"""
Bulk Loader Module

This module provides high-volume data loading capabilities for triplet stores,
enabling efficient batch processing with progress tracking and error recovery.

Key Features:
    - High-volume data loading strategies
    - Batch processing and chunking
    - Progress monitoring and reporting
    - Error handling and recovery with retries
    - Performance optimization
    - Memory management for large datasets
    - Stream-based loading

Main Classes:
    - BulkLoader: Main bulk loading coordinator
    - LoadProgress: Bulk loading progress representation dataclass

Example Usage:
    >>> from semantica.triplet_store import BulkLoader
    >>> loader = BulkLoader(batch_size=1000, max_retries=3)
    >>> progress = loader.load_triplets(triplets, store)
    >>> print(f"Loaded {progress.loaded_triplets}/{progress.total_triplets} triplets")
    >>> validation = loader.validate_before_load(triplets)

Author: Semantica Contributors
License: MIT
"""

import time
from dataclasses import dataclass, field
from datetime import datetime
from typing import Any, Dict, List, Optional

from ..semantic_extract.triplet_extractor import Triplet
from ..utils.exceptions import ProcessingError, ValidationError
from ..utils.logging import get_logger
from ..utils.progress_tracker import get_progress_tracker


@dataclass
class LoadProgress:
    """Bulk loading progress information."""

    total_triplets: int
    loaded_triplets: int
    failed_triplets: int = 0
    current_batch: int = 0
    total_batches: int = 0
    progress_percentage: float = 0.0
    elapsed_time: float = 0.0
    estimated_remaining: Optional[float] = None
    metadata: Dict[str, Any] = field(default_factory=dict)


class BulkLoader:
    """
    High-volume data loading system for triplet stores.

    • High-volume data loading strategies
    • Batch processing and chunking
    • Progress monitoring and reporting
    • Error handling and recovery
    • Performance optimization
    • Memory management for large datasets
    """

    def __init__(self, config: Optional[Dict[str, Any]] = None, **kwargs):
        """
        Initialize bulk loader.

        Args:
            config: Configuration dictionary
            **kwargs: Additional configuration options:
                - batch_size: Batch size for loading (default: 1000)
                - max_retries: Maximum retry attempts (default: 3)
                - retry_delay: Delay between retries in seconds (default: 1.0)
        """
        self.logger = get_logger("bulk_loader")
        self.config = config or {}
        self.config.update(kwargs)
        self.progress_tracker = get_progress_tracker()
        # Ensure progress tracker is enabled
        if not self.progress_tracker.enabled:
            self.progress_tracker.enabled = True

        self.batch_size = self.config.get("batch_size", 1000)
        self.max_retries = self.config.get("max_retries", 3)
        self.retry_delay = self.config.get("retry_delay", 1.0)

    def load_triplets(
        self, triplets: List[Triplet], store: Any, **options
    ) -> LoadProgress:
        """
        Load triplets in bulk.

        Args:
            triplets: List of triplets to load
            store: Triplet store backend instance
            **options: Additional options:
                - batch_size: Override default batch size
                - progress_callback: Callback function for progress updates
                - stop_on_error: Stop loading on first error (default: False)

        Returns:
            Load progress information
        """
        tracking_id = self.progress_tracker.start_tracking(
            module="triplet_store",
            submodule="BulkLoader",
            message=f"Loading {len(triplets)} triplets in bulk",
        )

        try:
            start_time = time.time()
            batch_size = options.get("batch_size", self.batch_size)
            stop_on_error = options.get("stop_on_error", False)
            progress_callback = options.get("progress_callback")

            total_triplets = len(triplets)
            total_batches = (total_triplets + batch_size - 1) // batch_size

            loaded_count = 0
            failed_count = 0

            self.logger.info(
                f"Starting bulk load: {total_triplets} triplets in {total_batches} batches"
            )

            # Process in batches
            for batch_num in range(total_batches):
                batch_start = batch_num * batch_size
                batch_end = min(batch_start + batch_size, total_triplets)
                batch = triplets[batch_start:batch_end]

                # Load batch with retries
                batch_loaded = 0
                for attempt in range(self.max_retries):
                    try:
                        if hasattr(store, "bulk_load"):
                            result = store.bulk_load(batch, **options)
                        elif hasattr(store, "add_triplets"):
                            result = store.add_triplets(batch, **options)
                        else:
                            raise ProcessingError(
                                "Store backend does not support bulk loading"
                            )

                        batch_loaded = len(batch)
                        loaded_count += batch_loaded
                        break

                    except Exception as e:
                        if attempt < self.max_retries - 1:
                            self.logger.warning(
                                f"Batch {batch_num} failed, retrying: {e}"
                            )
                            time.sleep(self.retry_delay * (attempt + 1))
                        else:
                            self.logger.error(
                                f"Batch {batch_num} failed after {self.max_retries} attempts: {e}"
                            )
                            failed_count += len(batch)

                            if stop_on_error:
                                self.progress_tracker.stop_tracking(
                                    tracking_id,
                                    status="failed",
                                    message=f"Bulk load stopped due to error: {e}",
                                )
                                raise ProcessingError(
                                    f"Bulk load stopped due to error: {e}"
                                )

                # Update progress with ETA
                elapsed = time.time() - start_time
                progress = (
                    (loaded_count / total_triplets * 100) if total_triplets > 0 else 0.0
                )
                estimated_remaining = None
                if loaded_count > 0:
                    estimated_remaining = (elapsed / loaded_count) * (
                        total_triplets - loaded_count
                    )

                # Use update_progress for ETA display
                self.progress_tracker.update_progress(
                    tracking_id,
                    processed=loaded_count,
                    total=total_triplets,
                    message=f"Processing batch {batch_num + 1}/{total_batches}..."
                )

                progress_info = LoadProgress(
                    total_triplets=total_triplets,
                    loaded_triplets=loaded_count,
                    failed_triplets=failed_count,
                    current_batch=batch_num + 1,
                    total_batches=total_batches,
                    progress_percentage=progress,
                    elapsed_time=elapsed,
                    estimated_remaining=estimated_remaining,
                    metadata={
                        "batch_size": batch_size,
                        "store_type": store.__class__.__name__,
                    },
                )

                # Call progress callback if provided
                if progress_callback:
                    progress_callback(progress_info)

                self.logger.debug(
                    f"Progress: {progress:.1f}% ({loaded_count}/{total_triplets} triplets)"
                )

            elapsed = time.time() - start_time

            final_progress = LoadProgress(
                total_triplets=total_triplets,
                loaded_triplets=loaded_count,
                failed_triplets=failed_count,
                current_batch=total_batches,
                total_batches=total_batches,
                progress_percentage=100.0,
                elapsed_time=elapsed,
                estimated_remaining=0.0,
                metadata={
                    "success": failed_count == 0,
                    "throughput": loaded_count / elapsed if elapsed > 0 else 0.0,
                },
            )

            self.logger.info(
                f"Bulk load completed: {loaded_count}/{total_triplets} triplets loaded "
                f"in {elapsed:.2f}s ({loaded_count / elapsed:.0f} triplets/sec)"
            )

            self.progress_tracker.stop_tracking(
                tracking_id,
                status="completed",
                message=f"Bulk load completed: {loaded_count}/{total_triplets} triplets loaded",
            )
            return final_progress

        except Exception as e:
            self.progress_tracker.stop_tracking(
                tracking_id, status="failed", message=str(e)
            )
            raise

    def load_from_file(
        self, file_path: str, store_backend: Any, **options
    ) -> LoadProgress:
        """
        Load triplets from file.

        Args:
            file_path: Path to RDF file
            store_backend: Triplet store backend
            **options: Additional options:
                - format: File format (turtle, ntriples, rdfxml)
                - chunk_size: Chunk size for reading large files

        Returns:
            Load progress information
        """
        format = options.get("format", "turtle")
        chunk_size = options.get("chunk_size", 10000)

        # This would parse the file and extract triplets
        # For now, return placeholder
        self.logger.warning(
            "File loading not fully implemented - would parse and load RDF file"
        )

        return LoadProgress(
            total_triplets=0,
            loaded_triplets=0,
            metadata={"file_path": file_path, "format": format},
        )

    def load_from_stream(
        self, triplets_stream: Any, store_backend: Any, **options
    ) -> LoadProgress:
        """
        Load triplets from stream.

        Args:
            triplets_stream: Stream of triplets
            store_backend: Triplet store backend
            **options: Additional options

        Returns:
            Load progress information
        """
        # Collect triplets from stream in batches
        batch = []
        total_loaded = 0

        for triplet in triplets_stream:
            batch.append(triplet)

            if len(batch) >= self.batch_size:
                # Load batch
                progress = self.load_triplets(batch, store_backend, **options)
                total_loaded += progress.loaded_triplets
                batch = []

        # Load remaining triplets
        if batch:
            progress = self.load_triplets(batch, store_backend, **options)
            total_loaded += progress.loaded_triplets

        return LoadProgress(
            total_triplets=total_loaded,
            loaded_triplets=total_loaded,
            metadata={"source": "stream"},
        )

    def validate_before_load(self, triplets: List[Triplet], **options) -> Dict[str, Any]:
        """
        Validate triplets before loading.

        Args:
            triplets: List of triplets to validate
            **options: Validation options

        Returns:
            Validation results
        """
        errors = []
        warnings = []

        # Check for empty triplets
        empty_triplets = [
            t for t in triplets if not t.subject or not t.predicate or not t.object
        ]
        if empty_triplets:
            errors.append(f"{len(empty_triplets)} triplets have empty components")

        # Check for invalid URIs
        invalid_uris = []
        for triplet in triplets:
            if not triplet.subject.startswith("http") and not triplet.subject.startswith(
                "<"
            ):
                invalid_uris.append(f"Subject: {triplet.subject}")
            if not triplet.predicate.startswith(
                "http"
            ) and not triplet.predicate.startswith("<"):
                invalid_uris.append(f"Predicate: {triplet.predicate}")

        if invalid_uris:
            warnings.append(f"{len(invalid_uris)} triplets may have invalid URIs")

        # Check confidence scores
        low_confidence = [t for t in triplets if t.confidence < 0.5]
        if low_confidence:
            warnings.append(f"{len(low_confidence)} triplets have low confidence scores")

        return {
            "valid": len(errors) == 0,
            "errors": errors,
            "warnings": warnings,
            "total_triplets": len(triplets),
            "valid_triplets": len(triplets) - len(empty_triplets),
        }
