from __future__ import annotations

import asyncio
import shutil
import zipfile
from collections.abc import Sequence
from pathlib import Path
from typing import Any

from app.core.exceptions import ProcessingError
from app.models.media import InputMedia, OperationResult
from app.operations.common import execute, output_path, require_inputs, video_codecs
from app.services.ffmpeg_service import FFmpegService
from app.services.validator import bounded_number, positive_int


async def thumbnail(
    ffmpeg: FFmpegService, inputs: Sequence[InputMedia], params: dict[str, Any], output_dir: Path
) -> OperationResult:
    require_inputs(inputs)
    timestamp = bounded_number(params, "timestamp", 0, 0, 86_400)
    output = output_path(output_dir, "thumbnail", "jpg")
    quality = min(31, positive_int(params, "quality", 3))
    return await execute(
        ffmpeg,
        [
            "-ss",
            str(timestamp),
            "-i",
            inputs[0].temp_path,
            "-frames:v",
            "1",
            "-q:v",
            str(quality),
            output,
        ],
        output,
        "video.thumbnail",
        {"timestamp": timestamp},
    )


async def extract_frames(
    ffmpeg: FFmpegService, inputs: Sequence[InputMedia], params: dict[str, Any], output_dir: Path
) -> OperationResult:
    require_inputs(inputs)
    fps = bounded_number(params, "fps", 1, 0.01, 60)
    frame_dir = output_dir / "frames"
    frame_dir.mkdir(parents=True, exist_ok=True)
    frame_pattern = frame_dir / "frame_%06d.jpg"
    args: list[str | Path] = ["-i", inputs[0].temp_path, "-vf", f"fps={fps}", "-q:v", "3"]
    maximum = params.get("max_frames")
    if maximum is not None:
        maximum_value = positive_int(params, "max_frames", 1)
        args += ["-frames:v", str(maximum_value)]
    args += [frame_pattern]
    await ffmpeg.run(args, operation="video.extract_frames")
    frames = sorted(frame_dir.glob("frame_*.jpg"))
    if not frames:
        raise ProcessingError("No frames were extracted")
    archive = output_path(output_dir, "frames", "zip")
    await asyncio.to_thread(_archive_frames, archive, frames)
    await asyncio.to_thread(shutil.rmtree, frame_dir, True)
    return OperationResult(
        path=archive,
        filename=archive.name,
        mime_type="application/zip",
        metadata={"frames": len(frames), "fps": fps},
    )


def _archive_frames(archive: Path, frames: list[Path]) -> None:
    with zipfile.ZipFile(archive, "w", zipfile.ZIP_DEFLATED) as zip_file:
        for frame in frames:
            zip_file.write(frame, frame.name)


async def generate_gif(
    ffmpeg: FFmpegService, inputs: Sequence[InputMedia], params: dict[str, Any], output_dir: Path
) -> OperationResult:
    require_inputs(inputs)
    fps = bounded_number(params, "fps", 10, 1, 30)
    width = positive_int(params, "width", 480)
    output = output_path(output_dir, "animation", "gif")
    palette = output_dir / "palette.png"
    await ffmpeg.run(
        [
            "-i",
            inputs[0].temp_path,
            "-vf",
            f"fps={fps},scale={width}:-1:flags=lanczos,palettegen",
            palette,
        ],
        operation="video.gif.palette",
    )
    await ffmpeg.run(
        [
            "-i",
            inputs[0].temp_path,
            "-i",
            palette,
            "-lavfi",
            f"fps={fps},scale={width}:-1:flags=lanczos[x];[x][1:v]paletteuse",
            output,
        ],
        operation="video.gif",
    )
    palette.unlink(missing_ok=True)
    if not output.is_file() or output.stat().st_size == 0:
        raise ProcessingError("GIF generation did not produce an output")
    return OperationResult(
        path=output,
        filename=output.name,
        mime_type="image/gif",
        metadata={"fps": fps, "width": width},
    )


async def blur_video(
    ffmpeg: FFmpegService, inputs: Sequence[InputMedia], params: dict[str, Any], output_dir: Path
) -> OperationResult:
    require_inputs(inputs)
    strength = min(100, positive_int(params, "strength", 5))
    output = output_path(output_dir, "blurred", "mp4")
    return await execute(
        ffmpeg,
        ["-i", inputs[0].temp_path, "-vf", f"boxblur={strength}:1", *video_codecs("mp4"), output],
        output,
        "video.blur",
        {"strength": strength},
    )


async def sharpen_video(
    ffmpeg: FFmpegService, inputs: Sequence[InputMedia], params: dict[str, Any], output_dir: Path
) -> OperationResult:
    require_inputs(inputs)
    amount = bounded_number(params, "amount", 1.0, 0, 5)
    output = output_path(output_dir, "sharpened", "mp4")
    return await execute(
        ffmpeg,
        [
            "-i",
            inputs[0].temp_path,
            "-vf",
            f"unsharp=5:5:{amount}:5:5:0",
            *video_codecs("mp4"),
            output,
        ],
        output,
        "video.sharpen",
        {"amount": amount},
    )


async def denoise_video(
    ffmpeg: FFmpegService, inputs: Sequence[InputMedia], params: dict[str, Any], output_dir: Path
) -> OperationResult:
    require_inputs(inputs)
    output = output_path(output_dir, "denoised", "mp4")
    return await execute(
        ffmpeg,
        ["-i", inputs[0].temp_path, "-vf", "hqdn3d", *video_codecs("mp4"), output],
        output,
        "video.denoise",
    )