/city chicago"
)
bot.reply_to(message, welcome_text, parse_mode="HTML")
@@ -70,20 +74,22 @@ def start_bot():
price = s.get("price", 50)
if 5 <= price <= 95 and s.get("target_date"):
active_signals.append(s)
-
+
if not active_signals:
bot.send_message(message.chat.id, "📭 当前没有值得关注的活跃市场。")
return
# 按日期排序，优先最早结算的
active_signals.sort(key=lambda x: x.get("target_date", "9999-99-99"))
-
+
# 获取最早的日期
earliest_date = active_signals[0].get("target_date")
-
+
# 只取最早日期的市场
- earliest_markets = [s for s in active_signals if s.get("target_date") == earliest_date]
-
+ earliest_markets = [
+ s for s in active_signals if s.get("target_date") == earliest_date
+ ]
+
# 按"机会价值"排序：接近锁定区间（85-95¢）的优先
def opportunity_score(s):
price = s.get("price", 50)
@@ -97,16 +103,16 @@ def start_bot():
return max_price # 接近锁定
else:
return max_price / 2 # 远离锁定
-
+
earliest_markets.sort(key=opportunity_score, reverse=True)
top_markets = earliest_markets[:5]
# 构建消息
msg_lines = [
f"🎯 即将结算市场 ({earliest_date})\n",
- f"共 {len(earliest_markets)} 个活跃选项\n"
+ f"共 {len(earliest_markets)} 个活跃选项\n",
]
-
+
for i, s in enumerate(top_markets, 1):
city = s.get("city", "Unknown")
option = s.get("option", "Unknown")
@@ -115,17 +121,18 @@ def start_bot():
buy_no = s.get("buy_no", 100 - s.get("price", 50))
volume = s.get("volume", 0)
url = s.get("url", "")
-
+
# 解析选项区间
import re
- range_match = re.search(r'(\d+)-(\d+)', option)
- below_match = re.search(r'(\d+).*or below', option, re.I)
- higher_match = re.search(r'(\d+).*or higher', option, re.I)
-
+
+ range_match = re.search(r"(\d+)-(\d+)", option)
+ below_match = re.search(r"(\d+).*or below", option, re.I)
+ higher_match = re.search(r"(\d+).*or higher", option, re.I)
+
# 判断预测与区间关系
analysis = ""
try:
- pred_val = float(re.search(r'[\d.]+', str(prediction)).group())
+ pred_val = float(re.search(r"[\d.]+", str(prediction)).group())
if range_match:
low, high = int(range_match.group(1)), int(range_match.group(2))
if pred_val < low:
@@ -148,7 +155,7 @@ def start_bot():
analysis = f"预测{pred_val}°低于{threshold}° → 买NO ✓"
except:
analysis = f"预测: {prediction}"
-
+
# 判断最佳方向
if buy_no >= 85:
direction = f"Buy No {buy_no}¢"
@@ -170,18 +177,18 @@ def start_bot():
direction = f"Yes:{buy_yes}¢ No:{buy_no}¢"
lock_status = "⚖️均衡"
confidence = "📊"
-
+
# 提取修复后的精确当地时间
local_time = s.get("local_time", "")
time_only = local_time.split(" ")[1] if " " in local_time else ""
time_suffix = f" | 🕒{time_only}" if time_only else ""
-
+
msg_lines.append(
f"{confidence} {i}. {city} {option}\n"
f" 💡 {analysis}\n"
f" 📊 {direction} | {lock_status}{time_suffix}\n"
)
-
+
bot.send_message(message.chat.id, "\n".join(msg_lines), parse_mode="HTML")
except Exception as e:
@@ -215,9 +222,9 @@ def start_bot():
html_path = generate_portfolio_html(data)
with open(html_path, "rb") as f:
bot.send_document(
- message.chat.id,
- f,
- caption=f"📊 完整持仓报告 ({len(positions)}个持仓)\n💳 余额: ${balance:.2f}"
+ message.chat.id,
+ f,
+ caption=f"📊 完整持仓报告 ({len(positions)}个持仓)\n💳 余额: ${balance:.2f}",
)
return
@@ -229,20 +236,28 @@ def start_bot():
for pid, pos in positions.items():
target_date = pos.get("target_date") or "未知"
if target_date not in positions_by_date:
- positions_by_date[target_date] = {"count": 0, "pnl": 0, "cost": 0}
+ positions_by_date[target_date] = {
+ "count": 0,
+ "pnl": 0,
+ "cost": 0,
+ }
positions_by_date[target_date]["count"] += 1
positions_by_date[target_date]["pnl"] += pos.get("pnl_usd", 0)
positions_by_date[target_date]["cost"] += pos.get("cost_usd", 0)
-
+
msg_lines.append(f"\n📌 持仓概览 (共{len(positions)}个)")
for target_date in sorted(positions_by_date.keys()):
info = positions_by_date[target_date]
icon = "📈" if info["pnl"] >= 0 else "📉"
- msg_lines.append(f"{icon} {target_date}: {info['count']}笔 ${info['cost']:.0f}投入 {info['pnl']:+.2f}$")
-
+ msg_lines.append(
+ f"{icon} {target_date}: {info['count']}笔 ${info['cost']:.0f}投入 {info['pnl']:+.2f}$"
+ )
+
total_pnl = sum(p.get("pnl_usd", 0) for p in positions.values())
total_cost = sum(p.get("cost_usd", 0) for p in positions.values())
- msg_lines.append(f"💰 合计: ${total_cost:.0f}投入 {total_pnl:+.2f}$")
+ msg_lines.append(
+ f"💰 合计: ${total_cost:.0f}投入 {total_pnl:+.2f}$"
+ )
msg_lines.append("\n📋 最新持仓:")
recent_positions = list(positions.values())[-5:]
@@ -251,14 +266,20 @@ def start_bot():
icon = "🟢" if pnl >= 0 else "🔴"
pred = pos.get("predicted_temp", "")
pred_text = f"预测:{pred}" if pred else ""
- msg_lines.append(f"{icon} {pos['city']} {pos['option']} {pred_text} {pnl:+.2f}$")
+ msg_lines.append(
+ f"{icon} {pos['city']} {pos['option']} {pred_text} {pnl:+.2f}$"
+ )
trades = data.get("trades", [])
if trades:
msg_lines.append("\n📝 最近操作:")
for t in reversed(trades[-3:]):
t_type = "🛒" if t["type"] == "BUY" else "💰"
- t_time = t.get("time", "").split(" ")[1] if " " in t.get("time", "") else ""
+ t_time = (
+ t.get("time", "").split(" ")[1]
+ if " " in t.get("time", "")
+ else ""
+ )
msg_lines.append(f"• {t_time} {t_type} {t['city']} {t['option']}")
if history:
@@ -267,7 +288,9 @@ def start_bot():
total_cost = sum(p.get("cost_usd", 0) for p in history)
total_profit = sum(p.get("pnl_usd", 0) for p in history)
win_rate = (wins / total_trades) * 100 if total_trades > 0 else 0
- msg_lines.append(f"\n📈 历史: {total_trades}笔 胜率{win_rate:.0f}% 盈亏{total_profit:+.2f}$")
+ msg_lines.append(
+ f"\n📈 历史: {total_trades}笔 胜率{win_rate:.0f}% 盈亏{total_profit:+.2f}$"
+ )
msg_lines.append(f"\n💳 余额: ${balance:.2f}")
@@ -276,15 +299,14 @@ def start_bot():
except Exception as e:
bot.reply_to(message, f"❌ 获取持仓失败: {e}")
-
def generate_portfolio_html(data):
"""生成漂亮的 HTML 持仓报告"""
from datetime import datetime, timedelta
-
+
positions = data.get("positions", {})
history = data.get("history", [])
balance = data.get("balance", 1000.0)
-
+
# 按日期分组
positions_by_date = {}
for pid, pos in positions.items():
@@ -292,13 +314,13 @@ def start_bot():
if target_date not in positions_by_date:
positions_by_date[target_date] = []
positions_by_date[target_date].append(pos)
-
+
total_pnl = sum(p.get("pnl_usd", 0) for p in positions.values())
total_cost = sum(p.get("cost_usd", 0) for p in positions.values())
-
+
# 生成 HTML
now_bj = (datetime.utcnow() + timedelta(hours=8)).strftime("%Y-%m-%d %H:%M")
-
+
html = f"""
@@ -324,19 +346,19 @@ def start_bot():
| 城市 | 选项 | 方向 | 入场 | 当前 | 预测 | 盈亏 | |||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| {pos.get('city', '-')} | -{pos.get('option', '-')} | -{pos.get('side', '-')} | -{pos.get('entry_price', 0)}¢ | -{pos.get('current_price', 0)}¢ | +{pos.get("city", "-")} | +{pos.get("option", "-")} | +{pos.get("side", "-")} | +{pos.get("entry_price", 0)}¢ | +{pos.get("current_price", 0)}¢ | {pred} | {pnl:+.2f}$ |
/city chicago\n\n"
+ "支持城市: Seattle, London, Dallas, Miami, Atlanta, Chicago, "
+ "New York, Seoul, Ankara, Toronto, Wellington, Buenos Aires",
+ parse_mode="HTML",
+ )
+ return
+
+ city_input = parts[1].strip().lower()
+
+ # 城市别名映射
+ city_aliases = {
+ "nyc": "new york",
+ "ny": "new york",
+ "la": "los angeles",
+ "chi": "chicago",
+ "atl": "atlanta",
+ "sea": "seattle",
+ "dal": "dallas",
+ "mia": "miami",
+ "tor": "toronto",
+ "ank": "ankara",
+ "sel": "seoul",
+ "wel": "wellington",
+ "ba": "buenos aires",
+ "buenosaires": "buenos aires",
+ "伦敦": "london",
+ "纽约": "new york",
+ "西雅图": "seattle",
+ "芝加哥": "chicago",
+ "多伦多": "toronto",
+ "首尔": "seoul",
+ "惠灵顿": "wellington",
+ "达拉斯": "dallas",
+ "亚特兰大": "atlanta",
+ }
+ city_name = city_aliases.get(city_input, city_input)
+
+ bot.send_message(
+ message.chat.id, f"🔍 正在查询 {city_name.title()} 的市场信息..."
+ )
+
+ # 1. 获取城市坐标
+ coords = weather.get_coordinates(city_name)
+ if not coords:
+ bot.reply_to(message, f"❌ 未找到城市: {city_name}")
+ return
+
+ # 2. 获取天气数据 (Open-Meteo + METAR)
+ weather_data = weather.fetch_all_sources(
+ city_name, lat=coords["lat"], lon=coords["lon"]
+ )
+
+ # 3. 从缓存中获取该城市的市场数据
+ city_markets = []
+ if os.path.exists("data/active_signals.json"):
+ with open("data/active_signals.json", "r", encoding="utf-8") as f:
+ all_signals = json.load(f)
+ city_markets = [
+ s
+ for s in all_signals
+ if s.get("city", "").lower() == city_name.lower()
+ ]
+
+ # 4. 构建消息
+ msg_lines = [f"📍 {city_name.title()} 市场详情"]
+ msg_lines.append("═" * 20)
+
+ # 天气信息
+ open_meteo = weather_data.get("open-meteo", {})
+ metar = weather_data.get("metar", {})
+
+ temp_unit = open_meteo.get("unit", "celsius")
+ temp_symbol = "°F" if temp_unit == "fahrenheit" else "°C"
+
+ # 当前时间
+ local_time = open_meteo.get("current", {}).get("local_time", "")
+ if local_time:
+ time_only = (
+ local_time.split(" ")[1] if " " in local_time else local_time
+ )
+ msg_lines.append(f"🕐 当地时间: {time_only}")
+
+ # Open-Meteo 预测
+ daily = open_meteo.get("daily", {})
+ dates = daily.get("time", [])
+ max_temps = daily.get("temperature_2m_max", [])
+
+ today_str = datetime.now().strftime("%Y-%m-%d")
+
+ msg_lines.append(f"\n📊 Open-Meteo 预测")
+ for i, (d, t) in enumerate(zip(dates[:7], max_temps[:7])):
+ day_label = "今天" if d == today_str else d[5:] # MM-DD
+ is_today = "👉 " if d == today_str else " "
+ msg_lines.append(f"{is_today}{day_label}: 最高 {t}{temp_symbol}")
+
+ # METAR 实测
+ if metar:
+ icao = metar.get("icao", "")
+ metar_temp = metar.get("current", {}).get("temp")
+ wind_speed = metar.get("current", {}).get("wind_speed_kt")
+ obs_time = metar.get("observation_time", "")
+
+ # 解析观测时间
+ if obs_time:
+ try:
+ obs_dt = datetime.fromisoformat(obs_time.replace("Z", "+00:00"))
+ obs_time_str = obs_dt.strftime("%H:%M UTC")
+ except:
+ obs_time_str = obs_time[:16] if len(obs_time) > 16 else obs_time
+ else:
+ obs_time_str = "N/A"
+
+ msg_lines.append(f"\n✈️ 机场实测 ({icao})")
+ if metar_temp is not None:
+ msg_lines.append(f" 🌡️ {metar_temp}{temp_symbol}")
+ if wind_speed is not None:
+ msg_lines.append(f" 💨 风速: {wind_speed}kt")
+ msg_lines.append(f" 🕐 观测: {obs_time_str}")
+
+ # 市场信息已根据需求暂时移除
+ # (已在此处删除了之前的市场数据处理逻辑)
+
+ # 发送消息
+ final_msg = "\n".join(msg_lines)
+ if len(final_msg) > 4000:
+ # 消息太长，分段发送
+ bot.send_message(message.chat.id, final_msg[:4000], parse_mode="HTML")
+ bot.send_message(message.chat.id, final_msg[4000:], parse_mode="HTML")
+ else:
+ bot.send_message(message.chat.id, final_msg, parse_mode="HTML")
+
+ except Exception as e:
+ import traceback
+
+ traceback.print_exc()
+ bot.reply_to(message, f"❌ 查询失败: {e}")
+
import logging
+
# 强制关闭 telebot 内部的刷屏日志
telebot.logger.setLevel(logging.CRITICAL)
-
+
while True:
try:
bot.infinity_polling(timeout=60, long_polling_timeout=60)
diff --git a/check_tg.py b/check_tg.py
deleted file mode 100644
index 78377fa0..00000000
--- a/check_tg.py
+++ /dev/null
@@ -1,21 +0,0 @@
-import requests
-import os
-from dotenv import load_dotenv
-
-load_dotenv()
-
-def get_updates():
- token = os.getenv("TELEGRAM_BOT_TOKEN")
- proxy = os.getenv("HTTPS_PROXY")
- proxies = {"http": proxy, "https": proxy} if proxy else None
-
- url = f"https://api.telegram.org/bot{token}/getUpdates"
- try:
- resp = requests.get(url, proxies=proxies)
- data = resp.json()
- print(f"Updates: {data}")
- except Exception as e:
- print(f"Error: {e}")
-
-if __name__ == "__main__":
- get_updates()
diff --git a/main.py b/main.py
index 06b0e272..69378c96 100644
--- a/main.py
+++ b/main.py
@@ -12,9 +12,6 @@ from src.data_collection.polymarket_api import PolymarketClient
from src.data_collection.weather_sources import WeatherDataCollector
from src.data_collection.onchain_tracker import OnchainTracker
from src.models.statistical_model import TemperaturePredictor
-from src.analysis.volume_analyzer import VolumeAnalyzer
-from src.analysis.orderbook_analyzer import OrderbookAnalyzer
-from src.analysis.technical_indicators import TechnicalIndicators
from src.analysis.whale_tracker import WhaleTracker
from src.strategy.decision_engine import DecisionEngine
from src.strategy.risk_manager import RiskManager
@@ -38,7 +35,6 @@ def main():
# 3. 初始化分析与交易组件
predictor = TemperaturePredictor()
risk_manager = RiskManager(config_data.get("config", {}))
- orderbook_analyzer = OrderbookAnalyzer(config_data.get("config", {}))
decision_engine = DecisionEngine(config_data.get("config", {}))
whale_tracker = WhaleTracker(config_data.get("config", {}), onchain)
paper_trader = PaperTrader()
@@ -139,16 +135,18 @@ def main():
active_tid = m.get("active_token_id")
- # 如果是多选一市场（比如 Dallas 76-77°F）
- if len(ts) > 2 and active_tid:
+ # 智能识别买入/买否 Token
+ if active_tid and isinstance(ts, list):
# 获取该档位的买入价 (Ask)
price_requests.append({"token_id": active_tid, "side": "ask"})
- # 获取该档位的买入“否”价所需的 Bid 价
- price_requests.append({"token_id": active_tid, "side": "bid"})
- # 如果是传统的 Yes/No 二选一市场
- elif len(ts) == 2:
- price_requests.append({"token_id": ts[0], "side": "ask"}) # Buy Yes
- price_requests.append({"token_id": ts[1], "side": "ask"}) # Buy No
+
+ if len(ts) == 2:
+ # 传统的二选一，直接获取 No Token 的 Ask
+ no_tid = ts[1] if ts[0] == active_tid else ts[0]
+ price_requests.append({"token_id": no_tid, "side": "ask"})
+ else:
+ # 多选一，需要用 1 - Bid(Yes) 来模拟 Buy No
+ price_requests.append({"token_id": active_tid, "side": "bid"})
if price_requests:
logger.info(f"正在同步 {len(price_requests)} 个档位的真实盘口价格...")
@@ -157,13 +155,13 @@ def main():
# 3. 按城市分组（按condition_id去重）
markets_by_city = {}
- seen_condition_ids = set()
-
+ seen_condition_ids = set() # Initialize seen_condition_ids here
for i, m in enumerate(all_weather_markets):
- c_id = m.get("condition_id")
- if c_id in seen_condition_ids:
- continue # 跳过重复
- seen_condition_ids.add(c_id)
+ # Use condition_id + active_token_id as unique key to support multi-bracket markets
+ unique_market_key = f"{m.get('condition_id')}_{m.get('active_token_id')}"
+ if unique_market_key in seen_condition_ids:
+ continue
+ seen_condition_ids.add(unique_market_key)
# 注入实时批量价格
ts = m.get("tokens", [])
@@ -175,24 +173,24 @@ def main():
active_tid = m.get("active_token_id")
- # 多选一市场逻辑
- if len(ts) > 2 and active_tid:
+ if active_tid and isinstance(ts, list):
m["buy_yes_live"] = token_price_map.get(f"{active_tid}:ask")
- # 买入“否”的价格 = 1 - 该档位的 Bid
- bid_val = token_price_map.get(f"{active_tid}:bid")
- if bid_val:
- m["buy_no_live"] = 1.0 - bid_val
- # 二选一市场逻辑
- elif len(ts) == 2:
- m["buy_yes_live"] = token_price_map.get(f"{ts[0]}:ask")
- m["buy_no_live"] = token_price_map.get(f"{ts[1]}:ask")
+
+ if len(ts) == 2:
+ no_tid = ts[1] if ts[0] == active_tid else ts[0]
+ m["buy_no_live"] = token_price_map.get(f"{no_tid}:ask")
+ else:
+ # 1 - Bid(Yes) = Ask(No)
+ bid_val = token_price_map.get(f"{active_tid}:bid")
+ if bid_val:
+ m["buy_no_live"] = 1.0 - bid_val
# 优先使用发现阶段已经识别出的城市名
city = m.get("city")
- # 如果发现阶段没识别出，再尝试从问题文本提取
+ # 如果发现阶段没识别出，再尝试从问题文本或 Slug 提取
if not city or city == "Unknown":
- full_context = f"{m.get('event_title', '')} {m.get('question', '')}"
+ full_context = f"{m.get('event_title', '')} {m.get('question', '')} {m.get('slug', '')}"
city = weather.extract_city_from_question(full_context)
if i < 5:
@@ -341,34 +339,21 @@ def main():
# 严格触发条件: 价格必须处于 85-95¢ 区间 (真正的高概率信号)
yes_in_range = buy_yes_price and 0.85 <= buy_yes_price <= 0.95
no_in_range = buy_no_price and 0.85 <= buy_no_price <= 0.95
-
+
# 50¢ 保护：价格接近 50% 说明市场无明确方向，跳过
is_undecided = 0.45 <= current_prob <= 0.55
-
+
if (yes_in_range or no_in_range) and not is_undecided:
alert_key = f"alert_{market_id}_{int(current_prob * 100)}"
if alert_key not in pushed_signals:
- # 深度分析订单簿
- ob_data = (
- polymarket.get_orderbook(active_tid)
- if active_tid
- else None
+ # 获取温度符号（在此处定义以便后续使用）
+ temp_unit = weather_data.get("open-meteo", {}).get(
+ "unit", "celsius"
)
- ob_analysis = (
- orderbook_analyzer.analyze(ob_data)
- if ob_data
- else {
- "tradeable": False,
- "liquidity": "枯竭",
- "spread": 0,
- "mid_price": current_prob,
- }
+ temp_symbol = (
+ "°F" if temp_unit == "fahrenheit" else "°C"
)
- # 获取温度符号（在此处定义以便后续使用）
- temp_unit = weather_data.get("open-meteo", {}).get("unit", "celsius")
- temp_symbol = "°F" if temp_unit == "fahrenheit" else "°C"
-
# 预测偏差分析
if ref_temp:
city_pred_high = ref_temp # 记录到城市概览
@@ -391,7 +376,6 @@ def main():
f"预测温度{ref_temp}{temp_symbol}落在{question}区间，市场与模型一致"
)
-
# 模拟下单 - 使用 Ask 价格（实际可成交价格）
if buy_yes_price and buy_yes_price > 0.5:
trigger_side = "Buy Yes"
@@ -405,10 +389,14 @@ def main():
)
# 构建预测文本
- forecast_text = f"{ref_temp}{temp_symbol}" if ref_temp else "N/A"
-
+ forecast_text = (
+ f"{ref_temp}{temp_symbol}" if ref_temp else "N/A"
+ )
+
# 构建简约版消息
- side_display = "Buy No" if trigger_side == "Buy No" else "Buy Yes"
+ side_display = (
+ "Buy No" if trigger_side == "Buy No" else "Buy Yes"
+ )
msg = f"⚡ {question} ({target_date}): {side_display} {trigger_price}¢ | 预测:{forecast_text}"
success = paper_trader.open_position(
@@ -421,7 +409,7 @@ def main():
target_date=target_date,
predicted_temp=ref_temp,
)
-
+
# 添加模拟交易标签
if success:
msg += " [🛒 $5.0 💡试探]"
@@ -534,10 +522,8 @@ def main():
if is_categorical:
# 语义转换逻辑保持一致
if buy_no_price and buy_no_price >= 0.85:
- trigger_side = "Sell Yes"
- trigger_price = int(
- buy_no_price * 100
- ) # 预估价
+ trigger_side = "Buy No" # 直接统一为 Buy No
+ trigger_price = int(buy_no_price * 100)
else:
trigger_side = "Buy Yes"
trigger_price = int(buy_yes_price * 100)
@@ -551,84 +537,6 @@ def main():
else int(buy_no_price * 100)
)
- # --- 深度流动性与 Spread 检查 ---
- target_tid = (
- active_tid
- if is_categorical
- else (ts[0] if trigger_side == "Buy Yes" else ts[1])
- )
- ob_data = (
- polymarket.get_orderbook(target_tid)
- if target_tid
- else None
- )
-
- ob_analysis = {
- "tradeable": True,
- "liquidity": "未知",
- "spread": 0,
- "mid_price": trigger_price / 100,
- }
- if ob_data:
- ob_analysis = orderbook_analyzer.analyze(ob_data)
-
- if not ob_analysis.get("tradeable", True):
- confidence_tag = (
- f"🔴不可交易 ({ob_analysis.get('liquidity')})"
- )
- if not is_categorical:
- logger.warning(
- f"跳过不可交易信号 (Spread {ob_analysis.get('spread')}): {city} {question}"
- )
- continue
-
- # 更新实时数据显示
- mid_c = round(ob_analysis.get("mid_price", 0) * 100, 1)
- spr_c = round(ob_analysis.get("spread", 0) * 100, 1)
- depth = ob_analysis.get(
- "ask_depth"
- if trigger_side.startswith("Buy")
- else "bid_depth",
- 0,
- )
-
- # 流动性图标
- liq_map = {
- "充裕": "✅ 充裕",
- "正常": "🟡 正常",
- "稀薄": "🟠 稀薄",
- "枯竭": "🔴 枯竭",
- }
- liq_status = liq_map.get(
- ob_analysis.get("liquidity", "未知"), "❓ 未知"
- )
-
- if is_categorical:
- ask_str = (
- "--"
- if trigger_side == "Sell Yes"
- else f"{trigger_price}¢"
- )
- bid_str = (
- f"{trigger_price}¢"
- if trigger_side == "Sell Yes"
- else "--"
- )
-
- display_side = (
- f"📊 {question}\n"
- f"Ask: {ask_str} | Bid: {bid_str} | Mid: {mid_c}¢\n"
- f"Spread: {spr_c}¢ | 深度: ${depth}\n"
- f"流动性: {liq_status}"
- )
- else:
- display_side = (
- f"📊 {question}\n"
- f"报价: {trigger_side} {trigger_price}¢ | Mid: {mid_c}¢\n"
- f"Spread: {spr_c}¢ | 深度: ${depth}\n"
- f"流动性: {liq_status}"
- )
-
# --- 智能动态仓位计算 ---
# 1. 获取 Open-Meteo 对目标日期的最高温预测
predicted_high = None
@@ -745,11 +653,10 @@ def main():
elif trigger_price >= 92:
base_pos, confidence_tag = 5.0, "📌价格锁定"
- # 4. 四层过滤决策
+ # 4. 仓位决策
amount_usd, risk_reason = (
risk_manager.calculate_position_size(
base_confidence_usd=base_pos,
- depth=depth,
hours_to_settle=hours_to_settle,
is_high_relative_volume=is_rel_high_vol,
)
@@ -758,7 +665,7 @@ def main():
logger.info(
f"【Pro仓位】{city} {question} | "
f"基础:{base_pos}$ -> 最终:{amount_usd}$ | 原因:{risk_reason} | "
- f"深度:${depth} | 剩:{hours_to_settle:.1f}h"
+ f"剩:{hours_to_settle:.1f}h"
)
# --- 模拟交易触发逻辑 ---
@@ -798,9 +705,7 @@ def main():
)
# 构建简约版消息: ⚡ {question} ({date}): {side} {price}¢ | 预测:{forecast} [🛒 ${amount} {tag}]
- side_display = (
- "Buy No" if trigger_side == "Buy No" else "Buy Yes"
- )
+ side_display = trigger_side
msg = (
f"⚡ {question} ({target_date}): {side_display} {trigger_price}¢ | "
f"预测:{forecast_text} [🛒 ${amount_usd} {confidence_tag}]"
@@ -825,17 +730,28 @@ def main():
if city_alerts:
# 去重策略建议
unique_tips = list(dict.fromkeys(city_strategy_tips))
- notifier.send_combined_alert(
- city=city,
- alerts=city_alerts,
- local_time=city_local_time,
- forecast_temp=f"{city_pred_high}{temp_symbol}"
- if city_pred_high
- else "N/A",
- total_volume=city_total_vol,
- brackets_count=len(city_markets),
- strategy_tips=unique_tips,
+ # 获取 METAR 数据（仅当天结算的市场才显示）
+ today_str = datetime.now().strftime("%Y-%m-%d")
+ # 检查是否有当天结算的市场
+ has_today_market = any(
+ a.get("market") == today_str or a.get("market") == "今日"
+ for a in city_alerts
)
+ metar_data = (
+ weather_data.get("metar") if has_today_market else None
+ )
+ # notifier.send_combined_alert(
+ # city=city,
+ # alerts=city_alerts,
+ # local_time=city_local_time,
+ # forecast_temp=f"{city_pred_high}{temp_symbol}"
+ # if city_pred_high
+ # else "N/A",
+ # total_volume=city_total_vol,
+ # brackets_count=len(city_markets),
+ # strategy_tips=unique_tips,
+ # metar_data=metar_data,
+ # )
except Exception as e:
logger.error(f"分析城市 {city} 时出错: {e}")
@@ -844,13 +760,17 @@ def main():
# --- 周期性结算：保存高价值信号 ---
active_signals = []
for mid, entry in all_markets_cache.items():
- # 核心过滤：只有 ACTIVE 且 价格未锁定、日期未过期的才进入 signals 列表
- if entry.get("rationale") not in ["ENDED", "EXPIRED", "ERROR"]:
- # 再次双重检查日期 (硬核拦截 2026-02-06)
- target_dt = entry.get("target_date")
- if target_dt and target_dt < "2026-02-06":
- continue
- active_signals.append(entry)
+ # Relaxed filtering: Let the bot decide, but mark ENDED
+ rationale = entry.get("rationale")
+ if rationale == "ERROR":
+ continue
+
+ target_dt = entry.get("target_date")
+ # Only filter out truly ancient history
+ if target_dt and target_dt < "2026-02-01":
+ continue
+
+ active_signals.append(entry)
# 按分数排序
active_signals.sort(key=lambda x: x.get("score", 0), reverse=True)
@@ -926,7 +846,7 @@ def main():
report.append(
f"📈 累计浮动盈亏: {total_pnl:+.2f}$"
)
- notifier._send_message("\n".join(report))
+ # notifier._send_message("\n".join(report))
pushed_signals[summary_key] = time.time()
except Exception as e:
diff --git a/requirements.txt b/requirements.txt
index 0458e24f..904e0af6 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -4,5 +4,4 @@ pyTelegramBotAPI
python-dotenv
pytz
numpy
-py-clob-client
web3
diff --git a/src/data_collection/polymarket_api.py b/src/data_collection/polymarket_api.py
index f4ff209a..d186a27f 100644
--- a/src/data_collection/polymarket_api.py
+++ b/src/data_collection/polymarket_api.py
@@ -7,587 +7,285 @@ from loguru import logger
from datetime import datetime
from concurrent.futures import ThreadPoolExecutor
-from py_clob_client.client import ClobClient
-from py_clob_client.constants import POLYGON
-from py_clob_client.clob_types import ApiCreds, BookParams, OpenOrderParams
-
-
class PolymarketClient:
"""
- Polymarket API Client for market data and trading (Exclusive py-clob-client mode)
+ Polymarket API Client (Pure REST API version)
+ Directly uses Gamma API and CLOB REST API without py-clob-client dependency.
"""
def __init__(self, config: Dict):
- self.base_url = config.get("base_url", "https://clob.polymarket.com")
+ self.clob_url = config.get("base_url", "https://clob.polymarket.com")
+ self.gamma_url = "https://gamma-api.polymarket.com"
self.timeout = config.get("timeout", 20)
self.session = requests.Session()
- # 缓存机制
+ # Cache mechanism
self._weather_markets_cache = []
self._last_discovery_time = 0
- self._cache_ttl = 300 # 5 分钟缓存
+ self._cache_ttl = 300 # 5 minutes cache
- # 统一代理设置
+ # Proxy settings (automatically read from environment)
proxy = os.getenv("HTTPS_PROXY") or os.getenv("HTTP_PROXY")
if proxy:
self.session.proxies = {"http": proxy, "https": proxy}
- logger.info(f"正在使用代理: {proxy}")
+ logger.info(f"Requests session using proxy: {proxy}")
- # 设置公开接口通用的 User-Agent
+ # Set common User-Agent and headers
self.session.headers.update(
{
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36",
"Accept": "application/json",
+ "Content-Type": "application/json"
}
)
- # 初始化官方 CLOB 客户端
self.api_key = config.get("api_key")
- self.api_secret = config.get("api_secret")
- self.api_passphrase = config.get("api_passphrase")
-
- try:
-
- # 组装凭据对象 (如果提供)
- creds = None
- if self.api_key and self.api_secret:
- creds = ApiCreds(
- api_key=self.api_key,
- api_secret=self.api_secret,
- api_passphrase=self.api_passphrase
- )
-
- self.clob_client = ClobClient(
- host=self.base_url,
- key=None, # 除非有 0x 开头的私钥，否则传入 None 以避免报错
- creds=creds,
- chain_id=POLYGON
- )
- # 注入代理到官方客户端 (官方库使用 httpx 或 requests)
- if proxy:
- # 尝试给官方 client 的内部 session 设置代理 (取决于版本实现)
- try:
- if hasattr(self.clob_client, 'session'):
- self.clob_client.session.proxies = {"http": proxy, "https": proxy}
- except: pass
-
- logger.info("✅ 官方 py-clob-client 已满血上线，Requests 模式已彻底退役。")
- except Exception as e:
- logger.error(f"官方客户端启动失败: {e}")
- raise RuntimeError("必须安装并配置正确的 py-clob-client 才能运行。")
-
- self._setup_headers()
- logger.info(f"Polymarket 客户端初始化完成。Base URL: {self.base_url}")
-
- def _setup_headers(self):
- """Setup default headers for API requests"""
- self.session.headers.update(
- {"Content-Type": "application/json", "Accept": "application/json"}
- )
if self.api_key:
self.session.headers.update({"POLY_API_KEY": self.api_key})
+ logger.info(f"Polymarket REST Client initialized. CLOB: {self.clob_url}, Gamma: {self.gamma_url}")
+
def get_markets(self, next_cursor: str = None) -> Optional[Dict]:
- """
- 获取全量市场列表 (官方接口)
- """
+ """Fetch markets list via CLOB REST API"""
try:
- return self.clob_client.get_markets(next_cursor=next_cursor)
- except: return None
+ params = {}
+ if next_cursor:
+ params["next_cursor"] = next_cursor
+ resp = self.session.get(f"{self.clob_url}/markets", params=params, timeout=self.timeout)
+ return resp.json() if resp.status_code == 200 else None
+ except Exception as e:
+ logger.debug(f"get_markets failed: {e}")
+ return None
def get_market(self, market_id: str) -> Optional[Dict]:
- """
- 获取特定市场详情 (官方接口)
- """
+ """Fetch market details via CLOB REST API"""
try:
- return self.clob_client.get_market(market_id=market_id)
- except: return None
+ resp = self.session.get(f"{self.clob_url}/markets/{market_id}", timeout=self.timeout)
+ return resp.json() if resp.status_code == 200 else None
+ except Exception as e:
+ logger.debug(f"get_market failed: {e}")
+ return None
def get_price(self, token_id: str, side: str = "ask") -> Optional[float]:
- """
- 获取 Token 的实时盘口价格
- 优先使用官方库，失败时使用直接 REST API
- """
- # 方法1: 尝试官方库
+ """Fetch real-time price for a token via CLOB REST API"""
try:
- sdk_side = "BUY" if side == "ask" else "SELL"
- price_str = self.clob_client.get_price(token_id=token_id, side=sdk_side)
- if price_str:
- return float(price_str)
- except Exception as e:
- logger.debug(f"官方库 get_price 失败 ({token_id}): {e}")
-
- # 方法2: 直接调用 REST API (与 test_price.py 一致)
- try:
- resp = self.session.get(f"{self.base_url}/price", params={
- "token_id": token_id,
- "side": side.upper()
- }, timeout=10)
+ # Correct CLOB Mapping:
+ # 'sell' side price is the ASK (price you pay to BUY)
+ # 'buy' side price is the BID (price you get to SELL)
+ clob_side = "sell" if side.lower() in ["ask", "buy"] else "buy"
+ resp = self.session.get(
+ f"{self.clob_url}/price",
+ params={"token_id": token_id, "side": clob_side},
+ timeout=10
+ )
data = resp.json()
- return float(data.get("price", 0))
+ return float(data.get("price", 0)) if resp.status_code == 200 else None
except Exception as e:
- logger.debug(f"REST API get_price 失败 ({token_id}): {e}")
+ logger.debug(f"get_price failed ({token_id}): {e}")
return None
def get_orderbook(self, token_id: str) -> Optional[Dict]:
- """
- 获取订单簿深度
- 优先使用官方库，失败时使用直接 REST API
- """
- # 方法1: 尝试官方库
+ """Fetch orderbook for a token via CLOB REST API"""
try:
- return self.clob_client.get_orderbook(token_id=token_id)
+ resp = self.session.get(
+ f"{self.clob_url}/book", params={"token_id": token_id}, timeout=10
+ )
+ return resp.json() if resp.status_code == 200 else None
except Exception as e:
- logger.debug(f"官方库 get_orderbook 失败 ({token_id}): {e}")
-
- # 方法2: 直接调用 REST API (与 test_price.py 一致)
- try:
- resp = self.session.get(f"{self.base_url}/book", params={
- "token_id": token_id
- }, timeout=10)
- return resp.json()
- except Exception as e:
- logger.debug(f"REST API get_orderbook 失败 ({token_id}): {e}")
+ logger.debug(f"get_orderbook failed ({token_id}): {e}")
return None
-
def get_buy_prices(self, yes_token_id: str, no_token_id: str) -> Optional[Dict]:
- """
- 获取买入价格 (Buy Yes 和 Buy No)
-
- Args:
- yes_token_id: Yes token ID
- no_token_id: No token ID
-
- Returns:
- dict: {"buy_yes": float, "buy_no": float} 或 None
- """
+ """Fetch buy prices for both YES and NO tokens"""
try:
- # Buy Yes = Yes token 的最佳卖单 (asks)
- yes_book = self.get_orderbook(yes_token_id)
- buy_yes = None
- if (
- yes_book
- and isinstance(yes_book, dict)
- and yes_book.get("asks")
- and len(yes_book["asks"]) > 0
- ):
- buy_yes = float(yes_book["asks"][0].get("price", 0))
-
- # Buy No = No token 的最佳卖单 (asks)
- no_book = self.get_orderbook(no_token_id)
- buy_no = None
- if (
- no_book
- and isinstance(no_book, dict)
- and no_book.get("asks")
- and len(no_book["asks"]) > 0
- ):
- buy_no = float(no_book["asks"][0].get("price", 0))
+ # Buy Yes = Ask price of YES token
+ buy_yes = self.get_price(yes_token_id, "BUY")
+ # Buy No = Ask price of NO token
+ buy_no = self.get_price(no_token_id, "BUY")
if buy_yes is not None and buy_no is not None:
return {"buy_yes": buy_yes, "buy_no": buy_no}
-
except Exception as e:
- logger.debug(f"获取买入价格失败: {e}")
-
+ logger.debug(f"get_buy_prices failed: {e}")
return None
def get_multiple_prices(self, token_requests: List[Dict]) -> Dict[str, float]:
- """
- 批量获取多个 token 的价格
- 优先使用官方库，失败时使用直接 REST API
- """
+ """Batch fetch prices for multiple tokens using ThreadPoolExecutor"""
if not token_requests:
return {}
all_prices = {}
- batch_size = 20
def robust_float(val):
- if isinstance(val, (int, float)): return float(val)
- if isinstance(val, str):
- try: return float(val)
- except: return 0.0
- return 0.0
+ try: return float(val)
+ except: return 0.0
- chunks = [token_requests[i : i + batch_size] for i in range(0, len(token_requests), batch_size)]
-
- def fetch_chunk_sdk(chunk):
- """使用官方 SDK 批量获取"""
- try:
- batch_req = []
- for r in chunk:
- sdk_side = "BUY" if r.get("side") == "ask" else "SELL"
- batch_req.append(BookParams(token_id=r["token_id"], side=sdk_side))
-
- results = self.clob_client.get_prices(batch_req)
-
- chunk_prices = {}
- if isinstance(results, list):
- for item in results:
- tid = item.get("token_id")
- price_raw = item.get("price")
- res_side = item.get("side")
- if tid and price_raw:
- val = robust_float(price_raw)
- key_side = "ask" if res_side == "BUY" else "bid"
- chunk_prices[f"{tid}:{key_side}"] = val
- return chunk_prices
- except Exception as e:
- logger.debug(f"SDK batch fetch failed: {e}")
- return None
-
- def fetch_chunk_rest(chunk):
- """使用 REST API 逐个获取 (备用方案)"""
- chunk_prices = {}
- for r in chunk:
- try:
- resp = self.session.get(f"{self.base_url}/price", params={
- "token_id": r["token_id"],
- "side": r.get("side", "ask").upper()
- }, timeout=10)
- data = resp.json()
- price = robust_float(data.get("price", 0))
- if price > 0:
- chunk_prices[f"{r['token_id']}:{r.get('side', 'ask')}"] = price
- except Exception as e:
- logger.debug(f"REST API price fetch failed for {r['token_id'][:16]}...: {e}")
- return chunk_prices
+ def fetch_single(req):
+ tid = req["token_id"]
+ side = req.get("side", "ask").lower()
+ # To get ASK (price to buy), request 'sell' side
+ # To get BID (price to sell), request 'buy' side
+ api_side = "sell" if side == "ask" else "buy"
+ val = self.get_price(tid, api_side)
+ if val:
+ return f"{tid}:{side.lower()}", val
+ return None
- # 使用线程池并发抓取
- with ThreadPoolExecutor(max_workers=3) as executor:
- future_results = list(executor.map(fetch_chunk_sdk, chunks))
-
- # 检查结果，如果 SDK 全部失败，使用 REST API 备用
- sdk_success = False
- for chunk_result in future_results:
- if chunk_result:
- all_prices.update(chunk_result)
- sdk_success = True
-
- # 如果 SDK 完全失败，使用 REST API
- if not sdk_success and token_requests:
- logger.info("SDK 批量获取失败，使用 REST API 逐个获取...")
- with ThreadPoolExecutor(max_workers=5) as executor:
- future_results = list(executor.map(fetch_chunk_rest, chunks))
- for chunk_result in future_results:
- all_prices.update(chunk_result)
-
+ with ThreadPoolExecutor(max_workers=5) as executor:
+ results = list(executor.map(fetch_single, token_requests))
+
+ for res in results:
+ if res:
+ key, val = res
+ all_prices[key] = val
+
return all_prices
-
def get_midpoint(self, token_id: str) -> Optional[float]:
- """
- 获取中点价格 (官方接口)
- """
+ """Fetch midpoint price via CLOB REST API"""
try:
- res = self.clob_client.get_midpoint(token_id)
- if res and "mid" in res:
- return float(res["mid"])
- except: pass
- return None
-
- def search_markets(self, query: str) -> Optional[Dict]:
- """
- 搜索市场
- """
- try:
- # Note: The py-clob-client's get_markets method does not directly support a 'query' parameter for searching.
- # It primarily supports pagination (next_cursor).
- # This implementation will fetch the first page of markets and return them.
- # A more robust search would involve fetching all markets and filtering locally,
- # or using a different API endpoint if available.
- return self.clob_client.get_markets(next_cursor=None)
- except Exception as e:
- logger.error(f"搜索市场失败: {e}")
- return None
-
- # --- 交易指令 (强依赖官方库) ---
- def create_order(
- self,
- token_id: str,
- side: str,
- price: float,
- size: float,
- order_type: str = "GTC",
- ) -> Optional[Dict]:
- """
- 创建新订单
- """
- try:
- # 转换方向
- side_val = "BUY" if side.upper() == "BUY" else "SELL"
- # 使用官方签名下单 (SDK 会自动处理签名)
- return self.clob_client.create_order(
- token_id=token_id,
- price=price,
- size=size,
- side=side_val
- )
- except Exception as e:
- logger.error(f"下单失败: {e}")
- return None
-
- def cancel_order(self, order_id: str) -> Optional[Dict]:
- """
- 取消订单
- """
- try:
- return self.clob_client.cancel_order(order_id)
- except Exception as e:
- logger.error(f"取消订单失败: {e}")
- return None
-
- def get_orders(self, market_id: str = None) -> Optional[Dict]:
- """
- 获取当前活跃挂单
- """
- try:
- params = OpenOrderParams(market=market_id) if market_id else None
- return self.clob_client.get_orders(params=params)
- except Exception as e:
- logger.error(f"获取挂单失败: {e}")
+ resp = self.session.get(f"{self.clob_url}/midpoint", params={"token_id": token_id}, timeout=10)
+ data = resp.json()
+ return float(data.get("mid", 0)) if resp.status_code == 200 else None
+ except:
return None
def discover_weather_markets(self) -> list:
- """
- 通过全量扫描活跃事件发现最高温天气市场 (支持缓存机制)
- """
- # 缓存检查
+ """Scan Gamma API for all weather-related markets with prioritized search and city targeting"""
+ # Cache check
current_time = time.time()
if self._weather_markets_cache and (current_time - self._last_discovery_time < self._cache_ttl):
- logger.debug(f"使用缓存的市场列表 (剩余寿命: {int(self._cache_ttl - (current_time - self._last_discovery_time))}s)")
+ logger.debug(f"Using cached market list ({len(self._weather_markets_cache)} items)")
return self._weather_markets_cache
- logger.info("📡 正在全量扫描 Polymarket 发现天气市场...")
- gamma_url = "https://gamma-api.polymarket.com/events"
+ logger.info("📡 Scanning Polymarket via Gamma API for weather markets...")
all_weather_markets = []
- seen_condition_ids = set()
-
- def process_events(events, source_label):
- if not isinstance(events, list):
- return
-
- new_markets_count = 0
- for event in events:
- title = event.get("title", "")
- is_weather_event = (
- "Highest temperature" in title or "temperature in" in title.lower()
- )
-
- event_slug = event.get("slug", "")
- for m in event.get("markets", []):
- question = m.get("groupItemTitle") or m.get("question") or ""
-
- # 强化过滤：必须在标题中包含明确的气温气象词，且排除非气温市场
- t_lower = title.lower()
- q_lower = question.lower()
-
- # 1. 标题必须像个气温市场
- if not any(k in t_lower for k in ["highest temperature", "high temperature", "will temperature", "daily temperature"]):
- continue
-
- # 2. 排除干扰项
- if "climate" in t_lower or "rain" in t_lower or "snow" in t_lower:
- continue
-
- # 3. 确保这个具体的 market (bracket) 是我们想要的
- if not any(k in q_lower for k in ["temperature", "be", "highest", "range"]):
- # 补充：如果是多选一市场的子项，question 可能只是一个数字或范围，此时看 title
- if not any(k in t_lower for k in ["temperature", "highest"]):
- continue
-
- c_id = m.get("conditionId")
- # 识别 outcome_index
- t_ids = m.get("clobTokenIds", [])
- active_id = m.get("activeTokenId")
- idx = 0
- if isinstance(t_ids, list) and active_id in t_ids:
- idx = t_ids.index(active_id)
-
- # 对于多选一市场，不同档位共享 conditionId，但 tokenId 不同
- unique_key = f"{c_id}_{active_id}"
- if c_id and unique_key not in seen_condition_ids:
- all_weather_markets.append(
- {
- "condition_id": c_id,
- "question": question,
- "active_token_id": active_id,
- "outcome_index": idx,
- "tokens": t_ids,
- "prices": m.get("outcomePrices"),
- "event_title": title,
- "slug": event_slug,
- }
- )
- seen_condition_ids.add(unique_key)
- new_markets_count += 1
- if new_markets_count > 0:
- logger.debug(f"[{source_label}] 发现 {new_markets_count} 个新市场合约")
-
+ seen_keys = set()
+
+ # 1. Target newest markets by query and ID sorting
+ search_queries = ["highest temperature", "temperature in", "daily weather"]
+
try:
- # 1. 扫描活跃且未合并的 (全量)
- for offset in range(0, 20000, 1000):
- params = {
- "active": "true",
- "closed": "false",
- "limit": 1000,
- "offset": offset,
- }
-
- # 增加重试机制
- success = False
- for retry in range(3):
- try:
- response = self.session.get(
- gamma_url, params=params, timeout=self.timeout
- )
- if response.status_code == 200:
- events = response.json()
- if not events:
- break
- process_events(events, f"Open-O{offset}")
- success = True
- break
- else:
- logger.warning(f"Gamma API 状态码异常 ({response.status_code})，第 {retry+1} 次重试...")
- except Exception as e:
- logger.warning(f"发现市场请求出错: {e}，第 {retry+1} 次重试...")
- time.sleep(2)
-
- if not success:
- break
+ # Use multiple offsets to find more historical/diverse markets
+ for offset in [0, 500, 1000]:
+ for query in search_queries:
+ logger.debug(f"Searching with query: {query} (offset {offset})")
+ params = {
+ "query": query,
+ "active": "true",
+ "limit": 500,
+ "offset": offset,
+ "order": "id",
+ "ascending": "false"
+ }
+ resp = self.session.get(f"{self.gamma_url}/markets", params=params, timeout=self.timeout)
+ if resp.status_code == 200:
+ markets = resp.json()
+ logger.debug(f"Query '{query}' returned {len(markets)} markets")
+ for m in markets:
+ q = m.get("question", "").lower()
+ slug = m.get("slug", "").lower()
+
+ # Filter for weather markets (Broadened)
+ is_weather = any(k in q or k in slug for k in [
+ "highest temperature", "highest-temperature",
+ "temperature in", "temperature-in",
+ "daily weather", "daily-weather",
+ "weather", "气温", "温度"
+ ])
+ if is_weather:
+ c_id = m.get("conditionId")
+ t_ids = m.get("clobTokenIds")
+ active_id = m.get("activeTokenId")
+
+ # Robust JSON parsing for clobTokenIds string
+ if isinstance(t_ids, str) and t_ids.startswith("["):
+ try:
+ import json
+ t_ids = json.loads(t_ids)
+ except:
+ pass
+
+ # For Neg Risk markets, activeTokenId might be missing in list view
+ # If we have clobTokenIds, we can work with it
+ if not t_ids:
+ continue
+
+ if not active_id and isinstance(t_ids, list) and len(t_ids) > 0:
+ active_id = t_ids[0] # Assume first is YES
- # 2. 扫描活跃但已关闭的
- for offset in range(0, 20000, 1000):
- params = {
- "active": "true",
- "closed": "true",
- "limit": 1000,
- "offset": offset,
- }
-
- success = False
- for retry in range(3):
- try:
- response = self.session.get(
- gamma_url, params=params, timeout=self.timeout
- )
- if response.status_code == 200:
- events = response.json()
- if not events:
- break
- process_events(events, f"Closed-O{offset}")
- success = True
- break
- except Exception as e:
- logger.warning(f"发现关闭市场请求出错: {e}，第 {retry+1} 次重试...")
- time.sleep(2)
-
- if not success:
- break
-
- # 3. 扫描非活跃但未关闭的市场
- for offset in range(0, 10000, 1000):
- params = {
- "active": "false",
- "closed": "false",
- "limit": 1000,
- "offset": offset,
- }
- response = self.session.get(
- gamma_url, params=params, timeout=self.timeout
- )
- if response.status_code == 200:
- events = response.json()
- if not events:
- break
- process_events(events, f"Inactive-O{offset}")
+ if not active_id:
+ continue
+
+ unique_key = f"{c_id}_{active_id}"
+ if unique_key not in seen_keys:
+ logger.debug(f"Found weather segment: {q}")
+ all_weather_markets.append({
+ "condition_id": c_id,
+ "question": m.get("question"),
+ "active_token_id": active_id,
+ "outcome_index": t_ids.index(active_id) if isinstance(t_ids, list) and active_id in t_ids else 0,
+ "tokens": t_ids,
+ "prices": m.get("outcomePrices"),
+ "event_title": m.get("description", "")[:100],
+ "slug": m.get("slug"),
+ "group_id": m.get("negRiskMarketID")
+ })
+ seen_keys.add(unique_key)
else:
+ logger.debug(f"Query '{query}' failed with status {resp.status_code}")
+
+ if len(all_weather_markets) > 50:
break
- # 4. 扫描非活跃且已关闭的市场（某些即将结算的市场可能在这里）
- for offset in range(0, 10000, 1000):
- params = {
- "active": "false",
- "closed": "true",
- "limit": 1000,
- "offset": offset,
- }
- response = self.session.get(
- gamma_url, params=params, timeout=self.timeout
- )
- if response.status_code == 200:
- events = response.json()
- if not events:
- break
- process_events(events, f"InactiveClosed-O{offset}")
- else:
- break
-
- logger.info(
- f"全量发现结束，共获取 {len(all_weather_markets)} 个天气档位合约"
- )
-
- # 更新缓存
+ logger.info(f"Discovery complete: Found {len(all_weather_markets)} weather segments.")
self._weather_markets_cache = all_weather_markets
self._last_discovery_time = current_time
-
return all_weather_markets
except Exception as e:
- logger.error(f"全量发现天气市场失败: {e}")
+ logger.error(f"Market discovery failed: {e}")
+ return []
+
+ except Exception as e:
+ logger.error(f"Market discovery failed: {e}")
+ return []
+
+ except Exception as e:
+ logger.error(f"Market discovery failed: {e}")
return []
def get_weather_markets(self) -> list:
- """
- 获取全量活跃天气市场
- """
return self.discover_weather_markets()
- def get_event_by_slug(self, slug: str) -> Optional[Dict]:
- """
- 通过slug直接获取特定事件（用于捕获部分结算等特殊状态的市场）
- """
- try:
- url = f"{self.base_url.replace('clob', 'gamma-api')}/events"
- params = {"slug": slug}
- response = self.session.get(url, params=params, timeout=self.timeout)
-
- if response.status_code == 200:
- events = response.json()
- if events and len(events) > 0:
- return events[0]
- except Exception as e:
- logger.debug(f"通过slug获取事件失败 ({slug}): {e}")
- return None
-
def find_weather_market(self, city: str, date_str: str = None) -> Optional[Dict]:
- """
- 根据城市和日期精准查找
- """
- weather_markets = self.get_weather_markets()
- for m in weather_markets:
- content = (
- str(m.get("question", "")) + str(m.get("event_title", ""))
- ).lower()
+ markets = self.get_weather_markets()
+ for m in markets:
+ # Match against question, title AND slug
+ content = (str(m.get("question", "")) + str(m.get("event_title", "")) + str(m.get("slug", ""))).lower()
if city.lower() in content:
if date_str:
- if date_str.lower() in content:
- return m
+ if date_str.lower() in content: return m
else:
return m
return None
def get_weather_event_markets(self, city: str) -> list:
- """
- 获取某个城市相关的所有区间市场
- """
all_markets = self.get_weather_markets()
return [
- m
- for m in all_markets
- if city.lower()
- in (str(m.get("question", "")) + str(m.get("event_title", ""))).lower()
+ m for m in all_markets
+ if city.lower() in (str(m.get("question", "")) + str(m.get("event_title", "")) + str(m.get("slug", ""))).lower()
]
+
+ # --- Trading Stubs (Real trading requires signing, which is disabled in pure REST mode) ---
+ def create_order(self, *args, **kwargs) -> Optional[Dict]:
+ logger.warning("create_order: Real trading is disabled in pure REST mode. Please use paper trading.")
+ return None
+
+ def cancel_order(self, *args, **kwargs) -> Optional[Dict]:
+ logger.warning("cancel_order: Real trading is disabled in pure REST mode.")
+ return None
+
+ def get_orders(self, *args, **kwargs) -> Optional[Dict]:
+ logger.warning("get_orders: Real trading is disabled in pure REST mode.")
+ return None
diff --git a/src/data_collection/weather_sources.py b/src/data_collection/weather_sources.py
index c6432302..1bfc8fac 100644
--- a/src/data_collection/weather_sources.py
+++ b/src/data_collection/weather_sources.py
@@ -13,8 +13,27 @@ class WeatherDataCollector:
- OpenWeatherMap (free, fast updates)
- Weather Underground (Polymarket settlement source)
- Visual Crossing (rich historical data)
+ - NOAA Aviation Weather (METAR - airport observations)
"""
+ # Polymarket 12 个天气市场对应的 ICAO 机场代码
+ # 这些是 Weather Underground 结算源使用的气象站
+ CITY_TO_ICAO = {
+ "seattle": "KSEA", # Seattle-Tacoma Airport
+ "london": "EGLC", # London City Airport
+ "dallas": "KDAL", # Dallas Love Field
+ "miami": "KMIA", # Miami International
+ "atlanta": "KATL", # Hartsfield-Jackson
+ "chicago": "KORD", # O'Hare International
+ "new york": "KLGA", # LaGuardia Airport
+ "nyc": "KLGA", # Alias
+ "seoul": "RKSI", # Incheon International
+ "ankara": "LTAC", # Esenboğa International
+ "toronto": "CYYZ", # Toronto Pearson
+ "wellington": "NZWN", # Wellington International
+ "buenos aires": "SAEZ", # Ezeiza International
+ }
+
def __init__(self, config: dict):
self.config = config
self.wunderground_key = config.get("wunderground_api_key")
@@ -167,6 +186,113 @@ class WeatherDataCollector:
logger.error(f"Visual Crossing request failed: {e}")
return None
+ def get_icao_code(self, city: str) -> Optional[str]:
+ """
+ 根据城市名获取对应的 ICAO 机场代码
+ """
+ normalized = city.lower().strip()
+
+ # 直接匹配
+ if normalized in self.CITY_TO_ICAO:
+ return self.CITY_TO_ICAO[normalized]
+
+ # 模糊匹配
+ for key, icao in self.CITY_TO_ICAO.items():
+ if key in normalized or normalized in key:
+ return icao
+
+ return None
+
+ def fetch_metar(self, city: str, use_fahrenheit: bool = False) -> Optional[Dict]:
+ """
+ 从 NOAA Aviation Weather Center 获取 METAR 航空气象数据
+
+ 这是 Polymarket 天气市场的结算数据源 (Weather Underground) 使用的相同气象站
+
+ Args:
+ city: 城市名称
+ use_fahrenheit: 是否转换为华氏度
+
+ Returns:
+ dict: METAR 数据，包含温度、露点、风速等
+ """
+ icao = self.get_icao_code(city)
+ if not icao:
+ logger.warning(f"未找到城市 {city} 对应的 ICAO 代码")
+ return None
+
+ try:
+ # NOAA Aviation Weather API (免费，无需 Key)
+ url = "https://aviationweather.gov/api/data/metar"
+ params = {
+ "ids": icao,
+ "format": "json",
+ "hours": 3, # 获取最近3小时的观测
+ }
+
+ response = self.session.get(url, params=params, timeout=self.timeout)
+ response.raise_for_status()
+
+ data = response.json()
+ if not data:
+ logger.warning(f"METAR 数据为空: {icao}")
+ return None
+
+ # 取最新的观测记录
+ latest = data[0]
+
+ # 提取温度 (METAR 原始单位是摄氏度)
+ temp_c = latest.get("temp")
+ dewp_c = latest.get("dewp")
+
+ # 转换为华氏度（如果需要）
+ if use_fahrenheit and temp_c is not None:
+ temp = temp_c * 9 / 5 + 32
+ dewp = dewp_c * 9 / 5 + 32 if dewp_c is not None else None
+ unit = "fahrenheit"
+ else:
+ temp = temp_c
+ dewp = dewp_c
+ unit = "celsius"
+
+ # 解析观测时间
+ obs_time = latest.get("reportTime", "")
+
+ result = {
+ "source": "metar",
+ "icao": icao,
+ "station_name": latest.get("name", icao),
+ "timestamp": datetime.utcnow().isoformat(),
+ "observation_time": obs_time,
+ "raw_metar": latest.get("rawOb", ""),
+ "current": {
+ "temp": round(temp, 1) if temp is not None else None,
+ "dewpoint": round(dewp, 1) if dewp is not None else None,
+ "humidity": latest.get("rh"), # 相对湿度
+ "wind_speed_kt": latest.get("wspd"), # 风速 (knots)
+ "wind_dir": latest.get("wdir"), # 风向 (度)
+ "visibility_miles": latest.get("visib"), # 能见度 (英里)
+ "altimeter": latest.get("altim"), # 气压
+ "flight_category": latest.get("fltcat"), # VFR/IFR 等
+ "clouds": latest.get("clouds", []),
+ },
+ "unit": unit,
+ }
+
+ logger.info(
+ f"✈️ METAR {icao}: {temp:.1f}°{'F' if use_fahrenheit else 'C'} "
+ f"(obs: {obs_time})"
+ )
+
+ return result
+
+ except requests.exceptions.RequestException as e:
+ logger.error(f"METAR 请求失败 ({icao}): {e}")
+ return None
+ except (KeyError, IndexError, TypeError) as e:
+ logger.error(f"METAR 数据解析失败 ({icao}): {e}")
+ return None
+
def fetch_from_open_meteo(
self,
lat: float,
@@ -234,32 +360,35 @@ class WeatherDataCollector:
def extract_date_from_title(self, title: str) -> Optional[str]:
"""
从标题中提取日期并标准化为 YYYY-MM-DD
- 例如: "Highest temperature in Seattle on February 6?" -> "2026-02-06"
+ 支持: "February 6", "2月6日", "2-6" 等
"""
+ # 1. 尝试英文月份
months = {
- "January": "01",
- "February": "02",
- "March": "03",
- "April": "04",
- "May": "05",
- "June": "06",
- "July": "07",
- "August": "08",
- "September": "09",
- "October": "10",
- "November": "11",
- "December": "12",
+ "January": "01", "February": "02", "March": "03", "April": "04",
+ "May": "05", "June": "06", "July": "07", "August": "08",
+ "September": "09", "October": "10", "November": "11", "December": "12",
}
-
for month_name, month_val in months.items():
if month_name in title:
match = re.search(f"{month_name}\\s+(\\d+)", title)
if match:
day = int(match.group(1))
year = datetime.now().year
- # 简单处理跨年逻辑：如果提取到的月份小于当前月份太多，可能是指明年
- # 但对于天气预报通常只看近期几天
return f"{year}-{month_val}-{day:02d}"
+
+ # 2. 尝试中文格式 "2月7日" 或 "02月07日"
+ zh_match = re.search(r"(\d{1,2})月(\d{1,2})日", title)
+ if zh_match:
+ month = int(zh_match.group(1))
+ day = int(zh_match.group(2))
+ year = datetime.now().year
+ return f"{year}-{month:02d}-{day:02d}"
+
+ # 3. 尝试 ISO 格式 YYYY-MM-DD
+ iso_match = re.search(r"(\d{4})-(\d{2})-(\d{2})", title)
+ if iso_match:
+ return iso_match.group(0)
+
return None
def get_coordinates(self, city: str) -> Optional[Dict[str, float]]:
@@ -317,40 +446,36 @@ class WeatherDataCollector:
def extract_city_from_question(self, question: str) -> Optional[str]:
"""
- 从 Polymarket 问题描述中提取城市名称
- 支持多种描述方式:
- - "Highest temperature in Ankara on February 5?"
- - "Will the temperature in London be..."
- - "Temp in New York..."
+ 从 Polymarket 问题描述或 Slug 中提取城市名称
"""
q = question.lower()
- # 移除常见的干扰词
- for noise in ["highest ", "the ", "will ", "lowest "]:
- if q.startswith(noise):
- q = q[len(noise) :]
+ # 1. 优先尝试已知城市列表 (硬编码匹配)
+ known_cities = {
+ "london": "London", "伦敦": "London",
+ "new york": "New York", "new york's central park": "New York", "nyc": "New York", "纽约": "New York",
+ "seattle": "Seattle", "西雅图": "Seattle",
+ "chicago": "Chicago", "芝加哥": "Chicago",
+ "dallas": "Dallas", "达拉斯": "Dallas",
+ "miami": "Miami", "迈阿密": "Miami",
+ "atlanta": "Atlanta", "亚特兰大": "Atlanta",
+ "seoul": "Seoul", "首尔": "Seoul",
+ "toronto": "Toronto", "多伦多": "Toronto",
+ "ankara": "Ankara", "安卡拉": "Ankara",
+ "wellington": "Wellington", "惠灵顿": "Wellington",
+ "buenos aires": "Buenos Aires", "布宜诺斯艾利斯": "Buenos Aires"
+ }
+
+ for key, val in known_cities.items():
+ if key in q:
+ return val
- # 处理 "temperature in [City]" | "temp in [City]"
- triggers = ["temperature in ", "temp in ", "weather in "]
+ # 2. 从英文模板中提取
+ triggers = ["temperature in ", "temp in ", "weather in ", "highest-temperature-in-", "temperature-in-"]
for trigger in triggers:
if trigger in q:
part = q.split(trigger)[1]
- # 截断日期和其他后缀
- # 按照 "on", "at", "above", "below", "?", " ", "be", "is" 分割
- delimiters = [
- " on ",
- " at ",
- " above ",
- " below ",
- " be ",
- " is ",
- " will ",
- " has ",
- " reached ",
- "?",
- " (",
- ", ",
- ]
+ delimiters = [" on ", " at ", " above ", " below ", " be ", " is ", " will ", " has ", " reached ", "?", " (", ", ", "-"]
city = part
for d in delimiters:
if d in city:
@@ -404,6 +529,11 @@ class WeatherDataCollector:
else:
logger.info(f"🌡️ {city} 使用摄氏度 (°C)")
+ # METAR (Airport Weather - Same source as Weather Underground settlement)
+ metar_data = self.fetch_metar(city, use_fahrenheit=use_fahrenheit)
+ if metar_data:
+ results["metar"] = metar_data
+
# Open-Meteo (Primary Free Source - No Key)
if lat and lon:
open_meteo = self.fetch_from_open_meteo(
diff --git a/src/strategy/risk_manager.py b/src/strategy/risk_manager.py
index 967960e3..2feca543 100644
--- a/src/strategy/risk_manager.py
+++ b/src/strategy/risk_manager.py
@@ -1,14 +1,17 @@
from loguru import logger
+
class RiskManager:
"""
风险控制系统
"""
-
+
def __init__(self, config=None):
self.config = config or {}
# 基础风控参数
- self.max_single_trade = self.config.get("max_single_trade", 50.0) # 最大单笔调整为 $50
+ self.max_single_trade = self.config.get(
+ "max_single_trade", 50.0
+ ) # 最大单笔调整为 $50
self.max_daily_exposure = 50.0 # 每日最高投入上限
self.daily_used_exposure = 0.0
self.last_reset_date = ""
@@ -16,82 +19,81 @@ class RiskManager:
self.min_confidence = 0.5
self.peak_capital = 0
self.is_trading_paused = False
-
+
logger.info("Initializing Pro Risk Manager...")
def _reset_daily_exposure(self):
"""每日重置额度"""
from datetime import datetime
+
today = datetime.now().strftime("%Y-%m-%d")
if self.last_reset_date != today:
self.daily_used_exposure = 0.0
self.last_reset_date = today
logger.info(f"Daily exposure reset for {today}")
- def calculate_position_size(self,
- base_confidence_usd: float,
- depth: float,
- hours_to_settle: float,
- is_high_relative_volume: bool) -> tuple[float, str]:
+ def calculate_position_size(
+ self,
+ base_confidence_usd: float,
+ depth: float = 0,
+ hours_to_settle: float = 24,
+ is_high_relative_volume: bool = False,
+ ) -> tuple[float, str]:
"""
- 四层过滤仓位计算方法:
- 仓位 = base_position(置信度)
- × liquidity_factor(深度/仓位 >= 5x)
- × time_decay(离结算衰减)
+ 仓位计算方法 (简化版，移除流动性过滤):
+ 仓位 = base_position(置信度)
+ × time_decay(离结算衰减)
× budget_limit
"""
self._reset_daily_exposure()
-
+
final_pos = base_confidence_usd
reason = "Normal"
- # 1. 流动性过滤: 深度 < $50 强制跳过; 深度 < 仓位的 5 倍则缩减
- if depth < 50:
- return 0.0, "🚫深度不足 (min $50)"
-
- if depth < final_pos * 5:
- # 如果深度不足以承载期望仓位，按比例缩减至深度的 1/5
- final_pos = depth / 5.0
- reason = "⚠️深度限流"
-
- # 2. 时间衰减因子
+ # 1. 时间衰减因子
# 离结算时间越近，预测越准但也存在剧烈博弈风险
time_factor = 1.0
if hours_to_settle <= 1.0:
- time_factor = 0.0 # 最后 1 小时停止建仓
+ time_factor = 0.0 # 最后 1 小时停止建仓
reason = "🚫临近结算"
elif hours_to_settle <= 4.0:
- time_factor = 0.4 # 1-4小时：缩小 60%
+ time_factor = 0.4 # 1-4小时：缩小 60%
reason = "⏱️结算冲刺 (40%)"
elif hours_to_settle <= 12.0:
- time_factor = 0.7 # 4-12小时：缩小 30%
+ time_factor = 0.7 # 4-12小时：缩小 30%
reason = "⏳接近结算 (70%)"
-
- final_pos *= time_factor
- if final_pos <= 0: return 0.0, reason
- # 3. 预算上限过滤
+ final_pos *= time_factor
+ if final_pos <= 0:
+ return 0.0, reason
+
+ # 2. 预算上限过滤
remaining_daily = self.max_daily_exposure - self.daily_used_exposure
if remaining_daily <= 0:
return 0.0, "🚫今日总额度已满 ($50)"
-
+
if final_pos > remaining_daily:
final_pos = remaining_daily
reason = "🛑触及日风控上限"
- # 4. 高相对成交量加权 (如果是高成交量市场，且逻辑支持，可保持原状或微增)
+ # 3. 高相对成交量加权 (如果是高成交量市场，且逻辑支持，可保持原状或微增)
# 这里逻辑设定为：如果不是高成交量，再次缩减 20% 防御
if not is_high_relative_volume:
final_pos *= 0.8
- if reason == "Normal": reason = "📉低活缩减"
+ if reason == "Normal":
+ reason = "📉低活缩减"
return round(final_pos, 2), reason
def record_trade(self, amount: float):
"""记录成交额以扣除额度"""
self.daily_used_exposure += amount
- logger.debug(f"Applied exposure: ${amount}. Daily Total: ${self.daily_used_exposure}")
+ logger.debug(
+ f"Applied exposure: ${amount}. Daily Total: ${self.daily_used_exposure}"
+ )
- def check_trade_risk(self, trade_size: float, market_data: dict, model_confidence: float) -> dict:
+ def check_trade_risk(
+ self, trade_size: float, market_data: dict, model_confidence: float
+ ) -> dict:
"""保持基础接口兼容"""
return {"passed": True, "risks": []}
diff --git a/src/utils/notifier.py b/src/utils/notifier.py
index 5fdc7136..be0d733d 100644
--- a/src/utils/notifier.py
+++ b/src/utils/notifier.py
@@ -134,8 +134,9 @@ class TelegramNotifier:
total_volume: float = 0,
brackets_count: int = 0,
strategy_tips: list = None,
+ metar_data: dict = None,
):
- """发送简约版合并预警"""
+ """发送简约版合并预警 (含 METAR 航空气象数据)"""
if not alerts:
return
@@ -143,16 +144,38 @@ class TelegramNotifier:
# UTC+8 北京时间
now_bj = datetime.utcnow() + timedelta(hours=8)
- timestamp_bj = now_bj.strftime(
- "%H:%M"
- ) # 简化为仅显示时间，日期通常与当地一致或不重要
+ timestamp_bj = now_bj.strftime("%H:%M")
- # 1. 信号详情构建
+ # 1. METAR 航空气象数据区块
+ metar_text = ""
+ if metar_data and metar_data.get("current", {}).get("temp") is not None:
+ icao = metar_data.get("icao", "N/A")
+ temp = metar_data["current"]["temp"]
+ unit = "°F" if metar_data.get("unit") == "fahrenheit" else "°C"
+
+ # 解析观测时间 (格式: 2026-02-07T11:00:00.000Z)
+ obs_time_raw = metar_data.get("observation_time", "")
+ if "T" in obs_time_raw:
+ obs_time = obs_time_raw.split("T")[1][:5] + " UTC"
+ else:
+ obs_time = obs_time_raw or "N/A"
+
+ # 可选：风速信息
+ wind_kt = metar_data["current"].get("wind_speed_kt")
+ wind_text = f" | 风速:{wind_kt}kt" if wind_kt else ""
+
+ metar_text = (
+ f"✈️ 机场实测 ({icao}):\n"
+ f" 🌡️ {temp:.1f}{unit}{wind_text}\n"
+ f" 🕐 观测: {obs_time}\n\n"
+ )
+
+ # 2. 信号详情构建
items_text = ""
for a in alerts:
items_text += f"{a['msg']}\n\n"
- # 2. 策略建议（如果有）
+ # 3. 策略建议（如果有）
tips_text = ""
if strategy_tips:
tips_text = (
@@ -161,10 +184,11 @@ class TelegramNotifier:
+ "\n\n"
)
- # 3. 总体布局 (回归清爽风格)
+ # 4. 总体布局
text = (
f"🔔 城市监控报告 #{self._escape_html(city)}\n\n"
f"📍 城市: {self._escape_html(city)}\n"
+ f"{metar_text}"
f"📊 实时异动:\n"
f"{items_text}"
f"{tips_text}"
diff --git a/test_price.py b/test_price.py
deleted file mode 100644
index ddd6f9a7..00000000
--- a/test_price.py
+++ /dev/null
@@ -1,111 +0,0 @@
-"""
-Polymarket 天气市场价格查询
-直接获取 YES/NO 的真实买入价格（Ask）
-"""
-import requests
-
-# ============ 配置 ============
-# 替换成你要查的 token_id（从 Gamma API 获取）
-YES_TOKEN_ID = "你的YES_token_id"
-NO_TOKEN_ID = "你的NO_token_id"
-
-CLOB_BASE = "https://clob.polymarket.com"
-GAMMA_BASE = "https://gamma-api.polymarket.com"
-# ============ 方法1: 快速查价格 ============
-def get_price(token_id, side="buy"):
-"""获取单个 token 的买入/卖出价格"""
-resp = requests.get(f"{CLOB_BASE}/price", params={
-"token_id": token_id,
-"side": side.upper()
-})
-data = resp.json()
-return float(data.get("price", 0))
-
-# ============ 方法2: 查完整盘口 ============
-def get_orderbook(token_id):
-"""获取完整 orderbook，含深度"""
-resp = requests.get(f"{CLOB_BASE}/book", params={
-"token_id": token_id
-})
-return resp.json()
-
-# ============ 方法3: 从 Gamma 发现天气市场 ============
-def discover_weather_markets(city="New York"):
-"""自动发现天气市场，获取 token_id"""
-resp = requests.get(f"{GAMMA_BASE}/markets", params={
-"tag": "weather",
-"closed": "false",
-"limit": 50
-})
-markets = resp.json()
-results = []
-for m in markets:
-if city.lower() in m.get("question", "").lower():
-tokens = m.get("tokens", [])
-if len(tokens) >= 2:
- yes_token = None
- no_token = None
- for t in tokens:
- if t.get("outcome") == "Yes":
- yes_token = t["token_id"]
- else:
- no_token = t["token_id"]
- if yes_token and no_token:
- results.append({
- "question": m["question"],
- "yes_token": yes_token,
- "no_token": no_token,
- "slug": m.get("market_slug", "")
- })
-return results
-
-
-# ============ 主流程 ============
-def main():
-print("📡 正在发现 NYC 天气市场...\n")
-markets = discover_weather_markets("New York")
-if not markets:
-print("❌ 未找到天气市场，检查 Gamma API")
-return
-
-print(f"✅ 找到 {len(markets)} 个市场\n")
-print("=" * 55)
-
-for m in markets[:10]:
-q = m["question"]
-yes_id = m["yes_token"]
-no_id = m["no_token"]
-
-# 获取真实 Ask 价格
-yes_ask = get_price(yes_id, "buy")
-no_ask = get_price(no_id, "buy")
-
-# 获取 Bid
-yes_bid = get_price(yes_id, "sell")
-
-spread = yes_ask - yes_bid if yes_ask and yes_bid else None
-
-# 获取盘口深度
-book = get_orderbook(yes_id)
-ask_depth = sum(float(o.get("size", 0)) for o in book.get("asks", [])[:3])
-bid_depth = sum(float(o.get("size", 0)) for o in book.get("bids", [])[:3])
-
-# 流动性判断
-if ask_depth < 50:
-liq = "🔴枯竭"
-elif ask_depth < 500:
-liq = "🟡正常"
-else:
-liq = "🟢充裕"
-
-print(f"\n📊 {q}")
-print(f" YES Ask: {yes_ask*100:.1f}¢ | NO Ask: {no_ask*100:.1f}¢")
-print(f" YES Bid: {yes_bid*100:.1f}¢ | Spread: {spread*100:.1f}¢" if spread else " YES Bid: --")
-print(f" 深度: Ask ${ask_depth:.0f} | Bid ${bid_depth:.0f} | {liq}")
-print(f" 🔗 https://polymarket.com/event/{m['slug']}")
-
-print("\n" + "=" * 55)
-print("💡 价格单位: Ask = 你买入要付的价格")
-
-if __name__ == "__main__":
-main()
\ No newline at end of file
diff --git a/test_template.py b/test_template.py
deleted file mode 100644
index 186e1caf..00000000
--- a/test_template.py
+++ /dev/null
@@ -1,65 +0,0 @@
-
-import os
-import json
-from src.utils.config_loader import load_config
-from src.utils.notifier import TelegramNotifier
-
-def send_test_template():
- config_data = load_config()
- notifier = TelegramNotifier(config_data["telegram"])
-
- city = "Nyc"
- target_date = "2026-02-07"
-
- # 模拟异动信号数据
- alerts = [
- {
- "market": target_date,
- "msg": (
- "🟢 26°F+\n"
- "执行动作: BUY YES ⬆️\n"
- "Ask: 80¢ | Bid: -- | Mid: 79.5¢\n"
- "Spread: 1.2¢ | 深度: $1,847\n"
- "流动性: ✅ 充裕 | 可交易: ✅\n"
- "📐 预测偏差: -3.0°F (预测 23.0°F)"
- ),
- "bought": True,
- "amount": 7.0,
- "confidence": "⭐中置信"
- },
- {
- "market": target_date,
- "msg": (
- "🔴 18-19°F\n"
- "执行动作: SELL YES ⬇️\n"
- "Ask: -- | Bid: 5.0¢ | Mid: 4.5¢\n"
- "Spread: 0.5¢ | 深度: $312\n"
- "流动性: ✅ 正常 | 可交易: ✅\n"
- "📐 预测偏差: -4.0°F (预测 23.0°F)"
- ),
- "bought": False,
- "amount": 0.0,
- "confidence": ""
- }
- ]
-
- strategy_tips = [
- "预测温度 23.0°F 落在 22-23°F 区间，市场与模型一致",
- "26°F+ 区间出现主力大额买入，建议跟随",
- "18-19°F 流动性正常但偏差过大，已执行调仓"
- ]
-
- print("🚀 正在发送测试模板到 Telegram...")
- notifier.send_combined_alert(
- city=city,
- alerts=alerts,
- local_time="10:56 EST",
- forecast_temp="23.0°F",
- total_volume=40113,
- brackets_count=7,
- strategy_tips=strategy_tips
- )
- print("✅ 发送成功！请检查手机。")
-
-if __name__ == "__main__":
- send_test_template()