Now with working validation and correction feedback

backend/app/routers/spreadsheet.py

@@ -5,11 +5,13 @@ from app.services.spreadsheet_service import SampleSpreadsheetImporter, Spreadsh
 from fastapi.responses import FileResponse
 import os
 from pydantic import ValidationError  # Import ValidationError here
-
+from app.row_storage import row_storage  # Import the RowStorage instance
 
 router = APIRouter()
 logger = logging.getLogger(__name__)
 
+importer = SampleSpreadsheetImporter()  # assuming this is a singleton or manageable instance
+
 
 @router.get("/download-template", response_class=FileResponse)
 async def download_template():
@@ -36,7 +38,6 @@ async def upload_file(file: UploadFile = File(...)):
             raise HTTPException(status_code=400, detail="Invalid file format. Please upload an .xlsx file.")
 
         # Initialize the importer and process the spreadsheet
-        importer = SampleSpreadsheetImporter()
         validated_model, errors, raw_data, headers = importer.import_spreadsheet_with_errors(file)
 
         # Extract unique values for dewars, pucks, and samples
@@ -58,6 +59,11 @@ async def upload_file(file: UploadFile = File(...)):
             headers=headers  # Include headers in the response
         )
 
+        # Store row data for future use
+        for idx, row in enumerate(validated_model):
+            row_num = idx + 4  # Adjust row numbering if necessary
+            row_storage.set_row(row_num, row.dict())
+
         logger.info(f"Returning response with {len(validated_model)} records and {len(errors)} errors.")
         return response_data
 
@@ -72,23 +78,24 @@ async def upload_file(file: UploadFile = File(...)):
 
 @router.post("/validate-cell")
 async def validate_cell(data: dict):
-    """Validate a single cell value based on expected column type."""
     row_num = data.get("row")
     col_name = data.get("column")
     value = data.get("value")
 
-    importer = SampleSpreadsheetImporter()
+    # Get the full data for the row
+    current_row_data = row_storage.get_row(row_num)
 
-    # Ensure we've cleaned the value before validation
+    # Update the cell value
-    expected_type = importer.get_expected_type(col_name)
+    current_row_data[col_name] = importer._clean_value(value, importer.get_expected_type(col_name))
-    cleaned_value = importer._clean_value(value, expected_type)
 
-    logger.info(f"Validating cell: row {row_num}, column {col_name}, value {cleaned_value}")
+    # Temporarily store the updated row data
+    row_storage.set_row(row_num, current_row_data)
+
+    logger.info(f"Validating cell: row {row_num}, column {col_name}, value {value}")
 
     try:
-        # Construct a dictionary with the expected format for validation
+        # Ensure we're using the full row data context for validation
-        validation_data = {col_name: cleaned_value}
+        validated_row = SpreadsheetModel(**current_row_data)
-        SpreadsheetModel(**validation_data)
         logger.info(f"Validation succeeded for row {row_num}, column {col_name}")
         return {"is_valid": True, "message": ""}
     except ValidationError as e:

backend/app/row_storage.py

@@ -0,0 +1,12 @@
+class RowStorage:
+    def __init__(self):
+        self.data = {}
+
+    def get_row(self, row_num):
+        return self.data.get(row_num, {})
+
+    def set_row(self, row_num, row_data):
+        self.data[row_num] = row_data
+
+
+row_storage = RowStorage()  # Singleton instance for storing row data