"""Streaming CSV detection logger."""

import csv
from pathlib import Path
from typing import TextIO

from .config_loader import DetectionLoggingSettings
from .models import Detection, FrameInfo


class DetectionLogger:
    """Write one CSV row per detection, with optional empty-frame rows."""

    FIELDNAMES = [
        "experiment_id", "frame_number", "timestamp", "elapsed_time_sec", "frame_width", "frame_height",
        "measured_fps", "detection_index", "class_id", "class_name", "confidence", "bbox_x1", "bbox_y1",
        "bbox_x2", "bbox_y2", "bbox_width", "bbox_height", "center_x", "center_y", "foot_x", "foot_y",
        "inside_evaluation_region",
    ]

    def __init__(self, config: DetectionLoggingSettings, experiment_id: str, path: Path) -> None:
        self.config = config
        self.experiment_id = experiment_id
        self.path = path
        self._file: TextIO | None = None
        self._writer: csv.DictWriter[str] | None = None
        self._frames_since_flush = 0

    def open(self) -> None:
        self.path.parent.mkdir(parents=True, exist_ok=True)
        self._file = self.path.open("w", encoding="utf-8-sig", newline="")
        self._writer = csv.DictWriter(self._file, fieldnames=self.FIELDNAMES)
        self._writer.writeheader()

    def log_frame(self, info: FrameInfo, detections: list[Detection]) -> None:
        if self._writer is None:
            return
        base = {
            "experiment_id": self.experiment_id, "frame_number": info.frame_number, "timestamp": info.timestamp_iso,
            "elapsed_time_sec": f"{info.elapsed_time_sec:.6f}", "frame_width": info.width, "frame_height": info.height,
            "measured_fps": f"{info.measured_fps:.3f}",
        }
        if detections:
            for index, detection in enumerate(detections):
                b = detection.bbox
                self._writer.writerow(base | {
                    "detection_index": index, "class_id": detection.class_id, "class_name": detection.class_name,
                    "confidence": f"{detection.confidence:.6f}", "bbox_x1": b.x1, "bbox_y1": b.y1,
                    "bbox_x2": b.x2, "bbox_y2": b.y2, "bbox_width": b.width, "bbox_height": b.height,
                    "center_x": b.center_x, "center_y": b.center_y, "foot_x": b.foot_x, "foot_y": b.foot_y,
                    "inside_evaluation_region": detection.inside_evaluation_region,
                })
        elif self.config.log_empty_frames:
            self._writer.writerow(base)
        self._frames_since_flush += 1
        if self._frames_since_flush >= self.config.flush_interval_frames:
            self._file.flush()
            self._frames_since_flush = 0

    def close(self) -> None:
        if self._file is not None:
            self._file.close()
            self._file = None
            self._writer = None

    def __enter__(self) -> "DetectionLogger":
        self.open()
        return self

    def __exit__(self, *_args: object) -> None:
        self.close()