Update app.py

app.py

@@ -105,14 +105,6 @@ def dataset_nations():
     vals = [n for n in DF["Nation"].dropna().unique().tolist() if str(n).strip()]
     return sorted(set(vals))
 
-def all_countries_minus_excluded():
-    vals = []
-    for c in pycountry.countries:
-        nm = c.name
-        if re.sub(r"\s+"," ", nm).upper() not in EXCLUDED_NATIONS:
-            vals.append(nm)
-    return sorted(set(vals))
-
 def clubs_list():
     if "Club" not in DF.columns: return []
     vals = [c for c in DF["Club"].dropna().unique().tolist() if str(c).strip()]
@@ -151,39 +143,31 @@ def to_csv_bytes(df):
     return buf.getvalue().encode("utf-8")
 
 # =======================
-# UI (bubble layout + equalized heights)
+# UI (clean aesthetic; equal bubble heights; Search in Results header)
 # =======================
 THEME = gr.themes.Soft(primary_hue="blue")
 CSS = """
 #title { text-align:center; }
-.bubble { background:#fff; border-radius:16px; padding:12px; box-shadow:0 2px 10px rgba(0,0,0,.06); display:flex; flex-direction:column; justify-content:space-between; min-height:110px; }
+.bubble { background:#fff; border-radius:16px; padding:12px; box-shadow:0 2px 10px rgba(0,0,0,.06); display:flex; flex-direction:column; justify-content:space-between; min-height:120px; }
 .bubble.tall { min-height: 220px; }
 .grid { gap:12px; }
 .stat { font-weight:600; font-size:14px; }
 .banner { background:#f6f7ff; border:1px solid #e3e6ff; padding:10px 12px; border-radius:12px; }
+.header-row { display:flex; align-items:center; justify-content:space-between; gap:12px; }
+.header-row .stats { display:flex; gap:16px; }
 """
 
 with gr.Blocks(theme=THEME, css=CSS) as demo:
-    # Data banner shows linkage state (how many players + which columns)
+    # Top banner confirms linkage
     if DF.empty:
-        gr.Markdown("<div class='banner'><b>Dataset not found or empty.</b> Upload <code>players.dataset.xlsx</code> to the root.</div>")
+        gr.Markdown("<div class='banner'><b>No players loaded.</b> Make sure <code>players.dataset.xlsx</code> is in the root.</div>")
     else:
-        cols = ", ".join(DF.columns.tolist())
-        gr.Markdown(f"<div class='banner'>Loaded <b>{len(DF)}</b> players • Columns: <code>{cols}</code></div>")
+        gr.Markdown(f"<div class='banner'>Loaded <b>{len(DF)}</b> players.</div>")
 
     gr.Markdown("<h1 id='title'>ProScout — Player Finder</h1>")
 
-    # Toggle for nation list source (dataset vs all countries)
-    with gr.Row():
-        with gr.Column(scale=3):
-            pass
-        with gr.Column(scale=1):
-            with gr.Group(elem_classes="bubble"):
-                show_all_countries = gr.Checkbox(label="Show all countries", value=False, info="Default: only nations present in your dataset")
-
-    # Filters + results
     with gr.Row():
-        # Column 1 — categorical + search
+        # Column 1 — categorical + search (each in its own bubble)
         with gr.Column(scale=1, elem_classes="grid"):
             with gr.Group(elem_classes="bubble tall"):
                 pos = gr.CheckboxGroup(positions_list(), label="Positions", value=[], info="Pick one or more")
@@ -218,28 +202,16 @@ with gr.Blocks(theme=THEME, css=CSS) as demo:
             with gr.Group(elem_classes="bubble"):
                 max_wage = gr.Number(value=np.nan, label="Max Wage (EUR)")
 
-        # Results panel (wide)
+        # Results panel — Search button in header next to stats
         with gr.Column(scale=2):
             with gr.Group(elem_classes="bubble tall"):
+                header = gr.HTML("<div class='header-row'><div class='stats'><span id='stat-count'></span><span id='stat-ovr'></span><span id='stat-age'></span></div></div>")
                 results = gr.Dataframe(row_count=(12,"dynamic"), wrap=True, interactive=False, label="Results")
-                with gr.Row():
-                    count_box = gr.Markdown("", elem_classes="stat")
-                    avg_ovr_box = gr.Markdown("", elem_classes="stat")
-                    avg_age_box = gr.Markdown("", elem_classes="stat")
-                dl = gr.DownloadButton("Download CSV")
-
-    # Full-width Search button
-    with gr.Row():
-        with gr.Column(scale=3):
-            with gr.Group(elem_classes="bubble"):
+                count_box = gr.Markdown("", elem_id="stat-count")
+                avg_ovr_box = gr.Markdown("", elem_id="stat-ovr")
+                avg_age_box = gr.Markdown("", elem_id="stat-age")
                 btn = gr.Button("Search", variant="primary")
 
-    # Dynamic: switch nations list source
-    def update_nations_list(show_all):
-        return gr.update(choices=all_countries_minus_excluded() if show_all else dataset_nations(), value=[])
-
-    show_all_countries.change(update_nations_list, inputs=show_all_countries, outputs=nat)
-
     # Main callback
     def _run(positions, nations, clubs, min_overall, min_potential,
              max_age, min_h, max_h, min_w, max_w, max_val, max_wage, query):
@@ -247,21 +219,4 @@ with gr.Blocks(theme=THEME, css=CSS) as demo:
                             max_age, min_h, max_h, min_w, max_w, max_val, max_wage, query)
         count = len(df)
         avg_ovr = round(df["Overall"].mean(), 2) if "Overall" in df and not df["Overall"].isna().all() else "-"
-        avg_age = round(df["Age"].mean(), 2) if "Age" in df and not df["Age"].isna().all() else "-"
-        csv_bytes = to_csv_bytes(df)
-        return df, f"**Players:** {count}", f"**Avg OVR:** {avg_ovr}", f"**Avg Age:** {avg_age}", csv_bytes
-
-    # Load initial results automatically
-    demo.load(
-        _run,
-        inputs=[pos,nat,clu,min_ovr,min_pot,max_age,min_h,max_h,min_w,max_w,max_val,max_wage,query],
-        outputs=[results,count_box,avg_ovr_box,avg_age_box,dl]
-    )
-    btn.click(
-        _run,
-        inputs=[pos,nat,clu,min_ovr,min_pot,max_age,min_h,max_h,min_w,max_w,max_val,max_wage,query],
-        outputs=[results,count_box,avg_ovr_box,avg_age_box,dl]
-    )
-
-# Launch for Spaces
-demo.launch(server_name="0.0.0.0", server_port=int(os.environ.get("PORT", 7860)))
+        avg_age = round(df["Age"].mean(), 2) if "Age" in df and not df["Age"].isna(_