leads-optimizer/backfill_games_mayo.py
José Manuel Gómez bdc0d5ede3 Add GAMes table and daily margin table in Slack
- GAMes: new Airtable table aggregating daily fco_ metrics (coste, ingreso_sum, ingreso_lxp, leads, leads_lake)
- run.py: accumulate fco_ daily aggregate and write to GAMes each run
- slack_reporter.py: replace sparkline with daily margin % table (Sumatorio + LeadsxPPL per day)
- backfill_games_mayo.py: populated GAMes with all 17 existing May days

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-18 11:44:18 +02:00

74 lines
2.5 KiB
Python

"""
Script one-off: crea el registro de mayo 2026 en GAMes y rellena MetricasDiarias
con el agregado diario de todas las campañas fco_ a partir de GACampaignMes.
Ejecutar una sola vez:
python backfill_games_mayo.py
"""
import json
from airtable_client import AirtableClient
at = AirtableClient()
MES = 5
ANIO = 2026
print("Cargando registros GACampaignMes de mayo (campañas fco_)...")
records = at.gacampaignmes.all(
formula="AND({Mes}='5',{Año}='2026')",
fields=["CampaignID", "MetricasDiarias", "Campaign Name (from CampaignID)"],
)
campaigns_records = at.campaigns.all(fields=["CampaignID", "PPL"])
at_id_to_info = {
r["id"]: {
"gid": str(r["fields"].get("CampaignID", "")).strip(),
"ppl": float(r["fields"].get("PPL", 0) or 0),
}
for r in campaigns_records
}
# Agregar métricas por día para campañas fco_
daily_agg: dict[str, dict] = {}
for r in records:
at_cids = r["fields"].get("CampaignID", [])
if not at_cids:
continue
info = at_id_to_info.get(at_cids[0], {})
ppl = info.get("ppl", 0)
campaign_names = r["fields"].get("Campaign Name (from CampaignID)", [])
campaign_name = (campaign_names[0] if campaign_names else "").lower()
if not campaign_name.startswith("fco_"):
continue
try:
md = json.loads(r["fields"].get("MetricasDiarias") or "{}")
except (json.JSONDecodeError, TypeError):
md = {}
for day_str, vals in md.items():
if day_str not in daily_agg:
daily_agg[day_str] = {"coste": 0.0, "ingreso_sum": 0.0, "ingreso_lxp": 0.0, "leads": 0, "leads_lake": 0}
daily_agg[day_str]["coste"] += vals.get("coste", 0)
daily_agg[day_str]["ingreso_sum"] += vals.get("ingreso", 0)
daily_agg[day_str]["ingreso_lxp"] += vals.get("leads_lake", 0) * ppl
daily_agg[day_str]["leads"] += int(vals.get("leads", 0))
daily_agg[day_str]["leads_lake"] += int(vals.get("leads_lake", 0))
print(f" > Dias agregados: {sorted(daily_agg.keys())}")
# Redondear
for d in daily_agg:
daily_agg[d] = {k: round(v, 2) if isinstance(v, float) else v for k, v in daily_agg[d].items()}
print("Creando/obteniendo registro GAMes de mayo 2026...")
games_rid = at.get_or_create_games_record(MES, ANIO)
print(f" > Record ID: {games_rid}")
print("Guardando MetricasDiarias en GAMes...")
at.update_games_metricas(games_rid, json.dumps(daily_agg, ensure_ascii=False))
print(f"OK Backfill GAMes completado: {len(daily_agg)} dias guardados.")