Update app.py

app.py

@@ -8,6 +8,10 @@ from entrenamiento_modelo import term_document_matrix, tf_idf_score
 from resultados_consulta import resultados_consulta, detalles_resultados
 import tensorflow as tf
 
+def split_frame(input_df, rows):
+    df = [input_df.loc[i : i + rows - 1, :] for i in range(0, len(input_df), rows)]
+    return df
+
 def crear_indice():
     df=cargar_articulos()
     vocab = limpieza_articulos(df)
@@ -28,8 +32,6 @@ def main():
 
     #crear_indice() 
 
-    
-
     st.set_page_config(page_title="Buscador de noticias periodicos dominicanos", page_icon="📰", layout="centered")
     st.image('repartidor_periodicos.jpeg', width=150)
     st.header('El Repartidor Dominicano')
@@ -118,6 +120,12 @@ def main():
             else:
             
                 df_results=detalles_resultados(df,result)
+                pagination = st.container()
+                batch_size = 10
+                total_pages = (int(len(df_results) / batch_size) if int(len(df_results) / batch_size) > 0 else 1
+                current_page = st.number_input("Página", min_value=1, max_value=total_pages, step=1)
+                st.markdown(f"Página **{current_page}** de **{total_pages}** ")
+                
                 N_cards_per_row = 1
                 for n_row, row in df_results.reset_index().iterrows():
                     i = n_row%N_cards_per_row
@@ -130,5 +138,8 @@ def main():
                         st.markdown(f"**{row['titulo'].strip()}**")
                         st.markdown(f"{row['resumen'].strip()}")
                         st.markdown(f"{row['link']}")
+                pages = split_frame(df_results, batch_size)
+                pagination.dataframe(data=pages[current_page - 1], use_container_width=True)
+                        
 if __name__ == "__main__":
     main()