2569718930@qq.com
22e2409e13
- fetch_all_sources 新增 om_from_cache_only 模式：force_refresh_observations_only 时直接从内存缓存取 OM 数据，不发起 HTTP 请求。缓存未命中则跳过， 避免机场推送 60s 周期持续触发 429 限流 - nws_open_meteo_sources 三类 fetch 函数冷却期加磁盘缓存兜底： 内存未命中时 force-reload SQLite 磁盘缓存再查一次 - 预热停止后冷却期自然过期（900s），下一次正常请求会填充缓存
24 lines
937 B
Python
24 lines
937 B
Python
"""Check which cities have hourly / multi-model data in the analysis cache."""
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import urllib.request, json
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TOK = "Bearer ZLuvwSsQvHSj2geIWfX7gjn9rJU_heOlgq0FBp7cUOgXaB2eHbE20R4PKwonP2FP"
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CITIES = [
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"london", "paris", "amsterdam", "helsinki", "istanbul", "ankara",
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"moscow", "new york", "los angeles", "chicago", "miami", "houston",
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"lagos", "jeddah", "karachi", "tel aviv",
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]
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for city in CITIES:
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url = f"http://localhost:8000/api/city/{city}/detail?force_refresh=false"
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req = urllib.request.Request(url, headers={"Authorization": TOK})
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try:
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r = urllib.request.urlopen(req, timeout=30)
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d = json.loads(r.read())
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except Exception as e:
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print(f"{city}: FAILED {e}")
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continue
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h = d.get("timeseries", {}).get("hourly", {})
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m = d.get("models", {})
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deb = d.get("deb", {})
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print(f"{city}: hourly={len(h.get('times',[]))}p models={len(m)} deb={deb.get('prediction')}")
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