"""
Structured JSON artifact export with complete run metadata.

Produces a self-contained JSON document suitable for programmatic
consumption, API integration, and archival.
"""
import json
import os
from datetime import datetime, timezone


def export_json(data, video_meta, engine_config, out_dir):
    """Generate a comprehensive JSON export of the analysis run.

    Args:
        data: Engine result dict (counts, congestion, events, etc.)
        video_meta: dict with filename, fps, frames, duration, resolution, pixels
        engine_config: dict with imgsz, conf, iou, stride, etc.
        out_dir: Output directory path

    Returns:
        Filename string or None
    """
    class_in = data.get("class_in", {})
    class_out = data.get("class_out", {})
    congestion = data.get("congestion", [])
    raw_events = data.get("raw_events", [])
    pcu_data = data.get("pcu", {})
    speed_data = data.get("speed", {})

    # Build events list from raw_events (skip header row)
    events = []
    for row in raw_events[1:]:
        events.append({
            "frame": row[0],
            "timestamp_sec": row[1],
            "vehicle_id": row[2],
            "class_name": row[3],
            "direction": row[4],
        })

    total_in = sum(class_in.values())
    total_out = sum(class_out.values())

    doc = {
        "urbanflow_version": "1.1",
        "generated_at": datetime.now(timezone.utc).isoformat(),
        "video": video_meta,
        "engine": {
            "model": "VehicleNet-Y26s (OpenVINO INT8)",
            "imgsz": engine_config.get("imgsz", 736),
            "conf": engine_config.get("conf", 0.12),
            "iou": engine_config.get("iou", 0.6),
            "stride": engine_config.get("detect_stride", 2),
            "tracker": "ByteTrack (custom)",
            "batch": 2,
        },
        "performance": {
            "processing_time_sec": data.get("processing_time", 0),
            "actual_fps": data.get("actual_fps", 0),
            "speed_vs_realtime": data.get("speed_vs_realtime", 0),
        },
        "counts": {
            "total_in": total_in,
            "total_out": total_out,
            "total": total_in + total_out,
            "per_class_in": {str(k): v for k, v in class_in.items()},
            "per_class_out": {str(k): v for k, v in class_out.items()},
        },
        "pcu": pcu_data,
        "speed_distribution": speed_data.get("distribution", {}),
        "congestion": {
            "peak": max(congestion) if congestion else 0,
            "average": round(sum(congestion) / len(congestion), 1) if congestion else 0,
            "timeline": congestion,
        },
        "flow_times": data.get("flow_times", []),
        "events": events,
    }

    path = os.path.join(out_dir, "analysis.json")
    with open(path, "w") as f:
        json.dump(doc, f, indent=2, default=str)

    return "analysis.json"