#!/usr/bin/env python3 """ build_artifact.py — собирает Live HTML-дашборд из insights.json + funnel_raw.json. Структура: - inline JSON в

Утренний отчёт WB · {{TARGET_DATE}}

Бейзлайн: 7 дней. Анализ обновляется при каждом запуске.

🔴 Просадки

🟢 Росты

⚠️ OOS-кандидаты

Методология и фильтры 









"""


def attach_history_14d(insights: dict[str, Any], funnel: dict[str, Any]) -> None:
    """Прикрепляем к каждому SKU историю за N дней для sparkline.
    Передаём ТОЛЬКО {date, orderCount} — sparkline рисует одну линию, остальные поля
    раздували бы payload в 10x без всякой пользы для UI."""
    by_nm = funnel.get("by_nm", {})
    for section in ("drops", "growths", "oos_candidates"):
        for s in insights.get(section, []):
            nm = str(s["nmID"])
            dates = (by_nm.get(nm) or {}).get("dates", {}) or {}
            sorted_items = sorted(dates.items())[-14:]
            s["history_14d"] = [
                {"date": d, "orderCount": vals.get("orderCount", 0)}
                for d, vals in sorted_items
            ]


def slim_insights_for_html(insights: dict[str, Any]) -> dict[str, Any]:
    """Отрезаем поля, которые HTML не использует: ok_skus (только в Excel), skipped (только в Excel),
    raw history полей кроме orderCount, лишние ключи enrichment."""
    SECTION_KEEP = ("drops", "growths", "oos_candidates")

    def slim_sku(s: dict[str, Any]) -> dict[str, Any]:
        # Урезаем today/baseline до набора метрик, которые реально использует UI
        keep_metrics = (
            "openCount", "cartCount", "orderCount", "orderSum", "buyoutCount",
            "addToCartConversion", "cartToOrderConversion", "buyoutPercent",
        )
        out = {
            "nmID": s.get("nmID"),
            "card": s.get("card"),
            "category": s.get("category"),
            "first_break": s.get("first_break"),
            "today": {k: (s.get("today") or {}).get(k) for k in keep_metrics},
            "baseline": {k: (s.get("baseline") or {}).get(k) for k in keep_metrics},
            "deltas": s.get("deltas"),
            "enrichment": s.get("enrichment"),
            "history_14d": s.get("history_14d"),
        }
        return out

    slim = {
        "target_date": insights.get("target_date"),
        "baseline_dates": insights.get("baseline_dates"),
        "settings_used": insights.get("settings_used"),
        "account_overview": insights.get("account_overview"),
        "totals": insights.get("totals"),
    }
    for sec in SECTION_KEEP:
        slim[sec] = [slim_sku(s) for s in insights.get(sec, [])]
    return slim


def main() -> int:
    p = argparse.ArgumentParser()
    p.add_argument("--insights", required=True)
    p.add_argument("--funnel", required=True)
    p.add_argument("--output", required=True)
    args = p.parse_args()

    with open(args.insights, encoding="utf-8") as f:
        insights = json.load(f)
    with open(args.funnel, encoding="utf-8") as f:
        funnel = json.load(f)

    attach_history_14d(insights, funnel)
    slim = slim_insights_for_html(insights)

    # КОМПАКТНЫЙ JSON для inline — separators без пробелов экономит ~30% размера
    data_json = json.dumps(slim, ensure_ascii=False, separators=(",", ":"))
    html = HTML_TEMPLATE \
        .replace("{{TARGET_DATE}}", insights["target_date"]) \
        .replace("{{DATA_JSON}}", data_json)
    with open(args.output, "w", encoding="utf-8") as f:
        f.write(html)
    print(f"[artifact] saved {args.output} (inline JSON: {len(data_json):,} bytes)", file=sys.stderr)
    return 0


if __name__ == "__main__":
    sys.exit(main())