import logging

from fastapi import HTTPException, UploadFile

from common.db.run import select_run
from common.db.file_data import insert_file, select_run_files, select_file, delete_file
from integrations.azure_blob import AzureBlobUploader
from models.file import FileListItem, FileType, FileUploadResponse

logger = logging.getLogger(__name__)

_MAX_UPLOAD_BYTES = 50 * 1024 * 1024  # 50MB


async def upload_file_to_blob(
    content: bytes,
    file_name: str,
    group: str,
    category: str = "file",
    content_type: str | None = None,
) -> str:
    """Azure Blob에 파일을 업로드하고 public URL을 반환. DB는 건드리지 않음."""
    uploader = AzureBlobUploader(group=group, category=category)
    return await uploader.upload_bytes(content=content, file_name=file_name, content_type=content_type)


async def upload_analysis_file(
    analysis_run_id: str,
    content: bytes,
    file_name: str,
    file_type: str = "file",
    content_type: str | None = None,
) -> tuple[int, str]:
    """analysis_run에 딸린 파일 업로드. Blob 업로드 + file_data row 생성. (file_id, url) 반환."""
    run = await select_run(analysis_run_id)
    if not run:
        raise HTTPException(status_code=404, detail="analysis_run not found")
    hospital_id = run["hospital_id"]

    public_url = await upload_file_to_blob(
        content=content,
        file_name=file_name,
        group=analysis_run_id,
        category=file_type,
        content_type=content_type,
    )

    file_id = await insert_file(
        analysis_run_id=analysis_run_id,
        hospital_id=hospital_id,
        file_type=file_type,
        file_name=file_name,
        file_url=public_url,
        size_bytes=len(content),
    )
    logger.info("uploaded analysis file run=%s file_id=%s url=%s", analysis_run_id, file_id, public_url)
    return file_id, public_url


async def list_analysis_files(analysis_run_id: str) -> list[dict]:
    """analysis_run에 딸린 (삭제 안 된) 파일 목록."""
    return await select_run_files(analysis_run_id)


async def handle_analysis_file_upload(
    analysis_run_id: str,
    upload: UploadFile,
    file_type: FileType,
) -> FileUploadResponse:
    """multipart UploadFile 검증 + 업로드 + 응답 모델 생성."""
    if not upload.filename:
        raise HTTPException(status_code=400, detail="filename is required")
    content = await upload.read()
    if not content:
        raise HTTPException(status_code=400, detail="empty file")
    if len(content) > _MAX_UPLOAD_BYTES:
        raise HTTPException(status_code=413, detail=f"file too large (max {_MAX_UPLOAD_BYTES} bytes)")

    file_id, public_url = await upload_analysis_file(
        analysis_run_id=analysis_run_id,
        content=content,
        file_name=upload.filename,
        file_type=file_type.value,
        content_type=upload.content_type,
    )
    return FileUploadResponse(
        id=file_id,
        analysis_run_id=analysis_run_id,
        file_type=file_type,
        file_name=upload.filename,
        file_url=public_url,
        size_bytes=len(content),
    )


async def get_analysis_files_response(analysis_run_id: str) -> list[FileListItem]:
    """run 존재 확인 + 응답 모델 생성."""
    if not await select_run(analysis_run_id):
        raise HTTPException(status_code=404, detail="analysis_run not found")
    rows = await list_analysis_files(analysis_run_id)
    return [FileListItem(**{**r, "created_at": str(r["created_at"])}) for r in rows]


async def soft_delete_analysis_file(analysis_run_id: str, file_id: int) -> None:
    """analysis_run에 딸린 파일을 소프트 삭제. 멱등성 보장."""
    row = await select_file(file_id, analysis_run_id)
    if not row:
        raise HTTPException(status_code=404, detail="file not found")
    await delete_file(file_id)
    logger.info("soft-deleted analysis file run=%s file_id=%s", analysis_run_id, file_id)