"""
Training Progress Tracker
Manages progress calculation for parallel product training (20-80% range)
"""

import asyncio
import structlog
from typing import Optional
from datetime import datetime, timezone

from app.services.training_events import publish_product_training_completed
from app.utils.time_estimation import calculate_estimated_completion_time
from app.core.training_constants import (
    PROGRESS_TRAINING_RANGE_START,
    PROGRESS_TRAINING_RANGE_END,
    PROGRESS_TRAINING_RANGE_WIDTH
)

logger = structlog.get_logger()


class ParallelProductProgressTracker:
    """
    Tracks parallel product training progress and emits events.

    For N products training in parallel:
    - Each product completion contributes 60/N% to overall progress
    - Progress range: 20% (after data analysis) to 80% (before completion)
    - Thread-safe for concurrent product trainings
    - Calculates time estimates based on elapsed time and progress
    """

    def __init__(self, job_id: str, tenant_id: str, total_products: int):
        self.job_id = job_id
        self.tenant_id = tenant_id
        self.total_products = max(total_products, 1)  # Ensure at least 1 to avoid division by zero
        self.products_completed = 0
        self._lock = asyncio.Lock()
        self.start_time = datetime.now(timezone.utc)

        # Calculate progress increment per product
        # Training range (from PROGRESS_TRAINING_RANGE_START to PROGRESS_TRAINING_RANGE_END) divided by number of products
        self.progress_per_product = PROGRESS_TRAINING_RANGE_WIDTH / self.total_products if self.total_products > 0 else 0

        if total_products == 0:
            logger.warning("ParallelProductProgressTracker initialized with zero products",
                          job_id=job_id)

        logger.info("ParallelProductProgressTracker initialized",
                   job_id=job_id,
                   total_products=self.total_products,
                   progress_per_product=f"{self.progress_per_product:.2f}%")

    async def mark_product_completed(self, product_name: str) -> int:
        """
        Mark a product as completed and publish event with time estimates.
        Returns the current overall progress percentage.
        """
        async with self._lock:
            self.products_completed += 1
            current_progress = self.products_completed

        # Calculate time estimates based on elapsed time and progress
        elapsed_seconds = (datetime.now(timezone.utc) - self.start_time).total_seconds()
        products_remaining = self.total_products - current_progress

        # Calculate estimated time remaining
        # Avg time per product * remaining products
        estimated_time_remaining_seconds = None
        estimated_completion_time = None

        if current_progress > 0 and products_remaining > 0:
            avg_time_per_product = elapsed_seconds / current_progress
            estimated_time_remaining_seconds = int(avg_time_per_product * products_remaining)

            # Calculate estimated completion time
            estimated_duration_minutes = estimated_time_remaining_seconds / 60
            completion_datetime = calculate_estimated_completion_time(estimated_duration_minutes)
            estimated_completion_time = completion_datetime.isoformat()

        # Publish product completion event with time estimates
        await publish_product_training_completed(
            job_id=self.job_id,
            tenant_id=self.tenant_id,
            product_name=product_name,
            products_completed=current_progress,
            total_products=self.total_products,
            estimated_time_remaining_seconds=estimated_time_remaining_seconds,
            estimated_completion_time=estimated_completion_time
        )

        # Calculate overall progress (PROGRESS_TRAINING_RANGE_START% base + progress from completed products)
        # This calculation is done on the frontend/consumer side based on the event data
        if self.total_products > 0:
            overall_progress = PROGRESS_TRAINING_RANGE_START + int((current_progress / self.total_products) * PROGRESS_TRAINING_RANGE_WIDTH)
        else:
            overall_progress = PROGRESS_TRAINING_RANGE_START

        logger.info("Product training completed",
                   job_id=self.job_id,
                   product_name=product_name,
                   products_completed=current_progress,
                   total_products=self.total_products,
                   overall_progress=overall_progress,
                   estimated_time_remaining_seconds=estimated_time_remaining_seconds)

        return overall_progress

    def get_progress(self) -> dict:
        """Get current progress summary"""
        if self.total_products > 0:
            progress_percentage = PROGRESS_TRAINING_RANGE_START + int((self.products_completed / self.total_products) * PROGRESS_TRAINING_RANGE_WIDTH)
        else:
            progress_percentage = PROGRESS_TRAINING_RANGE_START

        return {
            "products_completed": self.products_completed,
            "total_products": self.total_products,
            "progress_percentage": progress_percentage
        }