"""
Lines Dataset Visualizer - Flask app to visualize line segments on cropped P&ID images
Supports train/validation/test splits.
"""

import json
from flask import Flask, render_template, jsonify, send_from_directory
from pathlib import Path

app = Flask(__name__)

# Configuration
BASE_DIR = Path(__file__).parent.parent
SPLITS = ["train", "validation", "test"]

# Cache for metadata per split
_metadata_cache = {}


def get_split_dir(split: str) -> Path:
    """Get the directory for a split."""
    return BASE_DIR / split


def load_metadata(split: str):
    """Load all metadata from the jsonl file for a split."""
    if split in _metadata_cache:
        return _metadata_cache[split]
    
    split_dir = get_split_dir(split)
    metadata_file = split_dir / "metadata.jsonl"
    
    if not metadata_file.exists():
        print(f"Metadata file not found: {metadata_file}")
        _metadata_cache[split] = []
        return []
    
    metadata = []
    with open(metadata_file, 'r') as f:
        for line in f:
            if line.strip():
                metadata.append(json.loads(line))
    
    _metadata_cache[split] = metadata
    return metadata


def get_available_splits():
    """Get list of available splits that have data."""
    available = []
    for split in SPLITS:
        split_dir = get_split_dir(split)
        if split_dir.exists() and (split_dir / "metadata.jsonl").exists():
            available.append(split)
    return available


def get_sample_count(split: str):
    """Get total number of samples in a split."""
    return len(load_metadata(split))


def get_sample(split: str, idx: int) -> dict:
    """Get a single sample by index from a split."""
    metadata = load_metadata(split)
    if 0 <= idx < len(metadata):
        return metadata[idx]
    return None


def get_pipelines_in_sample(sample: dict) -> list:
    """Get unique pipelines in a sample."""
    pipelines = sample.get("lines", {}).get("pipelines", [])
    unique = sorted(set(p for p in pipelines if p))
    return unique


@app.route("/")
def index():
    """Serve the main page."""
    return render_template("index.html")


@app.route("/api/splits")
def get_splits():
    """Get available splits with their sample counts."""
    splits = get_available_splits()
    split_info = []
    for split in splits:
        metadata = load_metadata(split)
        total_lines = sum(len(m.get("lines", {}).get("segments", [])) for m in metadata)
        split_info.append({
            "name": split,
            "sample_count": len(metadata),
            "line_count": total_lines
        })
    return jsonify({"splits": split_info})


@app.route("/api/stats")
def get_stats():
    """Get overall dataset statistics."""
    total_samples = 0
    total_lines = 0
    solid_count = 0
    dashed_count = 0
    source_images = set()
    
    for split in get_available_splits():
        metadata = load_metadata(split)
        total_samples += len(metadata)
        
        for m in metadata:
            source_images.add(m.get("source_image_idx", 0))
            lines_data = m.get("lines", {})
            segments = lines_data.get("segments", [])
            line_types = lines_data.get("line_types", [])
            
            total_lines += len(segments)
            solid_count += sum(1 for t in line_types if t == "solid")
            dashed_count += sum(1 for t in line_types if t == "dashed")
    
    return jsonify({
        "total_samples": total_samples,
        "total_lines": total_lines,
        "source_images": len(source_images),
        "solid_lines": solid_count,
        "dashed_lines": dashed_count
    })


@app.route("/api/<split>/stats")
def get_split_stats(split):
    """Get statistics for a specific split."""
    if split not in get_available_splits():
        return jsonify({"error": "Split not found"}), 404
    
    metadata = load_metadata(split)
    total_lines = sum(len(m.get("lines", {}).get("segments", [])) for m in metadata)
    
    solid_count = 0
    dashed_count = 0
    source_images = set()
    
    for m in metadata:
        source_images.add(m.get("source_image_idx", 0))
        line_types = m.get("lines", {}).get("line_types", [])
        solid_count += sum(1 for t in line_types if t == "solid")
        dashed_count += sum(1 for t in line_types if t == "dashed")
    
    return jsonify({
        "split": split,
        "total_samples": len(metadata),
        "total_lines": total_lines,
        "source_images": len(source_images),
        "solid_lines": solid_count,
        "dashed_lines": dashed_count
    })


@app.route("/api/<split>/samples")
def get_all_samples(split):
    """Get list of all sample indices and basic info for a split."""
    if split not in get_available_splits():
        return jsonify({"error": "Split not found"}), 404
    
    metadata = load_metadata(split)
    samples = []
    for idx, m in enumerate(metadata):
        samples.append({
            "idx": idx,
            "file_name": m.get("file_name"),
            "source_image_idx": m.get("source_image_idx"),
            "width": m.get("width"),
            "height": m.get("height"),
            "line_count": len(m.get("lines", {}).get("segments", []))
        })
    return jsonify({"samples": samples, "count": len(samples)})


@app.route("/api/<split>/sample/<int:idx>")
def get_sample_data(split, idx):
    """Get detailed data for a single sample."""
    if split not in get_available_splits():
        return jsonify({"error": "Split not found"}), 404
    
    sample = get_sample(split, idx)
    if sample is None:
        return jsonify({"error": "Sample not found"}), 404
    
    lines_data = sample.get("lines", {})
    segments = lines_data.get("segments", [])
    line_types = lines_data.get("line_types", [])
    pipelines = lines_data.get("pipelines", [])
    
    # Build detailed line list
    lines = []
    for i, seg in enumerate(segments):
        lines.append({
            "idx": i,
            "segment": seg,
            "type": line_types[i] if i < len(line_types) else "solid",
            "pipeline": pipelines[i] if i < len(pipelines) else ""
        })
    
    return jsonify({
        "file_name": sample.get("file_name"),
        "source_image_idx": sample.get("source_image_idx"),
        "crop_idx": sample.get("crop_idx"),
        "width": sample.get("width"),
        "height": sample.get("height"),
        "lines": lines,
        "line_count": len(lines),
        "unique_pipelines": get_pipelines_in_sample(sample)
    })


@app.route("/images/<split>/<path:filename>")
def serve_image(split, filename):
    """Serve images from a split directory."""
    split_dir = get_split_dir(split)
    return send_from_directory(split_dir, filename)


if __name__ == "__main__":
    print("Starting Lines Dataset Visualizer...")
    print(f"Base directory: {BASE_DIR}")
    
    available_splits = get_available_splits()
    print(f"Available splits: {available_splits}")
    
    for split in available_splits:
        count = get_sample_count(split)
        print(f"  {split}: {count} samples")
    
    app.run(debug=True, port=5051)