feat([2fd88f42]): implement smart PLZ column selection

heatmap-tool/backend/main.py

@@ -45,6 +45,9 @@ def load_plz_data():
 class FilterRequest(BaseModel):
     filters: Dict[str, List[str]]
 
+class PlzColumnRequest(BaseModel):
+    plz_column: str
+
 # --- API Endpoints ---
 @app.get("/")
 def read_root():
@@ -61,7 +64,7 @@ async def upload_file(file: UploadFile = File(...)):
         contents = await file.read()
         df = pd.read_excel(io.BytesIO(contents), dtype=str) # Read all as string to be safe
         df.fillna('N/A', inplace=True)
-
+        df_storage = df # Store dataframe temporarily
 
         # --- PLZ Column Detection ---
         temp_plz_col = None
@@ -71,30 +74,53 @@ async def upload_file(file: UploadFile = File(...)):
                 break
         
         if not temp_plz_col:
-            raise HTTPException(status_code=400, detail="No column with 'PLZ' found in the file.")
+            print("PLZ column not found automatically. Asking user for selection.")
+            return {"plz_column_needed": True, "columns": list(df.columns)}
 
+        # If we found a column, proceed as before
         plz_column_name = temp_plz_col
-        # Normalize PLZ data
         df[plz_column_name] = df[plz_column_name].str.strip().str.zfill(5)
+        df_storage = df # Update storage with normalized PLZ
 
-
-        # --- Dynamic Filter Detection ---
         filters = {}
         for col in df.columns:
             if col != plz_column_name:
                 unique_values = df[col].unique().tolist()
                 filters[col] = sorted(unique_values)
 
-        df_storage = df
-        
-        print(f"Successfully processed file. Found PLZ column: '{plz_column_name}'. Detected {len(filters)} filterable columns.")
-        return {"filename": file.filename, "filters": filters, "plz_column": plz_column_name}
+        print(f"Successfully processed file. Found PLZ column: '{plz_column_name}'.")
+        return {"plz_column_needed": False, "filters": filters, "plz_column": plz_column_name}
 
     except Exception as e:
         print(f"ERROR processing file: {e}")
         raise HTTPException(status_code=500, detail=f"An error occurred while processing the file: {e}")
 
 
+@app.post("/api/set-plz-column")
+async def set_plz_column(request: PlzColumnRequest):
+    global df_storage, plz_column_name
+    print(f"--- Received request to set PLZ column to: {request.plz_column} ---")
+    if df_storage is None:
+        raise HTTPException(status_code=400, detail="No data available. Please upload a file first.")
+
+    plz_column_name = request.plz_column
+    if plz_column_name not in df_storage.columns:
+        raise HTTPException(status_code=400, detail=f"Column '{plz_column_name}' not found in the uploaded file.")
+    
+    # Normalize PLZ data
+    df_storage[plz_column_name] = df_storage[plz_column_name].str.strip().str.zfill(5)
+
+    # --- Dynamic Filter Detection ---
+    filters = {}
+    for col in df_storage.columns:
+        if col != plz_column_name:
+            unique_values = df_storage[col].unique().tolist()
+            filters[col] = sorted(unique_values)
+
+    print(f"Successfully set PLZ column. Detected {len(filters)} filterable columns.")
+    return {"plz_column_needed": False, "filters": filters, "plz_column": plz_column_name}
+
+
 @app.post("/api/heatmap")
 async def get_heatmap_data(request: FilterRequest):
     global df_storage, plz_column_name, plz_geocoord_df