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Creatividades tab: vertical filter inside tab, campaign filter by name

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Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Jose Manuel 2026-06-26 10:02:58 +02:00
parent 4d67c25578
commit 2c12a48407
1 changed files with 30 additions and 9 deletions
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39
dashboard.py
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@ -26,6 +26,16 @@ st.set_page_config(
initial_sidebar_state="expanded", initial_sidebar_state="expanded",
) )
import streamlit.components.v1 as components
components.html("""
<script>
// Ping cada 30s para mantener el WebSocket activo y evitar el error 401 por inactividad
setInterval(function() {
fetch('/_stcore/health').catch(function() {});
}, 30000);
</script>
""", height=0)
_STRATEGY_LABELS = { _STRATEGY_LABELS = {
"LOWEST_COST_WITHOUT_CAP": "Menor coste", "LOWEST_COST_WITHOUT_CAP": "Menor coste",
"LOWEST_COST_WITH_BID_CAP": "Cap. puja", "LOWEST_COST_WITH_BID_CAP": "Cap. puja",
@ -497,23 +507,35 @@ with tab5:
df_all["score"] = pd.to_numeric(df_all.get("score", 0), errors="coerce").fillna(0) 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)) 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()}
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 = st.columns([2, 2, 2]) f1, f2, f3, f4 = st.columns([2, 2, 2, 2])
dates_available = sorted(df_all["created_at"].dropna().unique(), reverse=True) 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)
camp_ids = sorted(df_all["campaign_id"].dropna().unique().tolist()) if "campaign_id" in df_all.columns else [] verts_available = sorted(df_all["vertical"].dropna().unique().tolist())
sel_camp = f2.selectbox("Campaña", ["Todas"] + camp_ids) sel_vert_cr = f2.selectbox("Vertical", ["Todas"] + verts_available, key="cr_vert")
score_min = f3.slider("Score mínimo", 0.0, 10.0, 0.0, step=0.5) 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)
# Apply filters # Apply filters
df = df_all.copy() df = df_all.copy()
if sel_date: if sel_date:
df = df[df["created_at"] == sel_date] df = df[df["created_at"] == sel_date]
if sel_camp != "Todas" and "campaign_id" in df.columns: if sel_vert_cr != "Todas":
df = df[df["campaign_id"] == sel_camp] df = df[df["vertical"] == sel_vert_cr]
if sel_camp != "Todas":
df = df[df["campaign_name"] == sel_camp]
if score_min > 0: if score_min > 0:
df = df[df["score"] >= score_min] df = df[df["score"] >= score_min]
@ -540,12 +562,11 @@ with tab5:
# ── Table + Detail panel ────────────────────────────────────────────────── # ── Table + Detail panel ──────────────────────────────────────────────────
rename_map = { rename_map = {
"campaign_id": "Campaña ID", "campaign_name": "Campaña",
"vertical": "Vertical",
"ad_name": "Anuncio", "ad_name": "Anuncio",
"score": "Score", "score": "Score",
"created_at": "Fecha", "created_at": "Fecha",
"analysis": "Análisis",
"recommendations": "Recomendaciones",
} }
display_cols = [c for c in rename_map if c in df.columns] display_cols = [c for c in rename_map if c in df.columns]
df_display = df[display_cols].rename(columns=rename_map).reset_index(drop=True) df_display = df[display_cols].rename(columns=rename_map).reset_index(drop=True)