Add daily leads count per campaign to MetricasDiarias

- Fetch leads from Airtable per campaign on yesterday's date before second pass
- Include 'leads' field in MetricasDiarias JSON alongside coste/ingreso/margen
- Add get_leads_by_campaign_on_date() bulk fetch in AirtableClient
- Add backfill_leads_mayo.py one-off script (already executed for days 01-03)
- Fix UnboundLocalError: remove duplicate local timedelta import inside run()

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

airtable_client.py

@@ -1,6 +1,7 @@
 from pyairtable import Api
-from datetime import datetime
+from datetime import datetime, timedelta
 import json
+import re
 import config
 
 
@@ -363,6 +364,32 @@ class AirtableClient:
         ids = [r["id"] for r in records]
         return len(ids), ids
 
+    def get_leads_by_campaign_on_date(self, date_str: str) -> dict:
+        """
+        Devuelve {google_campaign_id: count} para todos los leads de un día concreto.
+        Una sola llamada bulk para todos los campañas — más eficiente que una por campaña.
+        date_str: 'YYYY-MM-DD'
+        """
+        next_day = (datetime.strptime(date_str, "%Y-%m-%d") + timedelta(days=1)).strftime("%Y-%m-%d")
+        formula = f"AND({{creado}}>='{date_str}',{{creado}}<'{next_day}')"
+        records = self.leads.all(
+            formula=formula,
+            fields=["GACampaignID", "GoogleCampaignID", "attr_referer"],
+        )
+        counts: dict[str, int] = {}
+        for r in records:
+            f = r["fields"]
+            cid = str(f.get("GACampaignID") or "").strip()
+            if not cid:
+                cid = str(f.get("GoogleCampaignID") or "").strip()
+            if not cid:
+                m = re.search(r"gad_campaignid=(\d+)", f.get("attr_referer", ""))
+                if m:
+                    cid = m.group(1)
+            if cid:
+                counts[cid] = counts.get(cid, 0) + 1
+        return counts
+
     def update_gacampaignmes_leads_lake(self, gcm_record_id: str, lead_ids: list[str]) -> None:
         """Actualiza el campo 'Leads Lake' de un registro GACampaignMes."""
         self.gacampaignmes.update(gcm_record_id, {"Leads Lake": lead_ids})

backfill_leads_mayo.py

@@ -0,0 +1,79 @@
+"""
+Script one-off: rellena el campo 'leads' en MetricasDiarias para cada día
+de mayo ya registrado en GACampaignMes.
+
+Ejecutar una sola vez:
+    python backfill_leads_mayo.py
+"""
+import json
+from datetime import datetime, timedelta
+from airtable_client import AirtableClient
+
+at = AirtableClient()
+now = datetime.now()
+
+print("Cargando registros GACampaignMes de mayo...")
+records = at.gacampaignmes.all(
+    formula="AND({Mes}='5',{Año}='2026')",
+    fields=["CampaignID", "MetricasDiarias", "Campaign Name (from CampaignID)"],
+)
+
+# Mapping google_campaign_id → (gcm_record_id, metricas_dict)
+gid_to_gcm: dict[str, tuple[str, dict]] = {}
+campaigns_records = at.campaigns.all(fields=["CampaignID"])
+at_id_to_gid = {r["id"]: str(r["fields"].get("CampaignID", "")).strip() for r in campaigns_records}
+
+for r in records:
+    at_cids = r["fields"].get("CampaignID", [])
+    if not at_cids:
+        continue
+    gid = at_id_to_gid.get(at_cids[0], "")
+    if not gid:
+        continue
+    try:
+        md = json.loads(r["fields"].get("MetricasDiarias") or "{}")
+    except (json.JSONDecodeError, TypeError):
+        md = {}
+    gid_to_gcm[gid] = (r["id"], md)
+
+# Días de mayo que ya tienen métricas (sin 'leads')
+days_needed: set[str] = set()
+for _, (_, md) in gid_to_gcm.items():
+    for day_str, vals in md.items():
+        if "leads" not in vals:
+            days_needed.add(day_str)
+
+if not days_needed:
+    print("Todos los días ya tienen 'leads'. Nada que hacer.")
+    exit(0)
+
+print(f"Días a rellenar: {sorted(days_needed)}")
+
+# Para cada día, obtener leads bulk
+for day_str in sorted(days_needed):
+    try:
+        day_int = int(day_str)
+        date = datetime(now.year, 5, day_int)
+    except ValueError:
+        continue
+    date_iso = date.strftime("%Y-%m-%d")
+    print(f"  > {date_iso} ...", end=" ", flush=True)
+    leads_by_cid = at.get_leads_by_campaign_on_date(date_iso)
+    updated = 0
+    for gid, (gcm_id, md) in gid_to_gcm.items():
+        if day_str in md and "leads" not in md[day_str]:
+            md[day_str]["leads"] = leads_by_cid.get(gid, 0)
+            updated += 1
+    print(f"{updated} campañas actualizadas")
+
+# Guardar en Airtable en lotes
+print("\nGuardando en Airtable...")
+batch = [
+    {"id": gcm_id, "fields": {"MetricasDiarias": json.dumps(md, ensure_ascii=False)}}
+    for _, (gcm_id, md) in gid_to_gcm.items()
+    if any("leads" in v for v in md.values())
+]
+for i in range(0, len(batch), 10):
+    at.gacampaignmes.batch_update(batch[i:i+10])
+
+print(f"✓ Backfill completado: {len(batch)} registros actualizados.")

run.py

@@ -12,7 +12,7 @@ from agent import decide
 from optimizer import apply_decision
 from slack_reporter import build_and_send
 import config
-from datetime import datetime
+from datetime import datetime, timedelta
 
 
 class Tee:
@@ -100,6 +100,8 @@ def run():
     google_campaigns = gads.get_all_campaigns()
     monthly_metrics = gads.get_monthly_metrics_all()
     today_metrics   = gads.get_yesterday_metrics_all()
+    _ayer_date      = (datetime.now() - timedelta(days=1))
+    leads_yesterday = at.get_leads_by_campaign_on_date(_ayer_date.strftime("%Y-%m-%d"))
     print("  Calculando PPL y CapTotalMes...")
     ppl_lookup, cap_lookup = at.build_campaign_lookups()
     sync_result = at.sync_campaigns_from_google_ads(google_campaigns, monthly_metrics, ppl_lookup, cap_lookup)
@@ -217,7 +219,6 @@ def run():
     resumen = []
     advice_updates = []        # (gcm_record_id, consejo, criticidad) para batch update final
     metricas_updates = []      # {airtable_id, metricas_json} para MetricasDiarias
-    from datetime import timedelta
     ayer        = datetime.now() - timedelta(days=1)
     dia_hoy     = ayer.strftime("%d")
     cambio_mes  = ayer.month != datetime.now().month
@@ -302,7 +303,8 @@ def run():
             md = json.loads(campaign["metricas_diarias"])
         except (json.JSONDecodeError, TypeError):
             md = {}
-        md[dia_hoy] = {"coste": coste_hoy, "ingreso": ingreso_hoy, "margen": margen_hoy}
+        leads_hoy = leads_yesterday.get(cid, 0)
+        md[dia_hoy] = {"coste": coste_hoy, "ingreso": ingreso_hoy, "margen": margen_hoy, "leads": leads_hoy}
         campaign["metricas_diarias"] = json.dumps(md, ensure_ascii=False)
         metricas_updates.append({
             "airtable_id": campaign["airtable_id"],