#!/usr/bin/env python3
"""Reporte de datapoints y score de fiabilidad/completitud por persona en osint.

Para cada ficha personas/<slug>.md calcula:
  - score de completitud: campos de identidad presentes / 7 * 100
    (sexo, fecha_nacimiento, dni, telefono, email, direccion, pais)
  - datapoints totales: campos de identidad presentes + nº documentos + nº attachments + relaciones
  - campos faltantes (cuando el score < 100%)

Salida: tabla ordenada por score asc (las menos fiables primero) + totales globales.
Con --json imprime el detalle como JSON. Read-only.
"""
import sys, os, glob, json

sys.path.insert(0, "/home/enmanuel/fn_registry/python/functions")
from obsidian import read_obsidian_note

OSINT = "/home/enmanuel/Obsidian/osint"
IDENT = ["sexo", "fecha_nacimiento", "dni", "telefono", "email", "direccion", "pais"]


def main():
    as_json = "--json" in sys.argv
    rows = []
    tot_dp = 0
    for fp in sorted(glob.glob(f"{OSINT}/personas/*.md")):
        slug = os.path.splitext(os.path.basename(fp))[0]
        if slug.startswith("_"):
            continue
        fm = read_obsidian_note(fp)["frontmatter"]
        present = [k for k in IDENT if fm.get(k) not in (None, "", [])]
        missing = [k for k in IDENT if k not in present]
        score = round(len(present) / len(IDENT) * 100)
        ndocs = len(glob.glob(f"{OSINT}/personas/{slug}/*.md"))
        natt = len(glob.glob(f"{OSINT}/attachments/personas/{slug}/*"))
        nrel = len(fm.get("relaciones") or [])
        dp = len(present) + ndocs + natt + nrel
        tot_dp += dp
        rows.append({"slug": slug, "score": score, "datapoints": dp,
                     "ident": len(present), "docs": ndocs, "attachments": natt,
                     "relaciones": nrel, "faltan": missing})

    rows.sort(key=lambda r: (r["score"], -r["datapoints"]))
    if as_json:
        print(json.dumps({"total_datapoints": tot_dp, "personas": rows}, ensure_ascii=False, indent=2))
        return

    print(f"PERSONAS: {len(rows)} | datapoints totales: {tot_dp} | "
          f"score medio: {round(sum(r['score'] for r in rows)/len(rows))}%\n")
    print(f"{'persona':38} {'score':>5} {'dp':>4} {'id':>3} {'doc':>4} {'att':>4} {'rel':>4}  faltan")
    print("-" * 100)
    for r in rows:
        flag = "" if r["score"] == 100 else "  <-- " + ",".join(r["faltan"])
        print(f"{r['slug']:38} {r['score']:>4}% {r['datapoints']:>4} {r['ident']:>3} "
              f"{r['docs']:>4} {r['attachments']:>4} {r['relaciones']:>4}{flag}")
    bajo = [r for r in rows if r["score"] < 100]
    print(f"\nfichas por debajo del 100%: {len(bajo)}/{len(rows)} "
          f"({round(len(bajo)/len(rows)*100)}%)")


if __name__ == "__main__":
    main()