Update staged app.py with export button for filtered CSV download

_space/app.py

@@ -235,6 +235,7 @@ map.on('click', function(e) {
 CSS = """
 #results-table { max-height: 620px; }
 .modal-hint { font-size: 12px; color: #6b7280; }
+#table-top-bar { display: flex; justify-content: space-between; align-items: center; margin-bottom: 4px; }
 """
 
 
@@ -306,9 +307,9 @@ def build_map(pid):
     return iframe, title
 
 
-def apply_filters(garden_lo, garden_hi, parcel_lo, parcel_hi, cov_lo, cov_hi, nb_lo, nb_hi,
-                  gemeenten, secties, perc_lo, perc_hi, year_lo, year_hi, excl_year,
-                  doelen, residential, idq, limit):
+def get_filtered_df(garden_lo, garden_hi, parcel_lo, parcel_hi, cov_lo, cov_hi, nb_lo, nb_hi,
+                    gemeenten, secties, perc_lo, perc_hi, year_lo, year_hi, excl_year,
+                    doelen, residential, idq):
     df = DATA
     if garden_lo is None:
         garden_lo = 0.0
@@ -336,7 +337,6 @@ def apply_filters(garden_lo, garden_hi, parcel_lo, parcel_hi, cov_lo, cov_hi, nb
         m = m & df['sectie'].isin(secties)
     if doelen:
         m = m & df['gebruiksdoel'].isin(doelen)
-    # Perceelnummer uit een tekstveld halen (lege tekst = geen filter)
     perc_lo = _parse_int(perc_lo)
     perc_hi = _parse_int(perc_hi)
     if perc_lo is not None or perc_hi is not None:
@@ -362,9 +362,40 @@ def apply_filters(garden_lo, garden_hi, parcel_lo, parcel_hi, cov_lo, cov_hi, nb
             | df['straat_en_huisnummer'].astype(str).str.contains(q, case=False, na=False)
             | df['postcode'].astype(str).str.contains(q, case=False, na=False)
         )
-    res = df[m]
+    return df[m]
+
+
+def export_filtered_csv(garden_lo, garden_hi, parcel_lo, parcel_hi, cov_lo, cov_hi, nb_lo, nb_hi,
+                        gemeenten, secties, perc_lo, perc_hi, year_lo, year_hi, excl_year,
+                        doelen, residential, idq, limit):
+    res = get_filtered_df(garden_lo, garden_hi, parcel_lo, parcel_hi, cov_lo, cov_hi, nb_lo, nb_hi,
+                          gemeenten, secties, perc_lo, perc_hi, year_lo, year_hi, excl_year,
+                          doelen, residential, idq)
+    csv_path = os.path.join(tempfile.gettempdir(), 'maastricht_percelen_gefilterd.csv')
+    if res.empty:
+        empty_df = pd.DataFrame(columns=[RENAME.get(c, c) for c in TABLE_COLS])
+        empty_df.to_csv(csv_path, index=False)
+        return csv_path
+    res = res.sort_values('calculated_garden_area', ascending=False)
+    export = res[TABLE_COLS].rename(columns=RENAME)
+    for c in NUM_ROUND:
+        if c in export.columns:
+            export[c] = export[c].round(1)
+    export.to_csv(csv_path, index=False)
+    return csv_path
+
+
+def apply_filters(garden_lo, garden_hi, parcel_lo, parcel_hi, cov_lo, cov_hi, nb_lo, nb_hi,
+                  gemeenten, secties, perc_lo, perc_hi, year_lo, year_hi, excl_year,
+                  doelen, residential, idq, limit):
+    res = get_filtered_df(garden_lo, garden_hi, parcel_lo, parcel_hi, cov_lo, cov_hi, nb_lo, nb_hi,
+                          gemeenten, secties, perc_lo, perc_hi, year_lo, year_hi, excl_year,
+                          doelen, residential, idq)
+    csv_path = os.path.join(tempfile.gettempdir(), 'maastricht_percelen_gefilterd.csv')
     if res.empty:
-        return 'Geen percelen gevonden met deze filters. Probeer de bereiken te verruimen.', None, None
+        empty_df = pd.DataFrame(columns=[RENAME.get(c, c) for c in TABLE_COLS])
+        empty_df.to_csv(csv_path, index=False)
+        return 'Geen percelen gevonden met deze filters. Probeer de bereiken te verruimen.', None, csv_path, csv_path, csv_path
     res = res.sort_values('calculated_garden_area', ascending=False)
     shown = res[TABLE_COLS].head(int(limit)).copy()
     shown['Bekijken'] = [VIEW_CELL.replace('{pid}', str(v)) for v in shown[ID_COL]]
@@ -372,16 +403,16 @@ def apply_filters(garden_lo, garden_hi, parcel_lo, parcel_hi, cov_lo, cov_hi, nb
     export = res[TABLE_COLS].rename(columns=RENAME)
     for frame in (shown, export):
         for c in NUM_ROUND:
-            frame[c] = frame[c].round(1)
-    csv_path = os.path.join(tempfile.gettempdir(), 'maastricht_percelen_gefilterd.csv')
+            if c in frame.columns:
+                frame[c] = frame[c].round(1)
     export.to_csv(csv_path, index=False)
     # NaN (percelen zonder gebouwen hebben geen bouwjaar) is niet JSON-compatibel:
     # naar None converteren zodat de Dataframe-payload serialiseert.
     shown = shown.astype(object).where(pd.notna(shown), None)
-    status = ('**' + format(len(res), ',d') + '** percelen komen overeen (van ' + format(len(df), ',d')
+    status = ('**' + format(len(res), ',d') + '** percelen komen overeen (van ' + format(len(DATA), ',d')
               + ' in de momentopname). Tuin ' + _fmt(garden_lo) + '\u2013' + _fmt(garden_hi)
               + ' m\u00b2, gesorteerd op tuinoppervlak; top ' + str(len(shown)) + ' weergegeven.')
-    return status, shown, csv_path
+    return status, shown, csv_path, csv_path, csv_path
 
 
 def build_map_page(pid):
@@ -444,21 +475,27 @@ with ui.Blocks(title='Maastricht Tuinzoeker') as demo:
                                    label='Woonfunctie')
             idq = ui.Textbox(label='Zoeken (Adres, Postcode, Kadaster-ID)', placeholder='bijv. Boschstraat, 6211, 3430000927')
             limit = ui.Slider(minimum=5, maximum=500, value=25, step=5, label='Weergegeven rijen')
-            btn = ui.Button('Filters toepassen', variant='primary')
+            with ui.Row():
+                btn = ui.Button('Filters toepassen', variant='primary', scale=2)
+                export_btn = ui.DownloadButton('📥 Exporteer (.csv)', variant='secondary', scale=2)
             ui.Markdown('<div class="modal-hint">Klik op <b>Bekijken</b> in een rij om de '
                         'perceelkaart in een nieuw tabblad te openen.</div>')
 
         with ui.Column(scale=3):
-            status = ui.Markdown()
+            with ui.Row(elem_id='table-top-bar'):
+                status = ui.Markdown()
+                table_export_btn = ui.DownloadButton('📥 Exporteer naar .csv', variant='secondary', size='sm', scale=0)
             table = ui.Dataframe(datatype=DATATYPES, interactive=True, wrap=False,
                                  elem_id='results-table', label='Overeenkomende percelen')
-            download = ui.File(label='\U0001f4e5 Gefilterde CSV downloaden')
+            download = ui.File(label='📥 Gefilterde CSV downloaden')
 
     inputs = [garden_lo, garden_hi, parcel_lo, parcel_hi, cov_lo, cov_hi, nb_lo, nb_hi,
               gemeenten, secties, perc_lo, perc_hi, year_lo, year_hi, excl_year,
               doelen, residential, idq, limit]
-    btn.click(fn=apply_filters, inputs=inputs, outputs=[status, table, download])
-    demo.load(fn=apply_filters, inputs=inputs, outputs=[status, table, download])
+    btn.click(fn=apply_filters, inputs=inputs, outputs=[status, table, export_btn, table_export_btn, download])
+    demo.load(fn=apply_filters, inputs=inputs, outputs=[status, table, export_btn, table_export_btn, download])
+    export_btn.click(fn=export_filtered_csv, inputs=inputs, outputs=export_btn)
+    table_export_btn.click(fn=export_filtered_csv, inputs=inputs, outputs=table_export_btn)
 
 @app.get('/map/{pid}')
 def map_page(pid: str):