gavindiaz/weatherbot
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Delete bot_v2.py

Browse Source
This commit is contained in:
alteregoeth-ai
2026-03-10 13:40:15 -05:00
committed by GitHub
parent d906d24997
commit a8557a4887
1 changed files with 0 additions and 642 deletions
Download Patch File Download Diff File Expand all files Collapse all files
bot_v2.py
-642
View File
@@ -1,642 +0,0 @@
#!/usr/bin/env python3
"""
Weather Trading Bot v2 — Polymarket
Kelly Criterion + Expected Value simulation.
Usage:
python bot_v2.py # Paper mode with $1000 virtual balance
python bot_v2.py --live # Simulate trades against real prices
python bot_v2.py --positions
python bot_v2.py --reset # Reset simulation balance
python bot_v2.py --monitor # Live price monitor, updates dashboard every 10s
"""
import re
import json
import argparse
import requests
from datetime import datetime, timezone, timedelta
# =============================================================================
# CONFIG
# =============================================================================
with open("config.json") as f:
_cfg = json.load(f)
ENTRY_THRESHOLD = _cfg.get("entry_threshold", 0.15)
EXIT_THRESHOLD = _cfg.get("exit_threshold", 0.45)
MAX_TRADES = _cfg.get("max_trades_per_run", 5)
MIN_HOURS_LEFT = _cfg.get("min_hours_to_resolution", 2)
PRICE_DROP_SIGNAL = _cfg.get("price_drop_threshold", 0.10)
# Kelly + EV settings
NOAA_ACCURACY = 0.78 # NOAA forecast accuracy for 1-3 day predictions
KELLY_FRACTION = 0.25 # Use 1/4 Kelly for safety
MAX_POSITION_PCT = 0.10 # Never bet more than 10% of balance on one trade
MIN_EV = 0.05 # Minimum EV to enter
SIM_BALANCE = 1000.0 # Starting virtual balance
# Airport coordinates — match the exact stations Polymarket resolves on
LOCATIONS = {
"nyc": {"lat": 40.7772, "lon": -73.8726, "name": "New York City"}, # KLGA LaGuardia
"chicago": {"lat": 41.9742, "lon": -87.9073, "name": "Chicago"}, # KORD O'Hare
"miami": {"lat": 25.7959, "lon": -80.2870, "name": "Miami"}, # KMIA
"dallas": {"lat": 32.8471, "lon": -96.8518, "name": "Dallas"}, # KDAL Love Field
"seattle": {"lat": 47.4502, "lon": -122.3088, "name": "Seattle"}, # KSEA Sea-Tac
"atlanta": {"lat": 33.6407, "lon": -84.4277, "name": "Atlanta"}, # KATL Hartsfield
}
# NWS hourly endpoints per city
NWS_ENDPOINTS = {
"nyc": "https://api.weather.gov/gridpoints/OKX/37,39/forecast/hourly",
"chicago": "https://api.weather.gov/gridpoints/LOT/66,77/forecast/hourly",
"miami": "https://api.weather.gov/gridpoints/MFL/106,51/forecast/hourly",
"dallas": "https://api.weather.gov/gridpoints/FWD/87,107/forecast/hourly",
"seattle": "https://api.weather.gov/gridpoints/SEW/124,61/forecast/hourly",
"atlanta": "https://api.weather.gov/gridpoints/FFC/50,82/forecast/hourly",
}
# Station IDs for real observations
STATION_IDS = {
"nyc": "KLGA", "chicago": "KORD", "miami": "KMIA",
"dallas": "KDAL", "seattle": "KSEA", "atlanta": "KATL",
}
ACTIVE_LOCATIONS = _cfg.get("locations", "nyc,chicago,miami,dallas,seattle,atlanta").split(",")
ACTIVE_LOCATIONS = [l.strip().lower() for l in ACTIVE_LOCATIONS]
MONTHS = ["january","february","march","april","may","june",
"july","august","september","october","november","december"]
# =============================================================================
# COLORS
# =============================================================================
class C:
GREEN = "\033[92m"
YELLOW = "\033[93m"
RED = "\033[91m"
CYAN = "\033[96m"
GRAY = "\033[90m"
RESET = "\033[0m"
BOLD = "\033[1m"
def ok(msg): print(f"{C.GREEN} ✅ {msg}{C.RESET}")
def warn(msg): print(f"{C.YELLOW} ⚠️ {msg}{C.RESET}")
def info(msg): print(f"{C.CYAN} {msg}{C.RESET}")
def skip(msg): print(f"{C.GRAY} ⏸️ {msg}{C.RESET}")
# =============================================================================
# KELLY CRITERION + EV
# =============================================================================
def calculate_ev(our_prob: float, market_price: float) -> float:
"""
Expected Value per $1 risked.
EV = (our_prob * payout) - (1 - our_prob)
payout = (1 / market_price) - 1
Example: our_prob=0.75, price=0.08
payout = 1/0.08 - 1 = 11.5x
EV = 0.75 * 11.5 - 0.25 = +$8.12 per $1 risked
"""
if market_price <= 0 or market_price >= 1:
return 0.0
payout = (1.0 / market_price) - 1.0
ev = (our_prob * payout) - (1.0 - our_prob)
return round(ev, 4)
def calculate_kelly(our_prob: float, market_price: float) -> float:
"""
Kelly Criterion: optimal fraction of bankroll to bet.
f* = (p * b - q) / b
We apply KELLY_FRACTION (0.25) for safety — fractional Kelly.
Result is capped at MAX_POSITION_PCT (10% of balance).
"""
if market_price <= 0 or market_price >= 1:
return 0.0
b = (1.0 / market_price) - 1.0
p = our_prob
q = 1.0 - p
kelly = (p * b - q) / b
kelly = max(0.0, kelly)
kelly = kelly * KELLY_FRACTION
kelly = min(kelly, MAX_POSITION_PCT)
return round(kelly, 4)
def calculate_position_size(kelly_fraction: float, balance: float) -> float:
return round(kelly_fraction * balance, 2)
# =============================================================================
# SIMULATION STATE
# =============================================================================
SIM_FILE = "simulation.json"
def load_sim() -> dict:
try:
with open(SIM_FILE) as f:
return json.load(f)
except FileNotFoundError:
return {
"balance": SIM_BALANCE,
"starting_balance": SIM_BALANCE,
"positions": {},
"trades": [],
"total_trades": 0,
"wins": 0,
"losses": 0,
"peak_balance": SIM_BALANCE,
}
def save_sim(sim: dict):
with open(SIM_FILE, "w") as f:
json.dump(sim, f, indent=2)
def reset_sim():
import os
if os.path.exists(SIM_FILE):
os.remove(SIM_FILE)
print(f"{C.GREEN} ✅ Simulation reset — balance back to ${SIM_BALANCE:.2f}{C.RESET}")
# =============================================================================
# NWS FORECAST
# =============================================================================
def get_forecast(city_slug: str) -> dict:
"""
Fetch daily max temperature from NWS.
Combines real station observations (past hours today) with
hourly forecast (upcoming hours) to get the true daily maximum.
"""
forecast_url = NWS_ENDPOINTS.get(city_slug)
station_id = STATION_IDS.get(city_slug)
daily_max = {}
headers = {"User-Agent": "weatherbot/1.0"}
# Real observations — what already happened today
try:
obs_url = f"https://api.weather.gov/stations/{station_id}/observations?limit=48"
r = requests.get(obs_url, timeout=10, headers=headers)
for obs in r.json().get("features", []):
props = obs["properties"]
time_str = props.get("timestamp", "")[:10]
temp_c = props.get("temperature", {}).get("value")
if temp_c is not None:
temp_f = round(temp_c * 9/5 + 32)
if time_str not in daily_max or temp_f > daily_max[time_str]:
daily_max[time_str] = temp_f
except Exception as e:
warn(f"Observations error for {city_slug}: {e}")
# Hourly forecast — upcoming hours
try:
r = requests.get(forecast_url, timeout=10, headers=headers)
periods = r.json()["properties"]["periods"]
for p in periods:
date = p["startTime"][:10]
temp = p["temperature"]
if p.get("temperatureUnit") == "C":
temp = round(temp * 9/5 + 32)
if date not in daily_max or temp > daily_max[date]:
daily_max[date] = temp
except Exception as e:
warn(f"Forecast error for {city_slug}: {e}")
return daily_max
# =============================================================================
# POLYMARKET API
# =============================================================================
def get_polymarket_event(city_slug: str, month: str, day: int, year: int) -> dict:
slug = f"highest-temperature-in-{city_slug}-on-{month}-{day}-{year}"
url = f"https://gamma-api.polymarket.com/events?slug={slug}"
try:
r = requests.get(url, timeout=10)
data = r.json()
if data and isinstance(data, list) and len(data) > 0:
return data[0]
except Exception as e:
warn(f"Polymarket API error: {e}")
return None
def get_price_history(market_id: str) -> list:
url = f"https://clob.polymarket.com/prices-history?market={market_id}&interval=1d&fidelity=60"
try:
r = requests.get(url, timeout=10)
return r.json().get("history", [])
except Exception:
return []
# =============================================================================
# PARSING
# =============================================================================
def parse_temp_range(question: str) -> tuple:
if not question:
return None
if "or below" in question.lower():
m = re.search(r'(\d+)°F or below', question, re.IGNORECASE)
if m: return (-999, int(m.group(1)))
if "or higher" in question.lower():
m = re.search(r'(\d+)°F or higher', question, re.IGNORECASE)
if m: return (int(m.group(1)), 999)
m = re.search(r'between (\d+)-(\d+)°F', question, re.IGNORECASE)
if m: return (int(m.group(1)), int(m.group(2)))
return None
def hours_until_resolution(event: dict) -> float:
try:
end_date = event.get("endDate") or event.get("end_date_iso")
if not end_date: return 999
end_dt = datetime.fromisoformat(end_date.replace("Z", "+00:00"))
delta = (end_dt - datetime.now(timezone.utc)).total_seconds() / 3600
return max(0, delta)
except Exception:
return 999
def detect_price_drop(history: list) -> dict:
if not history or len(history) < 2:
return {"dropped": False, "change": 0}
recent = history[-1].get("p", 0.5)
lookback = min(96, len(history) - 1)
old = history[-lookback].get("p", recent)
if old == 0: return {"dropped": False, "change": 0}
change = (recent - old) / old
return {"dropped": change < -PRICE_DROP_SIGNAL, "change": change}
# =============================================================================
# SHOW POSITIONS
# =============================================================================
def show_positions():
sim = load_sim()
positions = sim["positions"]
print(f"\n{C.BOLD}📊 Open Positions:{C.RESET}")
if not positions:
print(" No open positions")
return
total_pnl = 0
for mid, pos in positions.items():
try:
url = f"https://gamma-api.polymarket.com/markets/{mid}"
r = requests.get(url, timeout=5)
prices = json.loads(r.json().get("outcomePrices", "[0.5,0.5]"))
current_price = float(prices[0])
except Exception:
current_price = pos["entry_price"]
pnl = (current_price - pos["entry_price"]) * pos["shares"]
total_pnl += pnl
pnl_str = f"{C.GREEN}+${pnl:.2f}{C.RESET}" if pnl >= 0 else f"{C.RED}-${abs(pnl):.2f}{C.RESET}"
print(f"\n • {pos['question'][:65]}...")
print(f" Entry: ${pos['entry_price']:.3f} | Now: ${current_price:.3f} | "
f"Shares: {pos['shares']:.1f} | PnL: {pnl_str}")
print(f" Kelly used: {pos.get('kelly_pct', 0):.1%} | EV: {pos.get('ev', 0):.2f} | Cost: ${pos['cost']:.2f}")
print(f"\n Balance: ${sim['balance']:.2f}")
pnl_color = C.GREEN if total_pnl >= 0 else C.RED
print(f" Open PnL: {pnl_color}{'+'if total_pnl>=0 else ''}{total_pnl:.2f}{C.RESET}")
print(f" Total trades: {sim['total_trades']} | W/L: {sim['wins']}/{sim['losses']}")
# =============================================================================
# MAIN STRATEGY
# =============================================================================
def run(dry_run: bool = True):
print(f"\n{C.BOLD}{C.CYAN}🌤 Weather Trading Bot v2 — Kelly + EV Edition{C.RESET}")
print("=" * 55)
sim = load_sim()
balance = sim["balance"]
positions = sim["positions"]
mode = f"{C.YELLOW}PAPER MODE{C.RESET}" if dry_run else f"{C.GREEN}LIVE MODE{C.RESET}"
starting = sim["starting_balance"]
total_return = (balance - starting) / starting * 100
return_str = f"{C.GREEN}+{total_return:.1f}%{C.RESET}" if total_return >= 0 else f"{C.RED}{total_return:.1f}%{C.RESET}"
print(f"\n Mode: {mode}")
print(f" Virtual balance: {C.BOLD}${balance:.2f}{C.RESET} (started ${starting:.2f}, {return_str})")
print(f" Kelly fraction: {KELLY_FRACTION:.0%} of full Kelly")
print(f" Max per trade: {MAX_POSITION_PCT:.0%} of balance")
print(f" Min EV: {MIN_EV:.2f} per $1 risked")
print(f" NOAA accuracy: {NOAA_ACCURACY:.0%}")
print(f" Trades W/L: {sim['wins']}/{sim['losses']}")
forecast_cache = {}
trades_executed = 0
opportunities = 0
# Check exits
print(f"\n{C.BOLD}📤 Checking exits...{C.RESET}")
exits_found = 0
for mid, pos in list(positions.items()):
try:
url = f"https://gamma-api.polymarket.com/markets/{mid}"
r = requests.get(url, timeout=5)
prices = json.loads(r.json().get("outcomePrices", "[0.5,0.5]"))
current_price = float(prices[0])
except Exception:
continue
if current_price >= EXIT_THRESHOLD:
exits_found += 1
pnl = (current_price - pos["entry_price"]) * pos["shares"]
ok(f"EXIT: {pos['question'][:50]}...")
info(f"Price ${current_price:.3f} >= exit ${EXIT_THRESHOLD:.2f} | PnL: +${pnl:.2f}")
if not dry_run:
balance += pos["cost"] + pnl
sim["wins"] += 1 if pnl > 0 else 0
sim["losses"] += 1 if pnl <= 0 else 0
sim["trades"].append({
"type": "exit", "question": pos["question"],
"entry_price": pos["entry_price"], "exit_price": current_price,
"pnl": round(pnl, 2), "cost": pos["cost"],
"closed_at": datetime.now().isoformat(),
})
del positions[mid]
ok(f"Closed — PnL: {'+'if pnl>=0 else ''}{pnl:.2f}")
else:
skip("Paper mode — not selling")
if exits_found == 0:
skip("No exit opportunities")
# Scan entries
print(f"\n{C.BOLD}🔍 Scanning for entry signals...{C.RESET}")
for city_slug in ACTIVE_LOCATIONS:
if city_slug not in LOCATIONS:
warn(f"Unknown location: {city_slug}")
continue
loc_data = LOCATIONS[city_slug]
if city_slug not in forecast_cache:
forecast_cache[city_slug] = get_forecast(city_slug)
forecast = forecast_cache[city_slug]
if not forecast:
continue
for i in range(0, 4):
date = datetime.now() + timedelta(days=i)
date_str = date.strftime("%Y-%m-%d")
month = MONTHS[date.month - 1]
day = date.day
year = date.year
forecast_temp = forecast.get(date_str)
if forecast_temp is None:
continue
event = get_polymarket_event(city_slug, month, day, year)
if not event:
continue
hours_left = hours_until_resolution(event)
print(f"\n{C.BOLD}📍 {loc_data['name']} — {date_str}{C.RESET}")
info(f"Forecast: {forecast_temp}°F | Resolves in: {hours_left:.0f}h")
if hours_left < MIN_HOURS_LEFT:
skip(f"Resolves in {hours_left:.0f}h — too soon")
continue
matched = None
for market in event.get("markets", []):
question = market.get("question", "")
rng = parse_temp_range(question)
if rng and rng[0] <= forecast_temp <= rng[1]:
try:
prices = json.loads(market.get("outcomePrices", "[0.5,0.5]"))
yes_price = float(prices[0])
except Exception:
continue
matched = {"market": market, "question": question,
"price": yes_price, "range": rng}
break
if not matched:
skip(f"No bucket found for {forecast_temp}°F")
continue
price = matched["price"]
market_id = matched["market"].get("id", "")
question = matched["question"]
info(f"Bucket: {question[:60]}")
info(f"Market price: ${price:.3f}")
# Trend check
history = get_price_history(market_id)
trend = detect_price_drop(history)
if trend["dropped"]:
info(f"📉 Price dropped {abs(trend['change']):.0%} in 24h — stronger signal")
# Kelly + EV
our_prob = NOAA_ACCURACY
if trend["dropped"] and abs(trend["change"]) > 0.20:
our_prob = min(0.90, our_prob + 0.05)
ev = calculate_ev(our_prob, price)
kelly_pct = calculate_kelly(our_prob, price)
position_size = calculate_position_size(kelly_pct, balance)
print(f"\n {C.BOLD}📐 Kelly + EV Analysis:{C.RESET}")
info(f" Our probability: {our_prob:.0%}")
info(f" Market implies: {price:.1%}")
info(f" Edge: {our_prob - price:.1%}")
ev_color = C.GREEN if ev > 0 else C.RED
print(f" {C.CYAN} EV per $1: {ev_color}{ev:+.2f}{C.RESET}")
print(f" {C.CYAN} Kelly fraction: {kelly_pct:.1%} of balance{C.RESET}")
print(f" {C.CYAN} Position size: ${position_size:.2f}{C.RESET}")
if price >= ENTRY_THRESHOLD:
skip(f"Price ${price:.3f} above threshold ${ENTRY_THRESHOLD:.2f}")
continue
if ev < MIN_EV:
skip(f"EV {ev:.2f} below minimum {MIN_EV:.2f} — skip")
continue
if kelly_pct <= 0:
skip("Kelly says no edge — skip")
continue
opportunities += 1
ok(f"ENTRY signal! EV={ev:+.2f} | Kelly={kelly_pct:.1%} | Size=${position_size:.2f}")
if market_id in positions:
skip("Already in this market")
continue
if trades_executed >= MAX_TRADES:
skip(f"Max trades ({MAX_TRADES}) reached")
continue
if position_size < 0.50:
skip(f"Position size ${position_size:.2f} too small — skip")
continue
shares = position_size / price
info(f"Buying {shares:.1f} shares @ ${price:.3f} = ${position_size:.2f}")
if not dry_run:
balance -= position_size
positions[market_id] = {
"question": question,
"entry_price": price,
"shares": shares,
"cost": position_size,
"kelly_pct": kelly_pct,
"ev": ev,
"our_prob": our_prob,
"date": date_str,
"location": city_slug,
"forecast_temp": forecast_temp,
"opened_at": datetime.now().isoformat(),
}
sim["total_trades"] += 1
sim["trades"].append({
"type": "entry", "question": question,
"entry_price": price, "shares": shares,
"cost": position_size, "kelly_pct": kelly_pct,
"ev": ev, "our_prob": our_prob,
"opened_at": datetime.now().isoformat(),
})
trades_executed += 1
ok(f"Bought {shares:.1f} shares — ${position_size:.2f} deducted from balance")
else:
skip("Paper mode — not buying")
trades_executed += 1
if not dry_run:
sim["balance"] = round(balance, 2)
sim["positions"] = positions
sim["peak_balance"] = max(sim["peak_balance"], balance)
save_sim(sim)
print(f"\n{'=' * 55}")
print(f"{C.BOLD}📊 Summary:{C.RESET}")
info(f"Opportunities found: {opportunities}")
info(f"Trades executed: {trades_executed}")
info(f"Exits found: {exits_found}")
info(f"Balance: ${balance:.2f}")
if dry_run:
print(f"\n {C.YELLOW}[PAPER MODE — use --live to simulate trades against real prices]{C.RESET}")
# =============================================================================
# LIVE MONITOR
# =============================================================================
import time as _time
def monitor(interval: int = 10):
"""
Background monitor — fetches live prices every N seconds,
updates simulation.json so the dashboard stays current.
Auto-exits positions when price hits EXIT_THRESHOLD.
"""
print(f"\n{C.BOLD}{C.CYAN}📡 Live Monitor — refreshing every {interval}s{C.RESET}")
print(f" Auto-exit threshold: ${EXIT_THRESHOLD:.2f}")
print(f" Press Ctrl+C to stop\n")
while True:
try:
sim = load_sim()
positions = sim.get("positions", {})
if not positions:
print(f"{C.GRAY} {_time.strftime('%H:%M:%S')} — No open positions{C.RESET}")
_time.sleep(interval)
continue
total_pnl = 0
for mid, pos in list(positions.items()):
try:
url = f"https://gamma-api.polymarket.com/markets/{mid}"
r = requests.get(url, timeout=5)
data = r.json()
prices = json.loads(data.get("outcomePrices", "[0.5,0.5]"))
current_price = float(prices[0])
except Exception:
current_price = pos.get("current_price", pos["entry_price"])
pnl = (current_price - pos["entry_price"]) * pos["shares"]
pos["current_price"] = round(current_price, 4)
pos["pnl"] = round(pnl, 2)
total_pnl += pnl
pnl_str = f"{C.GREEN}+${pnl:.2f}{C.RESET}" if pnl >= 0 else f"{C.RED}-${abs(pnl):.2f}{C.RESET}"
print(f" {C.GRAY}{_time.strftime('%H:%M:%S')}{C.RESET} "
f"{pos['question'][:45]}... "
f"${current_price:.3f} {pnl_str}")
if current_price >= EXIT_THRESHOLD:
ok(f"AUTO EXIT: {pos['question'][:50]}... PnL: +${pnl:.2f}")
sim["balance"] = round(sim["balance"] + pos["cost"] + pnl, 2)
sim["wins"] += 1 if pnl > 0 else 0
sim["losses"] += 1 if pnl <= 0 else 0
sim["trades"].append({
"type": "exit",
"question": pos["question"],
"entry_price": pos["entry_price"],
"exit_price": current_price,
"pnl": round(pnl, 2),
"cost": pos["cost"],
"kelly_pct": pos.get("kelly_pct", 0),
"ev": pos.get("ev", 0),
"closed_at": datetime.now().isoformat(),
})
del sim["positions"][mid]
sim["peak_balance"] = max(sim.get("peak_balance", sim["balance"]), sim["balance"])
total_str = f"{C.GREEN}+${total_pnl:.2f}{C.RESET}" if total_pnl >= 0 else f"{C.RED}-${abs(total_pnl):.2f}{C.RESET}"
print(f" {'─'*60}")
print(f" Open PnL: {total_str} | Balance: ${sim['balance']:.2f} | "
f"Positions: {len(sim['positions'])}\n")
save_sim(sim)
except KeyboardInterrupt:
print(f"\n{C.YELLOW} Monitor stopped{C.RESET}")
break
except Exception as e:
warn(f"Monitor error: {e}")
_time.sleep(interval)
# =============================================================================
# CLI
# =============================================================================
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Weather Trading Bot v2 — Kelly + EV")
parser.add_argument("--live", action="store_true", help="Execute trades (updates simulation balance)")
parser.add_argument("--positions", action="store_true", help="Show open positions")
parser.add_argument("--reset", action="store_true", help="Reset simulation to $1000")
parser.add_argument("--monitor", action="store_true", help="Live price monitor")
parser.add_argument("--interval", type=int, default=10, help="Monitor refresh interval in seconds")
args = parser.parse_args()
if args.reset:
reset_sim()
elif args.positions:
show_positions()
elif args.monitor:
monitor(interval=args.interval)
else:
run(dry_run=not args.live)