH/SL = der Pivot der den Trend definierte)
bars_ago: Bars seit dem Bruch
"""
n = len(closes)
if n < pivot_win * 2 + 12:
return {"coc": None, "coc_level": None, "swing_extreme": None, "bars_ago": None}
w = pivot_win
lb = min(lookback, n - w - 2)
def _find_pivot(seq_high: bool, start: int, stop: int) -> tuple[int, float] | None:
for i in range(start, max(w, stop), -1):
lo = max(0, i - w); hi_r = min(n - 1, i + w)
if seq_high and highs[i] == max(highs[lo:hi_r + 1]):
return (i, highs[i])
if not seq_high and lows[i] == min(lows[lo:hi_r + 1]):
return (i, lows[i])
return None
# ── Jüngstes Swing-High und Swing-Low im Lookback ────────────────────────
recent_sh = _find_pivot(True, n - 1 - w, n - lb - 1)
recent_sl = _find_pivot(False, n - 1 - w, n - lb - 1)
if recent_sh is None or recent_sl is None:
return {"coc": None, "coc_level": None, "swing_extreme": None, "bars_ago": None}
sh_idx, sh_price = recent_sh
sl_idx, sl_price = recent_sl
lb_stop = max(w, n - lb - 1) # ältestes Bar das in Lookback fällt
# ── Bearish CoC: letztes Extrem war ein Swing-High ────────────────────────
if sh_idx > sl_idx:
# Suche den Swing-Low VOR dem SH (= der Higher Low im Uptrend)
# Suchbereich: komplett rückwärts bis Ende des Lookback-Fensters
hl = _find_pivot(False, sh_idx - w - 1, lb_stop)
if hl is None:
return {"coc": None, "coc_level": None, "swing_extreme": None, "bars_ago": None}
hl_price = hl[1]
for ago in range(1, 10):
if n - ago - 1 < 1:
break
c_now = closes[n - ago]
c_prev = closes[n - ago - 1]
if c_now < hl_price <= c_prev:
return {"coc": "bearish", "coc_level": round(hl_price, 5),
"swing_extreme": round(sh_price, 5), "bars_ago": ago}
# ── Bullish CoC: letztes Extrem war ein Swing-Low ─────────────────────────
elif sl_idx > sh_idx:
# Suche den Swing-High VOR dem SL (= der Lower High im Downtrend)
lh = _find_pivot(True, sl_idx - w - 1, lb_stop)
if lh is None:
return {"coc": None, "coc_level": None, "swing_extreme": None, "bars_ago": None}
lh_price = lh[1]
for ago in range(1, 10):
if n - ago - 1 < 1:
break
c_now = closes[n - ago]
c_prev = closes[n - ago - 1]
if c_now > lh_price >= c_prev:
return {"coc": "bullish", "coc_level": round(lh_price, 5),
"swing_extreme": round(sl_price, 5), "bars_ago": ago}
return {"coc": None, "coc_level": None, "swing_extreme": None, "bars_ago": None}
def calc_ichimoku(highs: list, lows: list, closes: list,
tenkan: int = 9, kijun: int = 26, senkou_b: int = 52) -> dict | None:
"""
Ichimoku Kinko Hyo — Wolken-Analyse (Standard 9/26/52).
ichi_bias: 4=strong_bull, 3=bull, 2=neutral, 1=bear, 0=strong_bear
"""
n = len(closes)
if n < senkou_b + kijun + 1:
return None
def midpoint(h_sl, l_sl):
return (max(h_sl) + min(l_sl)) / 2
tenkan_val = midpoint(highs[-tenkan:], lows[-tenkan:])
kijun_val = midpoint(highs[-kijun:], lows[-kijun:])
off = kijun
if n - off - 1 < senkou_b:
return None
idx = n - off - 1
t_ago = midpoint(highs[idx - tenkan + 1: idx + 1], lows[idx - tenkan + 1: idx + 1])
k_ago = midpoint(highs[idx - kijun + 1: idx + 1], lows[idx - kijun + 1: idx + 1])
a_val = (t_ago + k_ago) / 2
b_val = midpoint(highs[idx - senkou_b + 1: idx + 1], lows[idx - senkou_b + 1: idx + 1])
cloud_top = max(a_val, b_val)
cloud_bot = min(a_val, b_val)
cur = closes[-1]
price_vs_cloud = ("above" if cur > cloud_top else
"below" if cur < cloud_bot else "inside")
tk_signal = "bullish" if tenkan_val >= kijun_val else "bearish"
cloud_color = "green" if a_val >= b_val else "red"
chikou_signal = "neutral"
if n > kijun:
ref = closes[n - 1 - kijun]
chikou_signal = "bullish" if cur > ref else ("bearish" if cur < ref else "neutral")
bull_pts = (
(1 if price_vs_cloud == "above" else 0) +
(1 if tk_signal == "bullish" else 0) +
(1 if chikou_signal == "bullish" else 0) +
(1 if cloud_color == "green" else 0)
)
ichi_bias = {4: "strong_bull", 3: "bull", 1: "bear", 0: "strong_bear"}.get(bull_pts, "neutral")
return {
"tenkan": round(tenkan_val, 3),
"kijun": round(kijun_val, 3),
"senkou_a": round(a_val, 3),
"senkou_b": round(b_val, 3),
"cloud_top": round(cloud_top, 3),
"cloud_bot": round(cloud_bot, 3),
"cloud_color": cloud_color,
"price_vs_cloud": price_vs_cloud,
"tk_signal": tk_signal,
"chikou_signal": chikou_signal,
"ichi_bias": ichi_bias,
"bull_pts": bull_pts,
}