#!/usr/bin/env python3
"""
Enhanced Data Simulator for Bootstrap Sensors
Generates realistic real-time sensor data for the bootstrap sensors created by bootstrap_sensors.py
"""

import redis
import time
import random
import json
import logging
from datetime import datetime, timedelta
from typing import Dict, List, Any
import math

# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

# Redis configuration
REDIS_HOST = 'localhost'
REDIS_PORT = 6379
REDIS_CHANNEL = "energy_data"

# Bootstrap sensor IDs (must match bootstrap_sensors.py)
BOOTSTRAP_SENSORS = {
    # Living Room Sensors
    "lr_energy_001": {"type": "energy", "room": "living_room", "base_value": 2.5, "variance": 1.2},
    "lr_co2_001": {"type": "co2", "room": "living_room", "base_value": 420, "variance": 80},
    "lr_temp_001": {"type": "temperature", "room": "living_room", "base_value": 22.0, "variance": 2.0},

    # Kitchen Sensors
    "kt_energy_001": {"type": "energy", "room": "kitchen", "base_value": 3.8, "variance": 2.1},
    "kt_humidity_001": {"type": "humidity", "room": "kitchen", "base_value": 45.0, "variance": 15.0},
    "kt_temp_001": {"type": "temperature", "room": "kitchen", "base_value": 24.0, "variance": 3.0},

    # Bedroom Sensors
    "br_energy_001": {"type": "energy", "room": "bedroom", "base_value": 1.2, "variance": 0.8},
    "br_co2_001": {"type": "co2", "room": "bedroom", "base_value": 480, "variance": 120},
    "br_temp_001": {"type": "temperature", "room": "bedroom", "base_value": 20.5, "variance": 1.5},

    # Office Sensors
    "of_energy_001": {"type": "energy", "room": "office", "base_value": 2.1, "variance": 1.5},
    "of_co2_001": {"type": "co2", "room": "office", "base_value": 450, "variance": 100},
    "of_motion_001": {"type": "motion", "room": "office", "base_value": 0, "variance": 1},

    # Bathroom Sensors
    "bt_humidity_001": {"type": "humidity", "room": "bathroom", "base_value": 65.0, "variance": 20.0},
    "bt_temp_001": {"type": "temperature", "room": "bathroom", "base_value": 23.0, "variance": 2.5},

    # Garage Sensors
    "gr_energy_001": {"type": "energy", "room": "garage", "base_value": 0.8, "variance": 0.5},
    "gr_motion_001": {"type": "motion", "room": "garage", "base_value": 0, "variance": 1}
}

class SensorDataGenerator:
    """Generates realistic sensor data with time-based patterns"""

    def __init__(self):
        self.start_time = time.time()
        self.motion_states = {}  # Track motion sensor states

        # Initialize motion states
        for sensor_id, config in BOOTSTRAP_SENSORS.items():
            if config["type"] == "motion":
                self.motion_states[sensor_id] = {"active": False, "last_change": time.time()}

    def get_time_factor(self) -> float:
        """Get time-based multiplier for realistic daily patterns"""
        current_hour = datetime.now().hour

        # Energy usage patterns (higher during day, lower at night)
        if 6 <= current_hour <= 22:  # Daytime
            return 1.0 + 0.3 * math.sin((current_hour - 6) * math.pi / 16)
        else:  # Nighttime
            return 0.3 + 0.2 * random.random()

    def get_occupancy_factor(self, room: str) -> float:
        """Get occupancy-based multiplier for different rooms"""
        current_hour = datetime.now().hour

        occupancy_patterns = {
            "living_room": 1.2 if 18 <= current_hour <= 23 else 0.8,
            "kitchen": 1.5 if 7 <= current_hour <= 9 or 17 <= current_hour <= 20 else 0.6,
            "bedroom": 1.3 if 22 <= current_hour or current_hour <= 7 else 0.4,
            "office": 1.4 if 9 <= current_hour <= 17 else 0.3,
            "bathroom": 1.0,  # Consistent usage
            "garage": 0.8 if 7 <= current_hour <= 9 or 17 <= current_hour <= 19 else 0.2
        }

        return occupancy_patterns.get(room, 1.0)

    def generate_energy_reading(self, sensor_id: str, config: Dict) -> Dict[str, Any]:
        """Generate realistic energy consumption reading"""
        base_value = config["base_value"]
        variance = config["variance"]
        room = config["room"]

        # Apply time and occupancy factors
        time_factor = self.get_time_factor()
        occupancy_factor = self.get_occupancy_factor(room)

        # Add some randomness
        random_factor = 1.0 + (random.random() - 0.5) * 0.4

        # Calculate final value
        value = base_value * time_factor * occupancy_factor * random_factor
        value = max(0.1, value)  # Ensure minimum consumption

        return {
            "sensor_id": sensor_id,
            "room": room,
            "sensor_type": "energy",
            "timestamp": int(time.time()),
            "energy": {
                "value": round(value, 3),
                "unit": "kWh"
            },
            "metadata": {
                "time_factor": round(time_factor, 2),
                "occupancy_factor": round(occupancy_factor, 2)
            }
        }

    def generate_co2_reading(self, sensor_id: str, config: Dict) -> Dict[str, Any]:
        """Generate realistic CO2 level reading"""
        base_value = config["base_value"]
        variance = config["variance"]
        room = config["room"]

        # CO2 increases with occupancy
        occupancy_factor = self.get_occupancy_factor(room)
        co2_increase = (occupancy_factor - 0.5) * 150

        # Add random fluctuation
        random_variation = (random.random() - 0.5) * variance

        value = base_value + co2_increase + random_variation
        value = max(350, min(2000, value))  # Realistic CO2 range

        return {
            "sensor_id": sensor_id,
            "room": room,
            "sensor_type": "co2",
            "timestamp": int(time.time()),
            "co2": {
                "value": round(value, 1),
                "unit": "ppm"
            },
            "metadata": {
                "quality_level": "good" if value < 600 else "moderate" if value < 1000 else "poor"
            }
        }

    def generate_temperature_reading(self, sensor_id: str, config: Dict) -> Dict[str, Any]:
        """Generate realistic temperature reading"""
        base_value = config["base_value"]
        variance = config["variance"]
        room = config["room"]

        # Temperature varies with time of day and occupancy
        current_hour = datetime.now().hour
        daily_variation = 2 * math.sin((current_hour - 6) * math.pi / 12)

        occupancy_factor = self.get_occupancy_factor(room)
        occupancy_heat = (occupancy_factor - 0.5) * 1.5

        random_variation = (random.random() - 0.5) * variance

        value = base_value + daily_variation + occupancy_heat + random_variation

        return {
            "sensor_id": sensor_id,
            "room": room,
            "sensor_type": "temperature",
            "timestamp": int(time.time()),
            "temperature": {
                "value": round(value, 1),
                "unit": "°C"
            }
        }

    def generate_humidity_reading(self, sensor_id: str, config: Dict) -> Dict[str, Any]:
        """Generate realistic humidity reading"""
        base_value = config["base_value"]
        variance = config["variance"]
        room = config["room"]

        # Humidity patterns based on room usage
        if room == "bathroom":
            # Higher spikes during usage times
            current_hour = datetime.now().hour
            if 7 <= current_hour <= 9 or 19 <= current_hour <= 22:
                usage_spike = random.uniform(10, 25)
            else:
                usage_spike = 0
        elif room == "kitchen":
            # Cooking increases humidity
            current_hour = datetime.now().hour
            if 17 <= current_hour <= 20:
                usage_spike = random.uniform(5, 15)
            else:
                usage_spike = 0
        else:
            usage_spike = 0

        random_variation = (random.random() - 0.5) * variance
        value = base_value + usage_spike + random_variation
        value = max(20, min(95, value))  # Realistic humidity range

        return {
            "sensor_id": sensor_id,
            "room": room,
            "sensor_type": "humidity",
            "timestamp": int(time.time()),
            "humidity": {
                "value": round(value, 1),
                "unit": "%"
            }
        }

    def generate_motion_reading(self, sensor_id: str, config: Dict) -> Dict[str, Any]:
        """Generate realistic motion detection reading"""
        room = config["room"]
        current_time = time.time()

        # Get current state
        if sensor_id not in self.motion_states:
            self.motion_states[sensor_id] = {"active": False, "last_change": current_time}

        state = self.motion_states[sensor_id]

        # Determine if motion should be detected based on occupancy patterns
        occupancy_factor = self.get_occupancy_factor(room)
        motion_probability = occupancy_factor * 0.3  # 30% chance when occupied

        # Change state based on probability and time since last change
        time_since_change = current_time - state["last_change"]

        if state["active"]:
            # If motion is active, chance to stop after some time
            if time_since_change > 30:  # At least 30 seconds of motion
                if random.random() < 0.4:  # 40% chance to stop
                    state["active"] = False
                    state["last_change"] = current_time
        else:
            # If no motion, chance to start based on occupancy
            if time_since_change > 10:  # At least 10 seconds of no motion
                if random.random() < motion_probability:
                    state["active"] = True
                    state["last_change"] = current_time

        return {
            "sensor_id": sensor_id,
            "room": room,
            "sensor_type": "motion",
            "timestamp": int(time.time()),
            "motion": {
                "value": 1 if state["active"] else 0,
                "unit": "detected"
            },
            "metadata": {
                "duration_seconds": int(time_since_change) if state["active"] else 0
            }
        }

    def generate_sensor_reading(self, sensor_id: str) -> Dict[str, Any]:
        """Generate appropriate reading based on sensor type"""
        if sensor_id not in BOOTSTRAP_SENSORS:
            logger.warning(f"Unknown sensor ID: {sensor_id}")
            return None

        config = BOOTSTRAP_SENSORS[sensor_id]
        sensor_type = config["type"]

        if sensor_type == "energy":
            return self.generate_energy_reading(sensor_id, config)
        elif sensor_type == "co2":
            return self.generate_co2_reading(sensor_id, config)
        elif sensor_type == "temperature":
            return self.generate_temperature_reading(sensor_id, config)
        elif sensor_type == "humidity":
            return self.generate_humidity_reading(sensor_id, config)
        elif sensor_type == "motion":
            return self.generate_motion_reading(sensor_id, config)
        else:
            logger.warning(f"Unknown sensor type: {sensor_type}")
            return None

def main():
    """Main simulation loop"""
    logger.info("=== Starting Enhanced Data Simulator ===")

    # Connect to Redis
    try:
        redis_client = redis.Redis(host=REDIS_HOST, port=REDIS_PORT, db=0, decode_responses=True)
        redis_client.ping()
        logger.info(f"Successfully connected to Redis at {REDIS_HOST}:{REDIS_PORT}")
    except redis.exceptions.ConnectionError as e:
        logger.error(f"Could not connect to Redis: {e}")
        return

    # Initialize data generator
    generator = SensorDataGenerator()

    logger.info(f"Loaded {len(BOOTSTRAP_SENSORS)} bootstrap sensors")
    logger.info(f"Publishing to Redis channel: '{REDIS_CHANNEL}'")
    logger.info("Press Ctrl+C to stop simulation")

    sensor_ids = list(BOOTSTRAP_SENSORS.keys())

    try:
        while True:
            sensors_produced = []
            for a in range(5):

                # Generate data for a random sensor
                sensor_id = random.choice(sensor_ids)
                sensors_produced.append(sensor_id)
                reading = generator.generate_sensor_reading(sensor_id)

                if reading:
                    # Publish to Redis
                    payload = json.dumps(reading)
                    redis_client.publish(REDIS_CHANNEL, payload)

                    # Log the reading
                    sensor_type = reading["sensor_type"]
                    room = reading["room"]
                    value_info = ""

                    if "energy" in reading:
                        value_info = f"{reading['energy']['value']} {reading['energy']['unit']}"
                    elif "co2" in reading:
                        value_info = f"{reading['co2']['value']} {reading['co2']['unit']}"
                    elif "temperature" in reading:
                        value_info = f"{reading['temperature']['value']} {reading['temperature']['unit']}"
                    elif "humidity" in reading:
                        value_info = f"{reading['humidity']['value']} {reading['humidity']['unit']}"
                    elif "motion" in reading:
                        value_info = f"{'DETECTED' if reading['motion']['value'] else 'CLEAR'}"

                    logger.info(f"📊 {sensor_id} ({room}/{sensor_type}): {value_info}")

            # Random interval between readings (1-5 seconds)
            time.sleep(random.uniform(1, 5))

    except KeyboardInterrupt:
        logger.info("Stopping data simulation...")
    except Exception as e:
        logger.error(f"Simulation error: {e}")

if __name__ == "__main__":
    main()