Update app.py

app.py

@@ -44,7 +44,7 @@ def flatten_json(data, flattened=None, prefix=''):
             new_key = f"{prefix}[{i}]" if prefix else str(i)
             flatten_json(item, flattened, new_key)
     elif data is not None and data != "":
-        flattened[prefix] = data
+        flattened[prefix] = value
     
     return flattened
 
@@ -64,16 +64,15 @@ uploaded_zips = st.file_uploader("Upload ZIP files containing JSON files:", type
 
 if uploaded_zips:
     # Process all uploaded ZIP files
-    all_flattened_json = {}
-    total_files_processed = 0
+    all_flattened_json = []
     
     for zip_file in uploaded_zips:
         flattened_json = extract_and_combine_zip(zip_file)
-        all_flattened_json.update(flattened_json)
-        total_files_processed += 1
+        flattened_json['zip_file_name'] = zip_file.name  # Add ZIP file name to the flattened JSON
+        all_flattened_json.append(flattened_json)
 
     # Create a DataFrame from the flattened JSON data
-    df = pd.DataFrame([all_flattened_json])
+    df = pd.DataFrame(all_flattened_json)
 
     # Convert all object columns to string to avoid Arrow conversion issues
     for col in df.select_dtypes(include=['object']).columns:
@@ -84,8 +83,8 @@ if uploaded_zips:
     json_bytes = flattened_json_str.encode()
 
     # Display processing summary
-    st.write(f"Processed {total_files_processed} ZIP file(s)")
-    st.write(f"Total JSON objects flattened: {len(all_flattened_json)}")
+    st.write(f"Processed {len(uploaded_zips)} ZIP file(s)")
+    st.write(f"Total rows in the output: {len(all_flattened_json)}")
 
     # Create columns for download buttons
     col1, col2 = st.columns(2)
@@ -110,4 +109,8 @@ if uploaded_zips:
         )
 
     # Add a success message
-    st.success(f"All ZIP files have been successfully processed. JSON data has been flattened into a single object. You can now download the flattened JSON file or the Excel file.")
+    st.success(f"All ZIP files have been successfully processed. Each ZIP file is represented as a separate row in the output. You can now download the flattened JSON file or the Excel file.")
+
+    # Display a preview of the DataFrame
+    st.write("Preview of the processed data:")
+    st.dataframe(df.head())