quad_resolutions.csv

#!/usr/bin/env python3
"""quad_resolve.py - resolve paper BUY_YES signals against real market outcomes.

Reads the append-only ledger (mode=paper, action=BUY_YES_15M_UP), fetches each
market from gamma-api, and writes quad_resolutions.csv with win/loss + ROI per
signal. This is what the OOS evaluation needs (ledger alone never resolves).

Math (standard Polymarket YES): entry price p, shares = notional/p.
  win  -> payout shares*$1, ROI = (1-p)/p
  loss -> payout 0,        ROI = -1.0
outcomes = ["Up","Down"]; outcomePrices[0] is Up (the side we buy).

Idempotent: skips markets already in the resolutions file.
"""
import csv
import json
import os
import sys
import urllib.request
from datetime import datetime, timezone

LEDGER = os.environ.get("LEDGER_PATH", "/home/neo/quad_ledger.csv")
RESOLUTIONS = os.environ.get("RESOLUTIONS_PATH", "/home/neo/quad_resolutions.csv")
FIELDS = ["ts", "coin", "market_id", "question", "yes_price", "resolve_ts",
          "outcome", "win", "roi"]


def now_iso():
    return datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ")


def parse_yes_price(raw):
    """Ledger stores yes_price as either a JSON array of both outcome prices
    (autopilot) or a single YES price float (live-order paper mode)."""
    if not raw:
        return None
    raw = raw.strip()
    try:
        arr = json.loads(raw)
        if isinstance(arr, list) and arr:
            return float(arr[0])  # index 0 == Up == our side
    except Exception:
        pass
    try:
        return float(raw)
    except Exception:
        return None


def fetch_market(mid):
    url = f"https://gamma-api.polymarket.com/markets/{mid}"
    req = urllib.request.Request(url, headers={"User-Agent": "quad-lab/0.1"})
    with urllib.request.urlopen(req, timeout=30) as r:
        return json.load(r)


def outcome_prices(m):
    """gamma-api returns outcomePrices as a JSON *string* like '["1", "0"]'."""
    raw = m.get("outcomePrices")
    if isinstance(raw, list):
        return [str(x) for x in raw]
    if isinstance(raw, str):
        try:
            arr = json.loads(raw)
            return [str(x) for x in arr]
        except Exception:
            return []
    return []


def load_resolved():
    ids = set()
    if os.path.exists(RESOLUTIONS):
        with open(RESOLUTIONS) as f:
            for r in csv.DictReader(f):
                ids.add(r["market_id"])
    return ids


def append_resolution(row):
    exists = os.path.exists(RESOLUTIONS)
    with open(RESOLUTIONS, "a", newline="") as f:
        w = csv.DictWriter(f, fieldnames=FIELDS)
        if not exists:
            w.writeheader()
        w.writerow({k: row.get(k, "") for k in FIELDS})


def main():
    if not os.path.exists(LEDGER):
        sys.exit(f"ledger not found: {LEDGER}")
    rows = []
    with open(LEDGER) as f:
        rows = [r for r in csv.DictReader(f)]

    signals = [r for r in rows if r.get("action") == "BUY_YES_15M_UP"
               and r.get("mode") == "paper" and r.get("market_id")]
    done = load_resolved()
    pending = [r for r in signals if r.get("market_id") not in done]
    print(f"signals={len(signals)} already_resolved={len(signals) - len(pending)} pending={len(pending)}")

    wins = losses = unresolved = 0
    total_roi = 0.0
    for r in pending:
        mid = r["market_id"]
        try:
            m = fetch_market(mid)
        except Exception as e:
            print(f"  {mid} {r['coin']}: fetch err {e}")
            unresolved += 1
            continue
        status = m.get("umaResolutionStatus")
        prices = outcome_prices(m)
        if status != "resolved" or len(prices) < 2 or m.get("closed") is not True:
            print(f"  {mid} {r['coin']}: not resolved yet (status={status})")
            unresolved += 1
            continue
        p = parse_yes_price(r.get("yes_price"))
        if p is None:
            print(f"  {mid} {r['coin']}: unparsable yes_price={r.get('yes_price')!r}")
            unresolved += 1
            continue
        up_won = prices[0] == "1"
        roi = (1 - p) / p if up_won else -1.0
        row = {"ts": now_iso(), "coin": r["coin"], "market_id": mid,
               "question": r.get("question", ""), "yes_price": str(p),
               "resolve_ts": r.get("resolve_ts", ""),
               "outcome": "UP" if up_won else "DOWN",
               "win": str(up_won), "roi": f"{roi:.4f}"}
        append_resolution(row)
        wins += 1 if up_won else 0
        losses += 0 if up_won else 1
        total_roi += roi
        print(f"  {mid} {r['coin']}: price={p} -> {'WIN' if up_won else 'LOSS'} roi={roi:+.3f}")

    if wins + losses:
        n = wins + losses
        print(f"\nresolved now: {wins}W/{losses}L  hit={wins/n:.3f}  mean_roi={total_roi/n:+.3f}")
    if unresolved:
        print(f"unresolved still: {unresolved}")
    print("done", now_iso())


if __name__ == "__main__":
    main()