"""공유 테스트 픽스처.

모든 테스트는 GPU/모델/ffmpeg 없이 mock 기반으로 동작한다:
- ``FakeEngineOwner``: 세그먼트를 즉시 생성 (실제 decode 없음)
- ``FakeIngestor``: ffprobe/ffmpeg 대체
"""

from __future__ import annotations

from pathlib import Path

import pytest

from luke_scribe.config import Settings


class FakeSegments:
    """세그먼트 목록을 반복하는 mock — 취소 시 중단."""

    def __init__(self, segments: list[dict], cancel_on: callable | None = None) -> None:
        self._segs = iter(segments)
        self._cancel_on = cancel_on or (lambda: False)

    def __iter__(self):
        return self

    def __next__(self):
        if self._cancel_on():
            raise StopIteration
        return next(self._segs)

    def close(self) -> None:
        pass


class FakeEngine:
    def __init__(self, segments: list[dict], *, fail_on: list[str] | None = None) -> None:
        self.segments = segments
        self.fail_on = fail_on or []
        self.calls: list[dict] = []

    def transcribe(self, audio_path, options, should_cancel=None, download_progress=None) -> object:
        self.calls.append({"audio": audio_path, "options": options})
        # 실제 faster-whisper를 import하지 않는 mock
        return type(
            "Outcome",
            (),
            {
                "segments": FakeSegments(self.segments, cancel_on=should_cancel),
                "info": {"language": "ko"},
            },
        )()


class FakeEngineOwner:
    """EngineOwner mock — 프로파일 강등/캡을 검증 가능하게 함."""

    def __init__(
        self, engine: FakeEngine | None = None, segments: list[dict] | None = None
    ) -> None:
        self.engine = engine or FakeEngine(segments or _default_segments())
        self.last_request = None

    def transcribe(self, req) -> dict:
        self.last_request = req
        # 실제 EngineOwner처럼 첫 시도 프로파일을 기록 (downgrade_attempts 계산용)
        req.attempted_profiles.append(f"{req.options.device}/{req.options.compute_type or 'int8'}")
        outcome = self.engine.transcribe(
            req.audio_path, req.options, should_cancel=req.should_cancel
        )
        return {
            "segments": outcome.segments,
            "info": outcome.info,
            "device": req.options.device if req.options.device != "auto" else "cpu",
            "compute_type": req.options.compute_type or "int8",
            "attempted_profiles": list(req.attempted_profiles),
        }

    def emit_hypothesis(self, pcm_chunk: bytes) -> dict:
        return {"segments": [], "audio_sec": len(pcm_chunk) / 2 / 16000}

    def unload_all(self) -> None:
        pass


def _default_segments() -> list[dict]:
    return [
        {
            "index": 0,
            "start": 0.0,
            "end": 2.5,
            "text": "오늘 API 서버에서 vLLM을 사용해 보겠습니다.",
            "avg_logprob": -0.2,
            "no_speech_prob": 0.01,
        },
        {
            "index": 1,
            "start": 2.5,
            "end": 4.0,
            "text": "Kubernetes 클러스터에 배포합니다.",
            "avg_logprob": -0.3,
            "no_speech_prob": 0.02,
        },
    ]


class FakeIngestor:
    """ffprobe/ffmpeg 없는 mock ingestor."""

    def __init__(self, duration_sec: float = 10.0, codec: str = "mp3") -> None:
        self.duration_sec = duration_sec
        self.codec = codec
        self.cancelled = False

    def ingest(self, source: Path, *, should_cancel=None):
        if should_cancel and should_cancel():
            from luke_scribe.errors import CancelledError

            self.cancelled = True
            raise CancelledError("취소됨")
        from luke_scribe.audio.ingest import IngestResult, ProbeResult
        from luke_scribe.results.models import NormalizedAudio

        class _Cleanup:
            def close(self):
                pass

        return IngestResult(
            normalized_path="/tmp/fake-normalized.wav",
            normalized=NormalizedAudio(duration_sec=self.duration_sec),
            probe=ProbeResult(duration_sec=self.duration_sec, codec=self.codec, size_bytes=100),
            temp_dir="/tmp/fake-tmp",
            cleanup=lambda: None,
        )


@pytest.fixture
def settings(tmp_path: Path) -> Settings:
    return Settings(
        _env_file=None,
        results_dir=str(tmp_path / "results"),
        api_key_file=str(tmp_path / "api_keys.json"),
        queue_backend="inproc",
        model_cache_dir=None,
        max_queue=10,
    )


@pytest.fixture
def fake_owner() -> FakeEngineOwner:
    return FakeEngineOwner()


@pytest.fixture
def fake_ingestor() -> FakeIngestor:
    return FakeIngestor()


@pytest.fixture
def transcript_result() -> dict:
    return {
        "schema_version": "1.0",
        "status": "completed",
        "source": {"name": "test.mp3", "codec": "mp3", "size_bytes": 100},
        "normalized_audio": {
            "duration_sec": 4.0,
            "audio_format": "pcm_s16le",
            "sample_rate": 16000,
            "channels": 1,
        },
        "execution": {
            "model": "large-v3-turbo",
            "device": "cpu",
            "compute_type": "int8",
            "language_requested": "ko",
        },
        "timings": {"transcription_sec": 0.5, "rtf": 0.125},
        "text": "오늘 API 서버에서 vLLM을 사용해 보겠습니다.",
        "segments": [
            {
                "index": 0,
                "start": 0.0,
                "end": 2.5,
                "text": "오늘 API 서버에서 vLLM을 사용해 보겠습니다.",
                "avg_logprob": -0.2,
                "no_speech_prob": 0.01,
            }
        ],
        "warnings": [],
    }