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Henrik Jess Nielsen
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runner.py
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235
runner.py
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"""
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runner.py — MoneyMaker pipeline orchestrator.
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Usage:
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python runner.py # full pipeline (fetch → analyze → evaluate → execute)
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python runner.py --dry-run # simulate everything, no real orders
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python runner.py --analyze-only # only fetch news + run NLP, no orders
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python runner.py --report # print P&L report only
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Pipeline flow (each run):
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1. Fetch Ground News + Danish RSS feeds
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2. Run NLP+Claude analysis on new articles
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3. Evaluate buy/sell signals vs open positions
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4. Execute orders on Saxo SIM (skip if --dry-run)
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5. Print status summary
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Scheduled by cron:
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06:00 CET --analyze-only (full NLP before market opens)
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09:30 CET (default) trade window 1
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12:00 CET (default) trade window 2
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14:30 CET (default) trade window 3
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16:30 CET (default) trade window 4
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19:00 CET --report daily P&L summary
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"""
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import sys
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import argparse
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import traceback
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from datetime import datetime, timezone
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from db import get_conn, DB_TYPE, init_schema
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from ground_news import fetch_all
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from rss_feeds import fetch_all_rss
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from analyze import analyze_articles
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from portfolio import evaluate_orders, get_db as portfolio_db, _open_positions
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from report import print_report
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def run_pipeline(dry_run: bool = False, analyze_only: bool = False) -> None:
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ts = datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M UTC")
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print(f"\n{'═'*60}")
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print(f" MONEYMAKER RUNNER · {ts}")
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print(f" Mode: {'DRY RUN' if dry_run else 'LIVE'} · DB: {DB_TYPE}")
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print(f"{'═'*60}\n")
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# ── 1. Ensure schema is up-to-date ──────────────────────────────────────
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try:
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init_schema()
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except Exception as e:
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print(f"[runner] WARNING: init_schema() failed: {e}")
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# ── 2. Fetch news ────────────────────────────────────────────────────────
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db = get_conn()
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try:
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print("[runner] Henter Ground News …")
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n_gn = fetch_all(db)
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print(f" +{n_gn} nye artikler fra Ground News")
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print("[runner] Henter danske RSS feeds …")
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n_rss = fetch_all_rss(db)
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print(f" +{n_rss} nye artikler fra RSS feeds")
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finally:
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db.close()
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# ── 3. NLP analysis ───────────────────────────────────────────────────────
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print("\n[runner] Kører NLP analyse …")
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analyze_articles(
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force=False,
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dry_run=dry_run,
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use_claude=True,
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auto_fetch=False, # already fetched above
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)
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if analyze_only:
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print("\n[runner] --analyze-only flag sat. Stopper efter NLP.")
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return
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# ── 4. Evaluate orders ────────────────────────────────────────────────────
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print("\n[runner] Evaluerer ordre-forslag …")
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pdb = portfolio_db()
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try:
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evaluate_orders(pdb)
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finally:
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pdb.close()
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# ── 5. Auto-execute (skip if dry-run) ────────────────────────────────────
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if not dry_run:
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_auto_execute()
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else:
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print("\n[runner] DRY RUN — ingen ordre placeret.")
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print("\n[runner] Pipeline færdig.\n")
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def _auto_execute() -> None:
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"""
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Auto-place orders on Saxo SIM based on portfolio recommendations.
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1. AUTO-SELL: close positions that have hit stop-loss or take-profit.
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2. AUTO-BUY: open new positions when signal + analyst consensus align.
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Orders are placed via saxo_broker.place_order() and logged to saxo_orders.
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Sells record signal_correct in position_events.
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"""
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from portfolio import (
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CAPITAL, MAX_POSITIONS, MIN_SIGNAL, BUY_ANALYST,
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_open_positions, _open_count, _best_signals, _per_position, _c25_map,
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cmd_sell,
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)
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from saxo_broker import place_order, find_uic
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import yfinance as yf
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pdb = portfolio_db()
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c25 = _c25_map()
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# ── 1. Auto-sell: stop-loss / take-profit ─────────────────────────────
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for pos in _open_positions(pdb):
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ticker = pos["ticker"]
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yf_ticker = c25.get(ticker, {}).get("ticker_yahoo", ticker + ".CO")
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try:
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price = yf.Ticker(yf_ticker).fast_info.get("lastPrice")
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except Exception as e:
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print(f" SKIP SELL {ticker} — kurs fejl: {e}")
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continue
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if not price:
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continue
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stop_hit = price <= pos["stop_loss"]
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take_hit = price >= pos["take_profit"]
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if stop_hit or take_hit:
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reason = "stop-loss" if stop_hit else "take-profit"
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print(f" → SÆLGER {pos['shares']:.0f} stk {ticker} à {price:.2f} kr ({reason})")
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try:
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resp = place_order(
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ticker, pos["shares"], "Sell",
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price_dkk=price,
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note=f"runner auto-sell {reason}",
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)
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print(f" Saxo svar: {resp}")
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except Exception as e:
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print(f" FEJL ved Saxo ordre: {e}")
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# Record sell in portfolio DB (sets signal_correct)
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cmd_sell(pdb, [ticker, str(price)])
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# ── 2. Auto-buy: new positions ────────────────────────────────────────
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signals = _best_signals(pdb)
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open_pos = {p["ticker"]: p for p in _open_positions(pdb)}
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for sig in signals:
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ticker = sig["ticker"]
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score = sig["signal_score"] or 0
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momentum = sig["momentum_dir"] or "unknown"
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# Only buy if score is strong + not already in position
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if score < MIN_SIGNAL:
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continue
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if ticker in open_pos:
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continue
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if len(open_pos) >= MAX_POSITIONS:
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break
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# Check analyst recommendation
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try:
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from signals import analyst_rec
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rec = analyst_rec(ticker)
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rec_label_lower = rec["label"].lower().replace("🟢", "").strip()
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if rec_label_lower not in BUY_ANALYST:
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print(f" SKIP {ticker} — analyst={rec['label']}")
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continue
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except Exception as e:
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print(f" SKIP {ticker} — analyst check failed: {e}")
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continue
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# Get current price via yfinance
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try:
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yf_ticker = c25.get(ticker, {}).get("ticker_yahoo", ticker + ".CO")
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price = yf.Ticker(yf_ticker).fast_info.get("lastPrice")
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if not price:
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print(f" SKIP {ticker} — ingen kurs fra yfinance")
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continue
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except Exception as e:
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print(f" SKIP {ticker} — kurs fejl: {e}")
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continue
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per_pos = _per_position(pdb)
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if per_pos < 500:
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print(f" SKIP {ticker} — for lidt kapital: {per_pos} DKK")
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continue
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shares = int(per_pos // price)
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if shares < 1:
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print(f" SKIP {ticker} — 0 aktier til {price:.2f} DKK/stk")
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continue
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print(f" → KØBER {shares} stk {ticker} à ~{price:.2f} DKK (sig={score:.3f})")
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try:
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resp = place_order(
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ticker, shares, "Buy",
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price_dkk=price,
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signal_score=score,
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analyst_rec=rec["label"],
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note=f"runner auto-buy sig={score:.3f} mom={momentum}",
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)
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print(f" Saxo svar: {resp}")
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except Exception as e:
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print(f" FEJL ved ordre: {e}")
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open_pos[ticker] = {"ticker": ticker} # prevent double-buy in same run
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pdb.close()
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def main():
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parser = argparse.ArgumentParser(description="MoneyMaker pipeline runner")
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parser.add_argument("--dry-run", action="store_true", help="Simulate, no real orders")
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parser.add_argument("--analyze-only", action="store_true", help="Only fetch + NLP, no orders")
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parser.add_argument("--report", action="store_true", help="Print P&L report and exit")
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args = parser.parse_args()
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if args.report:
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print_report()
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return
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try:
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run_pipeline(dry_run=args.dry_run, analyze_only=args.analyze_only)
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except KeyboardInterrupt:
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print("\n[runner] Afbrudt.")
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except Exception:
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print("[runner] FEJL:")
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traceback.print_exc()
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sys.exit(1)
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if __name__ == "__main__":
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main()
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