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feat: Implement multi-source weather data collection from various APIs and integrate Polymarket API functionality.

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2569718930@qq.com
2026-02-06 22:15:42 +08:00
parent 1b4ffe2d10
commit bc4eb6445b
3 changed files with 59 additions and 50 deletions
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main.py
+53 -32
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@@ -124,22 +124,30 @@ def main():
time.sleep(300)
continue
# 2. 批量同步盘口价格 (优化：一次请求获取所有市场的 Buy Yes/No)
# 2. 批量同步盘口价格 (优化：为每个档位获取其对应的真实 Token 价格)
token_price_map = {}
price_requests = []
for m in all_weather_markets:
ts = m.get("tokens", [])
if isinstance(ts, str):
try:
ts = json.loads(ts)
except:
ts = []
if ts and len(ts) >= 2:
try: ts = json.loads(ts)
except: ts = []
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:
# 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 price_requests:
logger.info(f"正在同步 {len(price_requests)} 个档位的盘口价格...")
logger.info(f"正在同步 {len(price_requests)} 个档位的真实盘口价格...")
token_price_map = polymarket.get_multiple_prices(price_requests)
logger.info(f"价格同步完成，成功获取 {len(token_price_map)} 个实时报价")
@@ -156,11 +164,19 @@ def main():
# 注入实时批量价格
ts = m.get("tokens", [])
if isinstance(ts, str):
try:
ts = json.loads(ts)
except:
ts = []
if ts and len(ts) >= 2:
try: ts = json.loads(ts)
except: ts = []
active_tid = m.get("active_token_id")
# 多选一市场逻辑
if len(ts) > 2 and active_tid:
m["buy_yes_live"] = token_price_map.get(active_tid) # 该档位的 Ask
# 买入“否”的价格 = 1 - 该档位的 Bid (别人愿意买 Yes 的最高价)
bid_price = token_price_map.get(active_tid) # 这里逻辑稍后在下文 fallback 处理中增强
# 我们这里只是注入，真正复杂的 fallback 逻辑在循环内部
# 二选一市场逻辑
elif len(ts) == 2:
m["buy_yes_live"] = token_price_map.get(ts[0])
m["buy_no_live"] = token_price_map.get(ts[1])
@@ -243,37 +259,40 @@ def main():
ref_temp = max_temps[idx]
break
# --- 价格获取逻辑 ---
# --- 价格获取逻辑 (增强版) ---
buy_yes_price = market.get("buy_yes_live")
buy_no_price = market.get("buy_no_live")
# 如果批量接口没拿到，尝试单独查询 orderbook
ts = market.get("tokens", [])
if isinstance(ts, str): ts = json.loads(ts)
active_tid = market.get("active_token_id")
# 特殊逻辑：针对多选一型市场（Dallas/Chicago 等温度段）
if len(ts) > 2 and active_tid:
# 1. 尝试从批量映射中重新获取该档位的精确买入价(Ask)
buy_yes_price = polymarket.get_price(active_tid, side="ask") if buy_yes_price is None else buy_yes_price
# 2. 计算“否”的价格（在多选一里是 1 - 最高买入意愿价Bid）
bid_price = polymarket.get_price(active_tid, side="bid")
if bid_price:
buy_no_price = 1.0 - bid_price
if i < 3: # 仅对前几个档位打印调试
logger.debug(f"Categorical价格匹配 [{market.get('city')}-{market.get('question')}]: Yes={buy_yes_price}, No={buy_no_price} (from Bid={bid_price})")
# 通用回退逻辑 (二选一)
if buy_yes_price is None or buy_no_price is None:
ts = market.get("tokens", [])
if isinstance(ts, str):
try:
ts = json.loads(ts)
except:
ts = []
if ts and len(ts) >= 2:
prices = polymarket.get_buy_prices(ts[0], ts[1])
if prices:
buy_yes_price = prices.get("buy_yes")
buy_no_price = prices.get("buy_no")
# 最后回退：使用 gamma 概率
# 最后的回退：使用原始 Gamma 概率
if buy_yes_price is None or buy_no_price is None:
gamma_prices = market.get("prices", [])
if isinstance(gamma_prices, str):
try:
gamma_prices = json.loads(gamma_prices)
except:
gamma_prices = []
current_price = float(gamma_prices[0]) if gamma_prices else 0.5
if buy_yes_price is None:
buy_yes_price = current_price
if buy_no_price is None:
buy_no_price = 1.0 - current_price
if isinstance(gamma_prices, str): gamma_prices = json.loads(gamma_prices)
prob = float(gamma_prices[0]) if gamma_prices else 0.5
if buy_yes_price is None: buy_yes_price = prob
if buy_no_price is None: buy_no_price = 1.0 - prob
# C. 准备缓存
temp_unit = weather_data.get("open-meteo", {}).get(
@@ -286,6 +305,8 @@ def main():
.get("local_time")
)
current_price = buy_yes_price if buy_yes_price else 0.5
# 计算价格趋势
prev_data = price_history.get(market_id, {})
prev_price = prev_data.get("price", current_price)