update app.py

app.py

@@ -709,36 +709,83 @@ if file_upload is not None:
                     m.to_streamlit()
                     st.session_state.map_data = m
 
+# if st.button(f"Calculate {custom_formula}"):
+#     if not locations_df.empty:
+#         with st.spinner("Processing Data..."):
+#         results, processing_time = process_aggregation(  # Capture results and processing time
+#             locations_df,
+#             start_date_str,
+#             end_date_str,
+#             dataset_id,
+#             selected_bands,
+#             reducer_choice,
+#             shape_type,
+#             aggregation_period,
+#             custom_formula,
+#             kernel_size,
+#             include_boundary
+#         )
+#         if results:
+#             result_df = pd.DataFrame(results)
+#             st.write(f"Processed Results Table ({aggregation_period}) for Formula: {custom_formula}")
+#             st.dataframe(result_df)
+#             filename = f"{main_selection}_{dataset_id}_{start_date.strftime('%Y%m%d')}_{end_date.strftime('%Y%m%d')}_{aggregation_period.lower()}.csv"
+#             st.download_button(
+#                 label="Download results as CSV",
+#                 data=result_df.to_csv(index=False).encode('utf-8'),
+#                 file_name=filename,
+#                 mime='text/csv'
+#             )
+#             # Display processing time
+#             st.success(f"Processing complete! Total processing time: {processing_time:.2f} seconds.")
+#         else:
+#             st.warning("No results were generated. Check your inputs or formula.")
+#             st.info(f"Total processing time: {processing_time:.2f} seconds.")  # Show processing time even if no results
+#     else:
+#         st.warning("Please upload a file to proceed.")
+
 if st.button(f"Calculate {custom_formula}"):
     if not locations_df.empty:
-        results, processing_time = process_aggregation(  # Capture results and processing time
-            locations_df,
-            start_date_str,
-            end_date_str,
-            dataset_id,
-            selected_bands,
-            reducer_choice,
-            shape_type,
-            aggregation_period,
-            custom_formula,
-            kernel_size,
-            include_boundary
-        )
-        if results:
-            result_df = pd.DataFrame(results)
-            st.write(f"Processed Results Table ({aggregation_period}) for Formula: {custom_formula}")
-            st.dataframe(result_df)
-            filename = f"{main_selection}_{dataset_id}_{start_date.strftime('%Y%m%d')}_{end_date.strftime('%Y%m%d')}_{aggregation_period.lower()}.csv"
-            st.download_button(
-                label="Download results as CSV",
-                data=result_df.to_csv(index=False).encode('utf-8'),
-                file_name=filename,
-                mime='text/csv'
-            )
-            # Display processing time
-            st.success(f"Processing complete! Total processing time: {processing_time:.2f} seconds.")
-        else:
-            st.warning("No results were generated. Check your inputs or formula.")
-            st.info(f"Total processing time: {processing_time:.2f} seconds.")  # Show processing time even if no results
+        # Use a spinner to indicate data processing
+        with st.spinner("Processing Data..."):
+            try:
+                # Call the aggregation function and capture results and processing time
+                results, processing_time = process_aggregation(
+                    locations_df,
+                    start_date_str,
+                    end_date_str,
+                    dataset_id,
+                    selected_bands,
+                    reducer_choice,
+                    shape_type,
+                    aggregation_period,
+                    custom_formula,
+                    kernel_size,
+                    include_boundary
+                )
+                
+                # Check if results were generated
+                if results:
+                    result_df = pd.DataFrame(results)
+                    st.write(f"Processed Results Table ({aggregation_period}) for Formula: {custom_formula}")
+                    st.dataframe(result_df)
+                    
+                    # Generate a downloadable CSV file
+                    filename = f"{main_selection}_{dataset_id}_{start_date.strftime('%Y%m%d')}_{end_date.strftime('%Y%m%d')}_{aggregation_period.lower()}.csv"
+                    st.download_button(
+                        label="Download results as CSV",
+                        data=result_df.to_csv(index=False).encode('utf-8'),
+                        file_name=filename,
+                        mime='text/csv'
+                    )
+                    
+                    # Display processing time
+                    st.success(f"Processing complete! Total processing time: {processing_time:.2f} seconds.")
+                else:
+                    st.warning("No results were generated. Check your inputs or formula.")
+                    st.info(f"Total processing time: {processing_time:.2f} seconds.")  # Show processing time even if no results
+            
+            except Exception as e:
+                st.error(f"An error occurred during processing: {str(e)}")
     else:
         st.warning("Please upload a file to proceed.")