#!/usr/bin/env python3
"""
CLI entry point for disk-checker.

Usage:
    python -m disk_checker scan_latency.csv
    disk-checker scan_latency.csv --metric read_clat --unit ms
"""

import argparse
import sys
from pathlib import Path

from disk_checker.core.extractor import load_latency_csv
from disk_checker.core.helpers import percentile_table
from disk_checker.plotting.plots import generate_plot


def main():
    parser = argparse.ArgumentParser(
        description="Plot fio json+ wide-format latency CSV."
    )
    parser.add_argument("csv", help="CSV from fio_jsonplus_clat2csv")
    parser.add_argument("--metric", default=None,
                       help="Metric to plot (e.g. read_clat). "
                            "If omitted, the metric with the most I/Os is used.")
    parser.add_argument("--all-metrics", action="store_true",
                       help="Plot every metric that has data")
    parser.add_argument("--unit", choices=["ns", "us", "ms", "s"], default="us",
                       help="X-axis latency unit (default: us)")
    parser.add_argument("--log-y", action="store_true")
    parser.add_argument("--log-x", action="store_true")
    parser.add_argument("--cdf", action="store_true",
                       help="Add a CDF subplot below the histogram")
    parser.add_argument("--cdf-only", action="store_true")
    parser.add_argument("--normalize", action="store_true",
                       help="Normalize histogram to a probability density")
    parser.add_argument("--percentiles", default="50,90,99,99.9,99.99")
    parser.add_argument("--no-percentiles", action="store_true")
    parser.add_argument("--output", "-o", default=None)
    parser.add_argument("--dpi", type=int, default=150)
    parser.add_argument("--title", default="")
    parser.add_argument("--show", action="store_true")
    args = parser.parse_args()

    if not Path(args.csv).is_file():
        sys.exit(f"error: file not found: {args.csv}")

    df = load_latency_csv(args.csv)
    if df.empty:
        sys.exit("error: no latency data in CSV")

    available = sorted(df["metric"].unique())
    print("Metrics with data:", ", ".join(available))

    if args.all_metrics:
        metrics = available
    elif args.metric:
        if args.metric not in available:
            sys.exit(f"error: metric {args.metric!r} not in {available}")
        metrics = [args.metric]
    else:
        totals = df.groupby("metric")["count"].sum().sort_values(ascending=False)
        metrics = [totals.index[0]]
        print(f"Auto-selected metric: {metrics[0]}")

    output = args.output or f"{Path(args.csv).stem}_latency.png"
    generate_plot(
        df=df,
        metrics=metrics,
        output_path=Path(output),
        unit=args.unit,
        log_y=args.log_y,
        log_x=args.log_x,
        normalize=args.normalize,
        show_cdf=args.cdf,
        cdf_only=args.cdf_only,
        title=args.title,
        dpi=args.dpi,
    )
    print(f"Saved plot to {output}")

    if not args.no_percentiles:
        try:
            pcts = [float(x) for x in args.percentiles.split(",") if x.strip()]
        except ValueError:
            sys.exit("error: --percentiles must be comma-separated numbers")
        for m in metrics:
            print(percentile_table(df, m, args.unit, pcts))

    if args.show:
        import matplotlib.pyplot as plt
        plt.show()


if __name__ == "__main__":
    main()