from __future__ import annotations

import json
import time
from contextlib import contextmanager
from datetime import datetime, timezone
from pathlib import Path
from typing import Iterator

from app.config import settings


@contextmanager
def measure_pipeline_phase(
    phase: str,
    *,
    source_id: int | None = None,
    dataset_id: int | None = None,
    metadata: dict[str, object] | None = None,
) -> Iterator[dict[str, object]]:
    start = time.perf_counter()
    payload: dict[str, object] = dict(metadata or {})
    try:
        yield payload
    finally:
        duration = round(time.perf_counter() - start, 3)
        payload["duration_seconds"] = duration
        record_pipeline_metric(
            phase,
            source_id=source_id,
            dataset_id=dataset_id,
            duration_seconds=duration,
            metadata=payload,
        )


def record_pipeline_metric(
    phase: str,
    *,
    source_id: int | None = None,
    dataset_id: int | None = None,
    duration_seconds: float | None = None,
    metadata: dict[str, object] | None = None,
) -> None:
    path = _metric_path()
    path.parent.mkdir(parents=True, exist_ok=True)
    row = {
        "timestamp": datetime.now(timezone.utc).isoformat(),
        "phase": phase,
        "source_id": source_id,
        "dataset_id": dataset_id,
        "duration_seconds": duration_seconds,
        "metadata": metadata or {},
    }
    with path.open("a", encoding="utf-8") as handle:
        handle.write(json.dumps(row, separators=(",", ":"), default=str))
        handle.write("\n")


def _metric_path() -> Path:
    return settings.data_dir / "metrics" / "pipeline_metrics.jsonl"