Remove sidebar: move date/vertical filters into each tab independently
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
parent
2c12a48407
commit
c782db5a75
374
dashboard.py
374
dashboard.py
@ -20,10 +20,11 @@ def _extract_vertical(name: str) -> str:
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start = 1 if parts and parts[0].isdigit() else 0
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return parts[start].lower() if start < len(parts) else "otros"
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st.set_page_config(
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page_title=f"Meta Optimizer — {config.META_CAMPAIGN_PREFIX}",
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layout="wide",
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initial_sidebar_state="expanded",
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initial_sidebar_state="collapsed",
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)
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import streamlit.components.v1 as components
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@ -43,6 +44,18 @@ _STRATEGY_LABELS = {
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"MINIMUM_ROAS": "ROAS mín.",
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}
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_ACTION_COLORS = {
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"INCREASE_BUDGET": "🟢",
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"REDUCE_BUDGET": "🟠",
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"PAUSE": "🔴",
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"REVIEW_CREATIVES": "🟣",
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"MAINTAIN": "⚪",
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}
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_today = date.today()
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_yesterday = _today - timedelta(days=1)
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_default_from = _yesterday - timedelta(days=6)
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def _eur(val: float) -> str:
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return f"{val:.2f}€"
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@ -60,6 +73,20 @@ def _status(leads: int, spend: float) -> str:
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return "—"
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def _date_row(key: str, n_extra_cols: int = 0) -> tuple:
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"""Renders [Desde | Hasta | ...extra... | 🔄] columns. Returns (date_from, date_to, *extra_cols)."""
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cols = st.columns([2, 2] + [2] * n_extra_cols + [1])
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d_from = cols[0].date_input("Desde", value=_default_from, max_value=_yesterday, key=f"{key}_from")
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d_to = cols[1].date_input("Hasta", value=_yesterday, min_value=d_from, max_value=_yesterday, key=f"{key}_to")
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if cols[-1].button("🔄", key=f"{key}_ref", use_container_width=True, help="Limpiar caché"):
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st.cache_data.clear()
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st.rerun()
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extra = tuple(cols[2:-1])
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return (d_from, d_to) + extra
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# ── Cached data loaders ───────────────────────────────────────────────────────
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@st.cache_data(ttl=300, show_spinner="Cargando datos de Meta API...")
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def _load_data(date_from: str, date_to: str):
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meta = MetaAdsClient()
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@ -92,48 +119,98 @@ def _load_detail(campaign_id: str, date_from: str, date_to: str):
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return adsets, ads, bid
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# ── Sidebar ───────────────────────────────────────────────────────────────────
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@st.cache_data(ttl=3600, show_spinner=False)
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def _load_campaign_names() -> dict:
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"""Returns {campaign_id: campaign_name} for the last 30 days. Cached 1h."""
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meta = MetaAdsClient()
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end = _yesterday.strftime("%Y-%m-%d")
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start = (_yesterday - timedelta(days=29)).strftime("%Y-%m-%d")
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try:
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metrics = meta.get_campaign_metrics(start, end)
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return {cid: m["name"] for cid, m in metrics.items()}
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except Exception:
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return {}
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st.sidebar.title("Filtros")
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today = date.today()
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yesterday = today - timedelta(days=1)
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default_from = yesterday - timedelta(days=6) # últimos 7 días por defecto
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first_of_month = today.replace(day=1)
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c1, c2 = st.sidebar.columns(2)
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date_from = c1.date_input("Desde", value=default_from, max_value=yesterday)
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date_to = c2.date_input("Hasta", value=yesterday, min_value=date_from, max_value=yesterday)
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@st.cache_data(ttl=120, show_spinner="Cargando fechas disponibles...")
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def _load_snapshot_dates():
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return BaserowClient().get_snapshot_dates()
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if st.sidebar.button("🔄 Actualizar", use_container_width=True):
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st.cache_data.clear()
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date_from_str = date_from.strftime("%Y-%m-%d")
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date_to_str = date_to.strftime("%Y-%m-%d")
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@st.cache_data(ttl=120, show_spinner="Cargando análisis del día...")
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def _load_snapshots(run_date: str):
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import json
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rows = BaserowClient().get_snapshots_for_date(run_date)
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result = []
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for r in rows:
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try:
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adsets = json.loads(r.get("adsets_json") or "[]")
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except Exception:
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adsets = []
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try:
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ads = json.loads(r.get("ads_json") or "[]")
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except Exception:
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ads = []
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result.append({
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"campaign_name": r.get("campaign_name", ""),
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"vertical": r.get("vertical", ""),
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"spend": float(r.get("spend") or 0),
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"leads": int(r.get("leads") or 0),
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"cpl": float(r.get("cpl") or 0),
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"margin": float(r.get("margin") or 0),
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"action_type": r.get("action_type", "MAINTAIN"),
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"justification": r.get("justification", ""),
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"adsets": adsets,
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"ads": ads,
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})
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return sorted(result, key=lambda x: -x["spend"])
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if date_from > date_to:
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@st.cache_data(ttl=300, show_spinner="Cargando análisis de creatividades...")
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def _load_creatives():
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return BaserowClient().get_all_creative_analyses()
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# ── Header ────────────────────────────────────────────────────────────────────
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st.title(f"Meta Optimizer — {config.META_CAMPAIGN_PREFIX}")
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# ── Tabs ──────────────────────────────────────────────────────────────────────
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tab1, tab2, tab3, tab4, tab5 = st.tabs(
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["📅 Por día", "📊 Campañas", "🏷️ Verticales", "🗂️ Histórico", "🎨 Creatividades"]
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)
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# ── Tab 1: Por día ────────────────────────────────────────────────────────────
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with tab1:
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d_from_1, d_to_1 = _date_row("t1")
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if d_from_1 > d_to_1:
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st.error("La fecha inicio debe ser anterior a la fecha fin.")
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st.stop()
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else:
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try:
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daily_rows, _cm1, vertical_cpls_1 = _load_data(
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d_from_1.strftime("%Y-%m-%d"), d_to_1.strftime("%Y-%m-%d")
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)
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except Exception as e:
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st.error(f"Error cargando datos de Meta API: {e}")
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daily_rows, vertical_cpls_1 = [], {}
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# ── Data ──────────────────────────────────────────────────────────────────────
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try:
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daily_rows, campaign_metrics, vertical_cpls = _load_data(date_from_str, date_to_str)
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except Exception as _e:
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st.error(f"Error cargando datos de Meta API: {_e}")
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st.stop()
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# Aggregate daily totals with per-vertical margins
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_daily: dict = {}
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for row in daily_rows:
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_daily: dict = {}
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for row in daily_rows:
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v = _extract_vertical(row["campaign_name"])
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target = vertical_cpls.get(v, config.META_TARGET_CPL)
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margin = round((target - row["spend"] / row["leads"]) * row["leads"], 2) if row["leads"] > 0 else round(-row["spend"], 2)
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target = vertical_cpls_1.get(v, config.META_TARGET_CPL)
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margin = (
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round((target - row["spend"] / row["leads"]) * row["leads"], 2)
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if row["leads"] > 0 else round(-row["spend"], 2)
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)
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d = _daily.setdefault(row["date"], {"spend": 0.0, "leads": 0, "margin": 0.0})
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d["spend"] += row["spend"]
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d["leads"] += row["leads"]
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d["margin"] += margin
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daily_totals = [
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daily_totals = [
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{
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"date": dt,
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"spend": round(d["spend"], 2),
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@ -142,54 +219,20 @@ daily_totals = [
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"margin": round(d["margin"], 2),
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}
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for dt, d in sorted(_daily.items())
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]
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]
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# Aggregate verticals
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verticals: dict = {}
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for cid, m in campaign_metrics.items():
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v = _extract_vertical(m["name"])
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target = vertical_cpls.get(v, config.META_TARGET_CPL)
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margin = round((target - m["cpl"]) * m["leads"], 2) if m["leads"] > 0 else round(-m["spend"], 2)
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if v not in verticals:
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verticals[v] = {"spend": 0.0, "leads": 0, "margin": 0.0, "target_cpl": target}
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verticals[v]["spend"] += m["spend"]
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verticals[v]["leads"] += m["leads"]
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verticals[v]["margin"] += margin
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total_spend = sum(d["spend"] for d in daily_totals)
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total_leads = sum(d["leads"] for d in daily_totals)
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total_cpl = round(total_spend / total_leads, 2) if total_leads > 0 else 0.0
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total_margin = sum(d["margin"] for d in daily_totals)
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# Vertical filter (populated after load)
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v_options = ["Todos"] + sorted(verticals.keys())
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selected_vertical = st.sidebar.selectbox("Vertical", v_options)
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if selected_vertical != "Todos":
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campaign_metrics = {
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cid: m for cid, m in campaign_metrics.items()
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if _extract_vertical(m["name"]) == selected_vertical
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}
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k1, k2, k3, k4 = st.columns(4)
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k1.metric("Gasto total", _eur(total_spend))
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k2.metric("Leads totales", f"{total_leads:,}")
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k3.metric("CPL medio", _eur(total_cpl))
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k4.metric("Margen total", _margin(total_margin))
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st.divider()
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# ── Header ────────────────────────────────────────────────────────────────────
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st.title(f"Meta Optimizer — {config.META_CAMPAIGN_PREFIX}")
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st.caption(f"Período: **{date_from.strftime('%d/%m/%Y')}** → **{date_to.strftime('%d/%m/%Y')}**")
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total_spend = sum(d["spend"] for d in daily_totals)
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total_leads = sum(d["leads"] for d in daily_totals)
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total_cpl = round(total_spend / total_leads, 2) if total_leads > 0 else 0.0
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total_margin = sum(d["margin"] for d in daily_totals)
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k1, k2, k3, k4 = st.columns(4)
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k1.metric("Gasto total", _eur(total_spend))
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k2.metric("Leads totales", f"{total_leads:,}")
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k3.metric("CPL medio", _eur(total_cpl))
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k4.metric("Margen total", _margin(total_margin))
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st.divider()
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# ── Tabs ──────────────────────────────────────────────────────────────────────
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tab1, tab2, tab3, tab4, tab5 = st.tabs(["📅 Por día", "📊 Campañas", "🏷️ Verticales", "🗂️ Histórico", "🎨 Creatividades"])
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# ── Tab 1: Por día ────────────────────────────────────────────────────────────
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with tab1:
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if not daily_totals:
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st.info("Sin datos para el período seleccionado.")
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else:
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@ -212,28 +255,29 @@ with tab1:
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"Selecciona un día",
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day_opts,
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format_func=lambda s: s[8:10] + "/" + s[5:7] + "/" + s[:4],
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key="t1_day",
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)
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if selected_day:
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day_camp: dict = {}
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for row in daily_rows:
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if row["date"] != selected_day:
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continue
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key = row["campaign_name"]
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if key not in day_camp:
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v = _extract_vertical(key)
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target = vertical_cpls.get(v, config.META_TARGET_CPL)
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day_camp[key] = {
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"name": key, "vertical": v,
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"spend": 0.0, "leads": 0, "target_cpl": target,
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}
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day_camp[key]["spend"] += row["spend"]
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day_camp[key]["leads"] += row["leads"]
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k = row["campaign_name"]
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if k not in day_camp:
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v = _extract_vertical(k)
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target = vertical_cpls_1.get(v, config.META_TARGET_CPL)
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day_camp[k] = {"name": k, "vertical": v, "spend": 0.0, "leads": 0, "target_cpl": target}
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day_camp[k]["spend"] += row["spend"]
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day_camp[k]["leads"] += row["leads"]
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rows = []
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camp_rows = []
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for c in sorted(day_camp.values(), key=lambda x: -x["spend"]):
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cpl = round(c["spend"] / c["leads"], 2) if c["leads"] > 0 else 0.0
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margin = round((c["target_cpl"] - cpl) * c["leads"], 2) if c["leads"] > 0 else round(-c["spend"], 2)
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rows.append({
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margin = (
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round((c["target_cpl"] - cpl) * c["leads"], 2)
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if c["leads"] > 0 else round(-c["spend"], 2)
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)
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camp_rows.append({
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"Campaña": c["name"],
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"Vertical": c["vertical"],
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"Gasto": _eur(c["spend"]),
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@ -242,21 +286,43 @@ with tab1:
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"Obj": _eur(c["target_cpl"]),
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"Margen": _margin(margin),
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})
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if rows:
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st.dataframe(pd.DataFrame(rows), use_container_width=True, hide_index=True)
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if camp_rows:
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st.dataframe(pd.DataFrame(camp_rows), use_container_width=True, hide_index=True)
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else:
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st.info("Sin campañas activas ese día.")
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# ── Tab 2: Campañas ───────────────────────────────────────────────────────────
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with tab2:
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if not campaign_metrics:
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d_from_2, d_to_2, col_vert_2 = _date_row("t2", n_extra_cols=1)
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if d_from_2 > d_to_2:
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st.error("La fecha inicio debe ser anterior a la fecha fin.")
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else:
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try:
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_dr2, campaign_metrics_2, vertical_cpls_2 = _load_data(
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d_from_2.strftime("%Y-%m-%d"), d_to_2.strftime("%Y-%m-%d")
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)
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except Exception as e:
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st.error(f"Error cargando datos de Meta API: {e}")
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campaign_metrics_2, vertical_cpls_2 = {}, {}
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v_opts_2 = ["Todos"] + sorted({_extract_vertical(m["name"]) for m in campaign_metrics_2.values()})
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sel_vert_2 = col_vert_2.selectbox("Vertical", v_opts_2, key="t2_vert")
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if sel_vert_2 != "Todos":
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campaign_metrics_2 = {
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cid: m for cid, m in campaign_metrics_2.items()
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if _extract_vertical(m["name"]) == sel_vert_2
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}
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if not campaign_metrics_2:
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st.info("Sin campañas para el período seleccionado.")
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else:
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camp_rows = []
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for cid, m in sorted(campaign_metrics.items(), key=lambda x: -x[1]["spend"]):
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for cid, m in sorted(campaign_metrics_2.items(), key=lambda x: -x[1]["spend"]):
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v = _extract_vertical(m["name"])
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target = vertical_cpls.get(v, config.META_TARGET_CPL)
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target = vertical_cpls_2.get(v, config.META_TARGET_CPL)
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margin = round((target - m["cpl"]) * m["leads"], 2) if m["leads"] > 0 else round(-m["spend"], 2)
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camp_rows.append({
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"Campaña": m["name"],
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@ -275,11 +341,15 @@ with tab2:
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st.subheader("Detalle de campaña")
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camp_id_map = {r["Campaña"]: r["_cid"] for r in camp_rows}
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selected_camp = st.selectbox("Selecciona una campaña", list(camp_id_map.keys()))
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selected_camp = st.selectbox("Selecciona una campaña", list(camp_id_map.keys()), key="t2_camp")
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if selected_camp:
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selected_cid = camp_id_map[selected_camp]
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adsets, ads, bid_cfg = _load_detail(selected_cid, date_from_str, date_to_str)
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adsets, ads, bid_cfg = _load_detail(
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selected_cid,
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d_from_2.strftime("%Y-%m-%d"),
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d_to_2.strftime("%Y-%m-%d"),
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)
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strategy = bid_cfg.get("bid_strategy", "")
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strat_label = _STRATEGY_LABELS.get(strategy, strategy or "—")
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@ -324,11 +394,35 @@ with tab2:
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# ── Tab 3: Verticales ─────────────────────────────────────────────────────────
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with tab3:
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if not verticals:
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d_from_3, d_to_3 = _date_row("t3")
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if d_from_3 > d_to_3:
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st.error("La fecha inicio debe ser anterior a la fecha fin.")
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else:
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try:
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_dr3, campaign_metrics_3, vertical_cpls_3 = _load_data(
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d_from_3.strftime("%Y-%m-%d"), d_to_3.strftime("%Y-%m-%d")
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)
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except Exception as e:
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st.error(f"Error cargando datos de Meta API: {e}")
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campaign_metrics_3, vertical_cpls_3 = {}, {}
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verticals_3: dict = {}
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for cid, m in campaign_metrics_3.items():
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v = _extract_vertical(m["name"])
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target = vertical_cpls_3.get(v, config.META_TARGET_CPL)
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margin = round((target - m["cpl"]) * m["leads"], 2) if m["leads"] > 0 else round(-m["spend"], 2)
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if v not in verticals_3:
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verticals_3[v] = {"spend": 0.0, "leads": 0, "margin": 0.0, "target_cpl": target}
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verticals_3[v]["spend"] += m["spend"]
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verticals_3[v]["leads"] += m["leads"]
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verticals_3[v]["margin"] += margin
|
||||
|
||||
if not verticals_3:
|
||||
st.info("Sin datos de verticales.")
|
||||
else:
|
||||
vert_rows = []
|
||||
for v, data in sorted(verticals.items(), key=lambda x: -x[1]["margin"]):
|
||||
for v, data in sorted(verticals_3.items(), key=lambda x: -x[1]["margin"]):
|
||||
v_leads = data["leads"]
|
||||
v_spend = data["spend"]
|
||||
v_cpl = round(v_spend / v_leads, 2) if v_leads > 0 else 0.0
|
||||
@ -344,70 +438,23 @@ with tab3:
|
||||
|
||||
|
||||
# ── Tab 4: Histórico ──────────────────────────────────────────────────────────
|
||||
|
||||
_ACTION_COLORS = {
|
||||
"INCREASE_BUDGET": "🟢",
|
||||
"REDUCE_BUDGET": "🟠",
|
||||
"PAUSE": "🔴",
|
||||
"REVIEW_CREATIVES": "🟣",
|
||||
"MAINTAIN": "⚪",
|
||||
}
|
||||
|
||||
|
||||
@st.cache_data(ttl=120, show_spinner="Cargando fechas disponibles...")
|
||||
def _load_snapshot_dates():
|
||||
return BaserowClient().get_snapshot_dates()
|
||||
|
||||
|
||||
@st.cache_data(ttl=120, show_spinner="Cargando análisis del día...")
|
||||
def _load_snapshots(run_date: str):
|
||||
import json
|
||||
rows = BaserowClient().get_snapshots_for_date(run_date)
|
||||
result = []
|
||||
for r in rows:
|
||||
try:
|
||||
adsets = json.loads(r.get("adsets_json") or "[]")
|
||||
except Exception:
|
||||
adsets = []
|
||||
try:
|
||||
ads = json.loads(r.get("ads_json") or "[]")
|
||||
except Exception:
|
||||
ads = []
|
||||
result.append({
|
||||
"campaign_name": r.get("campaign_name", ""),
|
||||
"vertical": r.get("vertical", ""),
|
||||
"spend": float(r.get("spend") or 0),
|
||||
"leads": int(r.get("leads") or 0),
|
||||
"cpl": float(r.get("cpl") or 0),
|
||||
"margin": float(r.get("margin") or 0),
|
||||
"action_type": r.get("action_type", "MAINTAIN"),
|
||||
"justification": r.get("justification", ""),
|
||||
"adsets": adsets,
|
||||
"ads": ads,
|
||||
})
|
||||
return sorted(result, key=lambda x: -x["spend"])
|
||||
|
||||
|
||||
with tab4:
|
||||
dates = _load_snapshot_dates()
|
||||
|
||||
if not dates:
|
||||
st.info("Sin análisis guardados aún. Los snapshots se generan al ejecutar run.py.")
|
||||
else:
|
||||
c1, c2 = st.columns([3, 1])
|
||||
fmt_date = lambda s: s[8:10] + "/" + s[5:7] + "/" + s[:4]
|
||||
selected_date = st.selectbox(
|
||||
"Fecha del análisis",
|
||||
dates,
|
||||
format_func=fmt_date,
|
||||
)
|
||||
if st.button("🔄 Recargar", key="reload_hist"):
|
||||
selected_date = c1.selectbox("Fecha del análisis", dates, format_func=fmt_date, key="t4_date")
|
||||
if c2.button("🔄 Recargar", key="t4_ref", use_container_width=True):
|
||||
st.cache_data.clear()
|
||||
st.rerun()
|
||||
|
||||
snapshots = _load_snapshots(selected_date)
|
||||
if not snapshots:
|
||||
st.info("Sin datos para esa fecha.")
|
||||
else:
|
||||
# ── Resumen del día ───────────────────────────────────────────────
|
||||
d_spend = sum(s["spend"] for s in snapshots)
|
||||
d_leads = sum(s["leads"] for s in snapshots)
|
||||
d_cpl = round(d_spend / d_leads, 2) if d_leads > 0 else 0.0
|
||||
@ -419,7 +466,6 @@ with tab4:
|
||||
h4.metric("Margen", _margin(d_margin))
|
||||
st.divider()
|
||||
|
||||
# ── Tabla de campañas clicable ────────────────────────────────────
|
||||
df_snap = pd.DataFrame([
|
||||
{
|
||||
"Acción": _ACTION_COLORS.get(s["action_type"], "⚪") + " " + s["action_type"],
|
||||
@ -452,10 +498,9 @@ with tab4:
|
||||
if snap["justification"]:
|
||||
st.info(snap["justification"])
|
||||
|
||||
# ── Adsets — expanders con evaluación visible ─────────────────
|
||||
adsets = snap["adsets"]
|
||||
if adsets:
|
||||
st.markdown("**Conjuntos de anuncios**")
|
||||
st.markdown("**Conjuntos de anuncios** _(últimos 3 días)_")
|
||||
for a in adsets:
|
||||
label = (
|
||||
f"{a['name']} — "
|
||||
@ -471,10 +516,9 @@ with tab4:
|
||||
if a.get("recomendacion"):
|
||||
st.write(f"→ {a['recomendacion']}")
|
||||
|
||||
# ── Anuncios — expanders con evaluación visible ───────────────
|
||||
ads = snap["ads"]
|
||||
if ads:
|
||||
st.markdown("**Anuncios**")
|
||||
st.markdown("**Anuncios** _(últimos 7 días)_")
|
||||
for a in ads:
|
||||
label = (
|
||||
f"{a['name']} — "
|
||||
@ -492,33 +536,27 @@ with tab4:
|
||||
|
||||
# ── Tab 5: Creatividades ──────────────────────────────────────────────────────
|
||||
with tab5:
|
||||
@st.cache_data(ttl=300, show_spinner="Cargando análisis de creatividades...")
|
||||
def _load_creatives():
|
||||
return BaserowClient().get_all_creative_analyses()
|
||||
|
||||
creatives_raw = _load_creatives()
|
||||
|
||||
if not creatives_raw:
|
||||
st.info("No hay análisis de creatividades. Ejecuta `python analyze_creatives.py` para generar datos.")
|
||||
st.stop()
|
||||
|
||||
# Build dataframe
|
||||
else:
|
||||
df_all = pd.DataFrame(creatives_raw)
|
||||
df_all["score"] = pd.to_numeric(df_all.get("score", 0), errors="coerce").fillna(0)
|
||||
df_all["created_at"] = df_all.get("created_at", pd.Series(dtype=str))
|
||||
|
||||
# Map campaign_id → campaign_name using already-loaded Meta data
|
||||
camp_id_to_name = {cid: m["name"] for cid, m in campaign_metrics.items()}
|
||||
# Map campaign_id → name using a dedicated cached call (last 30d)
|
||||
camp_id_to_name = _load_campaign_names()
|
||||
df_all["campaign_name"] = df_all["campaign_id"].map(
|
||||
lambda cid: camp_id_to_name.get(str(cid), str(cid))
|
||||
)
|
||||
df_all["vertical"] = df_all["campaign_name"].map(_extract_vertical)
|
||||
|
||||
# ── Filters ───────────────────────────────────────────────────────────────
|
||||
# ── Filters ───────────────────────────────────────────────────────────
|
||||
f1, f2, f3, f4 = st.columns([2, 2, 2, 2])
|
||||
|
||||
dates_available = sorted(df_all["created_at"].dropna().unique(), reverse=True)
|
||||
sel_date = f1.selectbox("Fecha análisis", dates_available)
|
||||
sel_date = f1.selectbox("Fecha análisis", dates_available, key="cr_date")
|
||||
|
||||
verts_available = sorted(df_all["vertical"].dropna().unique().tolist())
|
||||
sel_vert_cr = f2.selectbox("Vertical", ["Todas"] + verts_available, key="cr_vert")
|
||||
@ -526,7 +564,7 @@ with tab5:
|
||||
camp_names = sorted(df_all["campaign_name"].dropna().unique().tolist())
|
||||
sel_camp = f3.selectbox("Campaña", ["Todas"] + camp_names, key="cr_camp")
|
||||
|
||||
score_min = f4.slider("Score mínimo", 0.0, 10.0, 0.0, step=0.5)
|
||||
score_min = f4.slider("Score mínimo", 0.0, 10.0, 0.0, step=0.5, key="cr_score")
|
||||
|
||||
# Apply filters
|
||||
df = df_all.copy()
|
||||
@ -539,7 +577,7 @@ with tab5:
|
||||
if score_min > 0:
|
||||
df = df[df["score"] >= score_min]
|
||||
|
||||
# ── KPIs ──────────────────────────────────────────────────────────────────
|
||||
# ── KPIs ──────────────────────────────────────────────────────────────
|
||||
scored_df = df[df["score"] > 0]
|
||||
avg_sc = round(scored_df["score"].mean(), 1) if not scored_df.empty else 0.0
|
||||
fatigue_n = int(df["analysis"].str.contains("FATIGA", na=False).sum()) if "analysis" in df.columns else 0
|
||||
@ -551,7 +589,6 @@ with tab5:
|
||||
k3.metric("Con fatiga", fatigue_n)
|
||||
k4.metric("Última ejecución", last_run)
|
||||
|
||||
# ── Fatigue alerts ────────────────────────────────────────────────────────
|
||||
if fatigue_n:
|
||||
fatigued = df[df["analysis"].str.contains("FATIGA", na=False)]
|
||||
with st.expander(f"⚠️ {fatigue_n} anuncios con fatiga creativa", expanded=True):
|
||||
@ -560,7 +597,7 @@ with tab5:
|
||||
|
||||
st.divider()
|
||||
|
||||
# ── Table + Detail panel ──────────────────────────────────────────────────
|
||||
# ── Table + Detail panel ──────────────────────────────────────────────
|
||||
rename_map = {
|
||||
"campaign_name": "Campaña",
|
||||
"vertical": "Vertical",
|
||||
@ -615,7 +652,6 @@ with tab5:
|
||||
st.markdown("**Recomendaciones**")
|
||||
st.info(rec)
|
||||
|
||||
# Score evolution across runs
|
||||
ad_id = str(row.get("ad_id", ""))
|
||||
if ad_id:
|
||||
history = BaserowClient().get_creative_history_by_ad(ad_id)
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user