""" label_charts.py -- [2026-10-01] The user: "do that (mark the best entry/exit on each chart) for the 22 days stocks and the sip stocks first". set "22d" : every stock-day on the 8/27-9/30 lists (labels from day_labels.jsonl) + the trade bot's own buys/sells on its live days set "sip" : every stock-day the sip_bot traded (/var/www/screener/premarket, READ ONLY), labeled the same way (label_days.label) + the sip_bot's buys/sells Charts: reports/playbook/labels_22d/ and labels_sip/ ; sip labels also appended to data/playbook/sip_day_labels.jsonl. """ import gzip import json import sys import time from collections import defaultdict from datetime import datetime from pathlib import Path from zoneinfo import ZoneInfo import matplotlib matplotlib.use("Agg") import matplotlib.dates as md import matplotlib.pyplot as plt HERE = Path(__file__).resolve().parent TRADE = Path("/var/www/screener/trade") sys.path.insert(0, str(TRADE)) sys.path.insert(0, str(HERE)) import reference as REF import label_days as LD import analyze_trades as A from alpaca_client import get_client ET = ZoneInfo("America/New_York") STOP_AT = (9, 10) def bot_trades(source): out = defaultdict(list) if source == "sip": for p in sorted(A.SIP.glob("*_trades.jsonl")): for t in A.load_trades(p.name[:10], "sip"): out[(p.name[:10], t["symbol"])].append(t) else: for p in sorted((TRADE / "data" / "trades").glob("*_trades.jsonl")): for l in open(p): t = json.loads(l) if t.get("exit_price") is not None: out[(p.name[:10], t["symbol"])].append(t) return out def draw(lab, B, trades, path, who): ts = [x["t"].replace(tzinfo=None) for x in B] fig, (ax, axv) = plt.subplots(2, 1, figsize=(10.5, 5.2), gridspec_kw={"height_ratios": [3, 1]}, sharex=True) ax.plot(ts, [x["c"] for x in B], color="#1f3a5f", lw=1) ax.plot(ts, [x["vwap"] for x in B], color="#c0392b", lw=1.1) ax.axhline(B[0]["o"], color="grey", ls=":", lw=.8) lo = min(x["l"] for x in B); hi = max(x["h"] for x in B); pad = (hi - lo) * .14 ax.set_ylim(lo - pad, hi + pad) for key, col in (("best_held", "#16a085"), ("leg2", "#2980b9")): mk = lab.get(key) if not mk: continue bi = next(x for x in B if x["m"] == mk["entry_m"]) bj = next(x for x in B if x["m"] == mk["exit_m"]) ax.scatter([bi["t"].replace(tzinfo=None)], [bi["c"]], marker="*", s=170, color=col, edgecolor="black", zorder=6) ax.scatter([bj["t"].replace(tzinfo=None)], [bj["c"]], marker="*", s=170, color="#8e44ad", edgecolor="black", zorder=6) ax.annotate(f"best buy {bi['c']:.2f}", (bi["t"].replace(tzinfo=None), bi["c"]), xytext=(6, -14), textcoords="offset points", fontsize=7, color=col, fontweight="bold") ax.annotate(f"best sell {bj['c']:.2f} (+{mk['gain_pct']:.1f}%)", (bj["t"].replace(tzinfo=None), bj["c"]), xytext=(6, 7), textcoords="offset points", fontsize=7, color="#8e44ad", fontweight="bold") pl = 0.0 for t in trades: ein, eout = A.et(t["entry_time"]).replace(tzinfo=None), A.et(t["exit_time"]).replace(tzinfo=None) ax.scatter([ein], [t["entry_price"]], marker="o", s=70, color="#27ae60", edgecolor="black", zorder=7) ax.scatter([eout], [t["exit_price"]], marker="o", s=70, color="#e74c3c", edgecolor="black", zorder=7) pl += t.get("pl_dollars") or 0 bh = lab.get("best_held") ax.set_title(f"{lab['symbol']} {lab['date']} open->close {lab['open_to_close_pct']:+.1f}% | " + ("NO GOOD TRADE" if lab["no_trade"] else f"best holdable +{bh['gain_pct']:.1f}%: " + ", ".join(bh['entry']['tags']) + " -> " + ", ".join(bh['exit']['tags'])) + (f" | {who}: {len(trades)} trade(s) {pl:+.2f}$" if trades else ""), fontsize=8) ax.grid(alpha=.3) axv.bar(ts, [x["v"] for x in B], width=1 / 1440, color=["#8e44ad" if x["volx"] >= 10 else "#1f3a5f" for x in B]) axv.xaxis.set_major_formatter(md.DateFormatter("%H:%M")) axv.grid(alpha=.3) plt.tight_layout() plt.savefig(path, dpi=95) plt.close() def too_late(): t = datetime.now(ET) return (t.hour, t.minute) >= STOP_AT def run_22d(): out = HERE / "labels_22d" out.mkdir(exist_ok=True) labs = {(l["date"], l["symbol"]): l for l in map(json.loads, open(LD.OUT)) if l["date"] >= "2026-08-27"} trades = bot_trades("trade") n = 0 for p in sorted(LD.BARS.glob("bars_2026-*.json.gz")): d = json.load(gzip.open(p, "rt")) if d["date"] < "2026-08-27": continue for s in d["top30_current"]: lab = labs.get((d["date"], s)) ref = REF.load(d["date"], s) if not lab or not ref: continue B = LD.build(d["symbols"][s]["bars"], ref) draw(lab, B, trades.get((d["date"], s), []), out / f"{d['date']}_{s}.png", "trade bot") n += 1 REF._CACHE.clear() if too_late(): print("stopped 9:10"); break print(f"22d charts: {n}", flush=True) def run_sip(): out = HERE / "labels_sip" out.mkdir(exist_ok=True) trades = bot_trades("sip") client = get_client() labs, n = [], 0 for (day, s), tr in sorted(trades.items()): if too_late(): print("stopped 9:10"); break ref = REF.load(day, s) if not ref: continue d = datetime.fromisoformat(day).replace(tzinfo=ET) try: raw = client.get_minute_bars(s, start=d.replace(hour=9, minute=30), end=d.replace(hour=16), limit=1000) except Exception as e: print(day, s, e); continue rows = [[int(b.timestamp.timestamp()), float(b.open), float(b.high), float(b.low), float(b.close), float(b.volume)] for b in raw] B = LD.build(rows, ref) if len(B) < 100: continue lab = LD.label(day, s, B) lab["source"] = "sip_bot" lab["bot_pl"] = round(sum(t["pl_dollars"] for t in tr), 2) labs.append(lab) draw(lab, B, tr, out / f"{day}_{s}.png", "sip_bot") n += 1 with open(TRADE / "data" / "playbook" / "sip_day_labels.jsonl", "w") as f: for l in labs: f.write(json.dumps(l, default=str) + "\n") print(f"sip charts: {n} of {len(trades)} traded stock-days", flush=True) if __name__ == "__main__": t0 = time.time() if "sip" in sys.argv: run_sip() if "22d" in sys.argv: run_22d() print(f"done in {time.time() - t0:.0f}s")