"""
ChunkHandler — job handler that wraps the chunker Pipeline.

Downloads source from S3/MinIO, runs FFmpeg chunking pipeline,
uploads mp4 segments + manifest back to S3/MinIO.
"""

import logging
import os
import shutil
import tempfile
from typing import Any, Callable, Dict, Optional

from core.chunker import Pipeline
from core.storage import BUCKET_IN, BUCKET_OUT, download_to_temp, upload_file

from .base import Handler

logger = logging.getLogger(__name__)


class ChunkHandler(Handler):
    """
    Handles chunk processing jobs by delegating to the chunker Pipeline.

    Expected payload keys:
        source_key: str — S3 key of the source file in BUCKET_IN
        chunk_duration: float — seconds per chunk (default: 10.0)
        num_workers: int — concurrent workers (default: 4)
        max_retries: int — retries per chunk (default: 3)
        processor_type: str — "ffmpeg", "checksum", "simulated_decode", "composite"
        queue_size: int — max queue depth (default: 10)
    """

    def process(
        self,
        job_id: str,
        payload: Dict[str, Any],
        progress_callback: Optional[Callable[[int, Dict[str, Any]], None]] = None,
    ) -> Dict[str, Any]:
        source_key = payload["source_key"]
        processor_type = payload.get("processor_type", "ffmpeg")

        logger.info(f"ChunkHandler starting job {job_id}: {source_key}")

        # Download source from S3/MinIO
        tmp_source = download_to_temp(BUCKET_IN, source_key)

        # Create temp output directory for chunks
        tmp_output_dir = tempfile.mkdtemp(prefix=f"chunks-{job_id}-")

        try:
            def event_bridge(event_type: str, data: Dict[str, Any]) -> None:
                """Bridge pipeline events to the job progress callback."""
                if progress_callback and event_type == "pipeline_complete":
                    progress_callback(100, data)
                elif progress_callback and event_type == "chunk_done":
                    total = data.get("total_chunks", 1)
                    if total > 0:
                        pct = min(int((data.get("sequence", 0) + 1) / total * 100), 99)
                        progress_callback(pct, data)

            pipeline = Pipeline(
                source=tmp_source,
                chunk_duration=payload.get("chunk_duration", 10.0),
                num_workers=payload.get("num_workers", 4),
                max_retries=payload.get("max_retries", 3),
                processor_type=processor_type,
                queue_size=payload.get("queue_size", 10),
                event_callback=event_bridge,
                output_dir=tmp_output_dir if processor_type == "ffmpeg" else None,
            )

            result = pipeline.run()

            # Upload chunks + manifest to S3/MinIO
            output_prefix = f"chunks/{job_id}"
            uploaded_files = []

            for chunk_file in result.chunk_files:
                filename = os.path.basename(chunk_file)
                output_key = f"{output_prefix}/{filename}"
                upload_file(chunk_file, BUCKET_OUT, output_key)
                uploaded_files.append(output_key)
                logger.info(f"Uploaded {output_key}")

            # Upload manifest
            manifest_path = os.path.join(tmp_output_dir, "manifest.json")
            if os.path.exists(manifest_path):
                manifest_key = f"{output_prefix}/manifest.json"
                upload_file(manifest_path, BUCKET_OUT, manifest_key)
                uploaded_files.append(manifest_key)
                logger.info(f"Uploaded {manifest_key}")

            return {
                "status": "completed" if result.failed == 0 else "completed_with_errors",
                "total_chunks": result.total_chunks,
                "processed": result.processed,
                "failed": result.failed,
                "retries": result.retries,
                "elapsed_time": result.elapsed_time,
                "throughput_mbps": result.throughput_mbps,
                "worker_stats": result.worker_stats,
                "errors": result.errors,
                "chunks_in_order": result.chunks_in_order,
                "output_prefix": output_prefix,
                "uploaded_files": uploaded_files,
            }

        finally:
            # Cleanup temp files
            try:
                os.unlink(tmp_source)
            except OSError:
                pass
            try:
                shutil.rmtree(tmp_output_dir, ignore_errors=True)
            except OSError:
                pass