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scripts/analyze_iot_api_fast.py

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+"""Fast sample scan of IoT flocks API — day/date mapping without full pagination."""
+import json
+import urllib.request
+from collections import defaultdict
+from datetime import datetime, timedelta, timezone
+
+BASE = "https://dashboard.cpsp.id/api/iot/flocks/"
+CYCLE_START = datetime(2026, 5, 22).date()
+TZ = timezone(timedelta(hours=7))
+
+
+def parse_dt(value: str) -> datetime:
+    return datetime.fromisoformat(value.replace("Z", "+00:00"))
+
+
+def fetch_page(page: int) -> dict:
+    with urllib.request.urlopen(f"{BASE}?page={page}", timeout=60) as resp:
+        return json.loads(resp.read())
+
+
+def summarize_records(records: list) -> None:
+    by_day: dict[int, list] = defaultdict(list)
+    for r in records:
+        day = r["payload"]["data"].get("day")
+        if day is not None:
+            by_day[day].append(r)
+
+    print(f"  unique days: {len(by_day)} range {min(by_day)}..{max(by_day)}")
+    for day in sorted(by_day)[:3]:
+        r = max(by_day[day], key=lambda x: parse_dt(x["fetched_at"]))
+        d = r["payload"]["data"]
+        cal = CYCLE_START + timedelta(days=day - 1)
+        print(
+            f"    day {day} -> {cal} | wind={d.get('wind')} hum={d.get('humidity')} "
+            f"temp={d.get('actualTemperature')} water={d.get('water')} HSI={d.get('HSI')}"
+        )
+    if len(by_day) > 6:
+        print("    ...")
+    for day in sorted(by_day)[-3:]:
+        r = max(by_day[day], key=lambda x: parse_dt(x["fetched_at"]))
+        d = r["payload"]["data"]
+        cal = CYCLE_START + timedelta(days=day - 1)
+        print(
+            f"    day {day} -> {cal} | wind={d.get('wind')} hum={d.get('humidity')} "
+            f"temp={d.get('actualTemperature')} water={d.get('water')} HSI={d.get('HSI')}"
+        )
+
+
+def main() -> None:
+    p1 = fetch_page(1)
+    total = p1["count"]
+    page_size = len(p1["results"])
+    last_page = (total + page_size - 1) // page_size
+    print(f"API total={total} page_size={page_size} pages={last_page}")
+
+    r0 = p1["results"][0]
+    d0 = r0["payload"]["data"]
+    coop = d0.get("coop") or {}
+    print(f"flock_id={r0['flock_id']} floor={d0.get('name')} site={coop.get('kode')}")
+    print(f"kandang field (Mongo id)={d0.get('kandang')}")
+
+    # Sample: first pages (newest), last pages (oldest), and mid pages
+    sample_pages = sorted({1, 2, 3, 10, 50, 100, 200, 400, 600, last_page, last_page - 1, last_page - 2})
+    all_records = []
+    for page in sample_pages:
+        if page < 1 or page > last_page:
+            continue
+        data = fetch_page(page)
+        all_records.extend(data["results"])
+        days = {r["payload"]["data"].get("day") for r in data["results"]}
+        fdates = {parse_dt(r["fetched_at"]).astimezone(TZ).date() for r in data["results"]}
+        print(f"page {page:4d}: days={min(days)}..{max(days)} fetched_dates={min(fdates)}..{max(fdates)}")
+
+    # Roll up sampled data: latest fetched_at per cycle day
+    daily: dict[int, dict] = {}
+    for r in all_records:
+        day = r["payload"]["data"].get("day")
+        if day is None:
+            continue
+        ts = parse_dt(r["fetched_at"])
+        if day not in daily or ts > daily[day]["ts"]:
+            daily[day] = {"ts": ts, "r": r}
+
+    print(f"\nFrom sample: {len(daily)} unique cycle days seen")
+    missing = [d for d in range(1, 50) if d not in daily]
+    print(f"Missing in sample (1..49): {missing}")
+
+    print("\nField mapping -> iot_panel (exclude experience_temperature):")
+    print("  date              = cycle_start + (day - 1)  # 2026-05-22 + day-1")
+    print("  wind_speed        = payload.data.wind")
+    print("  humidity          = payload.data.humidity  # likely /10 for %")
+    print("  water_total       = payload.data.water")
+    print("  average_temperature = payload.data.actualTemperature  # likely /10 for °C")
+    print("  experience_temperature = formula (HSI? TBD)")
+
+    print("\nSample rollup table:")
+    print(f"{'day':>3} {'date':>10} {'wind':>5} {'hum':>6} {'temp_raw':>8} {'water':>6} {'HSI':>7}")
+    for day in range(1, 50):
+        cal = CYCLE_START + timedelta(days=day - 1)
+        entry = daily.get(day)
+        if not entry:
+            continue
+        d = entry["r"]["payload"]["data"]
+        print(
+            f"{day:3d} {cal} {d.get('wind', 0):5} {d.get('humidity', 0):6} "
+            f"{d.get('actualTemperature', 0):8} {d.get('water', 0):6} {d.get('HSI', 0):7.2f}"
+        )
+
+
+if __name__ == "__main__":
+    main()