"""Virtual farm nodes — replay the cleaned farm log to the API so the dashboard works before the
hardware is deployed (and to load-test the server).

python simulate_nodes.py                 # live: one reading per node every 5 s
python simulate_nodes.py --backfill 72   # instantly insert the last 72 hours (timestamps shifted to now)
Also executes pending pump/fan commands like a real ESP32 would (prints them and sends the ACK).
"""
import argparse
import json
import time
import urllib.request
from datetime import datetime, timedelta
from pathlib import Path

import pandas as pd

import config

BASE = Path(__file__).resolve().parent
SRC = BASE.parent / "ai" / "outputs" / "node_log_clean.csv"
RAW = BASE.parent.parent / "datasets" / "node_log_raw.csv"


def call(url, payload=None):
    req = urllib.request.Request(url, data=json.dumps(payload).encode() if payload else None,
                                 headers={"X-API-Key": config.NODE_API_KEY, "Content-Type": "application/json"},
                                 method="POST" if payload is not None else "GET")
    with urllib.request.urlopen(req, timeout=5) as r:
        return json.load(r)


def load():
    df = pd.read_csv(SRC if SRC.exists() else RAW, parse_dates=["timestamp"])
    df = df.dropna(subset=["air_temp_c", "soil_moisture_pct"])
    return df.sort_values("timestamp")


def row_payload(r, ts):
    return {"node_id": r.node_id, "ts": ts.isoformat(timespec="seconds"), "air_temp_c": round(r.air_temp_c, 2),
            "air_humidity_pct": round(r.air_humidity_pct, 1), "soil_moisture_pct": round(r.soil_moisture_pct, 1),
            "light": int(r.light_adc), "battery_v": float(r.battery_v), "rssi": -67, "fw": "sim-1.0"}


if __name__ == "__main__":
    ap = argparse.ArgumentParser()
    ap.add_argument("--url", default="http://127.0.0.1:5000")
    ap.add_argument("--backfill", type=int, default=0, help="hours of history to insert instantly")
    ap.add_argument("--interval", type=float, default=5.0)
    a = ap.parse_args()
    df = load()

    if a.backfill:
        last = df["timestamp"].max()
        part = df[df["timestamp"] > last - timedelta(hours=a.backfill)]
        shift = datetime.now() - last
        for r in part.itertuples():
            call(a.url + "/api/v1/readings", row_payload(r, r.timestamp + shift))
        print(f"inserted {len(part)} readings ({a.backfill} h)")
    else:
        groups = {n: g.reset_index(drop=True) for n, g in df.groupby("node_id")}
        i = 0
        while True:
            for node, g in groups.items():
                r = g.iloc[i % len(g)]
                call(a.url + "/api/v1/readings", row_payload(r, datetime.now()))
                for c in call(a.url + f"/api/v1/commands/pending?node_id={node}")["commands"]:
                    print(f"[{node}] relay -> {c['actuator']} {c['action']} {c['duration_min']} min")
                    call(a.url + f"/api/v1/commands/{c['id']}/ack", {})
            i += 1
            print(datetime.now().strftime("%H:%M:%S"), "sent", len(groups), "readings")
            time.sleep(a.interval)