meta-optimizer/backfill.py

"""
Backfill: genera snapshots históricos con análisis Claude para un rango de fechas.

Uso:
    python backfill.py                             # mes en curso → ayer
    python backfill.py --from 2026-06-01 --to 2026-06-04
    python backfill.py --skip-existing             # no reprocesa días ya guardados
"""
import sys
import io
import argparse
sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding="utf-8", line_buffering=True)

from datetime import datetime, timedelta
import config
from meta_ads_client import MetaAdsClient
from agent import decide, analyze_unit
from baserow_client import BaserowClient

_ACTION_MAP = {
    "PAUSE": "PAUSE", "REDUCE_BUDGET": "REDUCE_BUDGET",
    "INCREASE_BUDGET": "INCREASE_BUDGET", "MAINTAIN": "MAINTAIN",
    "REVIEW_CREATIVES": "REVIEW_CREATIVES",
    "PAUSAR": "PAUSE", "REDUCIR_PRESUPUESTO": "REDUCE_BUDGET",
    "AUMENTAR_PRESUPUESTO": "INCREASE_BUDGET", "MANTENER": "MAINTAIN",
    "REVISAR_CREATIVIDADES": "REVIEW_CREATIVES",
}

def _extract_vertical(name: str) -> str:
    prefix = config.META_CAMPAIGN_PREFIX
    rest   = name[len(prefix):].lstrip("_")
    parts  = rest.split("_")
    start  = 1 if parts and parts[0].isdigit() else 0
    return parts[start].lower() if start < len(parts) else "otros"


def run_backfill(date_from: str, date_to: str, skip_existing: bool = False):
    meta    = MetaAdsClient()
    baserow = BaserowClient()

    # Vertical CPL targets
    vertical_cpls: dict = {}
    try:
        for v in baserow.get_all_verticals():
            name = (v.get("Nombre") or "").strip().lower()
            cpl  = float(v.get("target_cpl") or 0)
            if name and cpl:
                vertical_cpls[name] = cpl
    except Exception as e:
        print(f"Warning: could not fetch verticals: {e}")

    # Build date list
    d     = datetime.strptime(date_from, "%Y-%m-%d")
    d_end = datetime.strptime(date_to,   "%Y-%m-%d")
    dates = []
    while d <= d_end:
        dates.append(d.strftime("%Y-%m-%d"))
        d += timedelta(days=1)

    print(f"\n{'='*60}")
    print(f"  BACKFILL  {date_from} → {date_to}  ({len(dates)} días)")
    print(f"{'='*60}\n")

    total_saved = 0
    total_skip  = 0

    for run_date in dates:
        print(f"\n── {run_date} ───────────────────────────────────────────────")

        # Pre-load existing snapshots for this date if skip_existing
        existing_names: set = set()
        if skip_existing:
            try:
                for r in baserow.get_snapshots_for_date(run_date):
                    existing_names.add(r.get("campaign_name", ""))
            except Exception:
                pass

        campaign_metrics = meta.get_campaign_metrics(run_date, run_date)
        if not campaign_metrics:
            print("  Sin campañas con gasto.")
            continue

        print(f"  {len(campaign_metrics)} campañas activas.")

        # Adset bid configs (current — bid strategy doesn't change day to day)
        adset_bids_cache: dict = {}

        for cid, metrics in campaign_metrics.items():
            camp_name = metrics["name"]

            if skip_existing and camp_name in existing_names:
                print(f"  SKIP  {camp_name[:55]}")
                total_skip += 1
                continue

            vertical = _extract_vertical(camp_name)
            max_cpl  = vertical_cpls.get(vertical, config.META_TARGET_CPL) or config.META_TARGET_CPL
            margin   = round((max_cpl - metrics["cpl"]) * metrics["leads"], 2) if metrics["leads"] > 0 else round(-metrics["spend"], 2)

            print(f"  {camp_name[:55]}")
            print(f"    Spend {metrics['spend']}€  Leads {metrics['leads']}  CPL {metrics['cpl']}€  MaxCPL {max_cpl}€  Margen {margin:+.2f}€")

            # ── Claude: decisión ────────────────────────────────────────────
            analysis = {
                "campaign_id": cid, "name": camp_name, "status": "ACTIVE",
                "spend": metrics["spend"], "leads": metrics["leads"],
                "cpl": metrics["cpl"], "max_cpl": max_cpl,
                "ctr": metrics["ctr"], "cpm": metrics["cpm"],
                "impressions": metrics["impressions"], "clicks": metrics["clicks"],
            }
            try:
                decision    = decide(analysis)
                action_type = _ACTION_MAP.get(
                    decision.get("action") or decision.get("accion", "MAINTAIN"),
                    "MAINTAIN",
                )
            except Exception as e:
                print(f"    ERROR decide: {e}")
                decision    = {"action": "MAINTAIN", "justification": "", "parameter": 1.0}
                action_type = "MAINTAIN"

            print(f"    Decision: {action_type} — {(decision.get('justification') or '')[:70]}")

            # ── Claude: adsets ──────────────────────────────────────────────
            adsets_detail = []
            try:
                for as_m in meta.get_adset_metrics(cid, run_date, run_date)[:5]:
                    result = analyze_unit(as_m, "adset")
                    adsets_detail.append({**as_m, **result})
                    print(f"    [Adset] {as_m['name'][:45]} — {result.get('evaluacion','')[:50]}")
            except Exception as e:
                print(f"    ERROR adsets: {e}")

            # Add bid configs (cached per campaign)
            if cid not in adset_bids_cache:
                try:
                    adset_bids_cache[cid] = meta.get_adset_bid_configs(cid)
                except Exception:
                    adset_bids_cache[cid] = {}
            for adset in adsets_detail:
                b = adset_bids_cache[cid].get(adset["id"], {})
                adset["cost_cap_eur"] = b.get("cost_cap_eur")
                adset["bid_strategy"] = b.get("bid_strategy", "")

            # ── Claude: anuncios ────────────────────────────────────────────
            ads_detail = []
            try:
                for ad_m in meta.get_ad_metrics(cid, run_date, run_date)[:5]:
                    result = analyze_unit(ad_m, "ad")
                    ads_detail.append({**ad_m, **result})
                    print(f"    [Ad]    {ad_m['name'][:45]} — {result.get('evaluacion','')[:50]}")
            except Exception as e:
                print(f"    ERROR ads: {e}")

            # ── Guardar snapshot ────────────────────────────────────────────
            try:
                baserow.save_daily_snapshot({
                    "run_date":      run_date,
                    "campaign_id":   cid,
                    "campaign_name": camp_name,
                    "vertical":      vertical,
                    "spend":         metrics["spend"],
                    "leads":         metrics["leads"],
                    "cpl":           metrics["cpl"],
                    "margin":        margin,
                    "action_type":   action_type,
                    "justification": decision.get("justification") or "",
                    "adsets":        adsets_detail,
                    "ads":           ads_detail,
                })
                print(f"    ✓ Snapshot guardado")
                total_saved += 1
            except Exception as e:
                print(f"    ERROR snapshot: {e}")

    print(f"\n{'='*60}")
    print(f"  Backfill completo. Guardados: {total_saved}  Saltados: {total_skip}")
    print(f"{'='*60}\n")


if __name__ == "__main__":
    now           = datetime.now()
    default_from  = f"{now.year}-{now.month:02d}-01"
    default_to    = (now - timedelta(days=1)).strftime("%Y-%m-%d")

    parser = argparse.ArgumentParser(description="Backfill Meta Optimizer snapshots")
    parser.add_argument("--from", dest="date_from", default=default_from,
                        help=f"Fecha inicio YYYY-MM-DD (default: {default_from})")
    parser.add_argument("--to",   dest="date_to",   default=default_to,
                        help=f"Fecha fin YYYY-MM-DD (default: {default_to})")
    parser.add_argument("--skip-existing", action="store_true",
                        help="No reprocesa campañas que ya tienen snapshot ese día")
    args = parser.parse_args()
    run_backfill(args.date_from, args.date_to, args.skip_existing)