aaredb/backend/app/routers/spreadsheet.py

98 lines
4.1 KiB
Python

from app.sample_models import SpreadsheetModel, SpreadsheetResponse
from fastapi import APIRouter, UploadFile, File, HTTPException
import logging
from app.services.spreadsheet_service import SampleSpreadsheetImporter, SpreadsheetImportError
from fastapi.responses import FileResponse
import os
from pydantic import ValidationError # Import ValidationError here
router = APIRouter()
logger = logging.getLogger(__name__)
@router.get("/download-template", response_class=FileResponse)
async def download_template():
"""Serve a template file for spreadsheet upload."""
current_dir = os.path.dirname(__file__)
template_path = os.path.join(current_dir, "../../downloads/V7_TELLSamplesSpreadsheetTemplate.xlsx")
if not os.path.exists(template_path):
raise HTTPException(status_code=404, detail="Template file not found.")
return FileResponse(template_path, filename="template.xlsx",
media_type="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet")
@router.post("/upload", response_model=SpreadsheetResponse)
async def upload_file(file: UploadFile = File(...)):
"""Process the uploaded spreadsheet and return validation results."""
try:
logger.info(f"Received file: {file.filename}")
# Validate file format
if not file.filename.endswith('.xlsx'):
logger.error("Invalid file format")
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
dewars = {sample.dewarname for sample in validated_model if sample.dewarname}
pucks = {sample.puckname for sample in validated_model if sample.puckname}
samples = {sample.crystalname for sample in validated_model if sample.crystalname}
# Construct the response model with the processed data
response_data = SpreadsheetResponse(
data=validated_model,
errors=errors,
raw_data=raw_data,
dewars_count=len(dewars),
dewars=list(dewars),
pucks_count=len(pucks),
pucks=list(pucks),
samples_count=len(samples),
samples=list(samples),
headers=headers # Include headers in the response
)
logger.info(f"Returning response with {len(validated_model)} records and {len(errors)} errors.")
return response_data
except SpreadsheetImportError as e:
logger.error(f"Spreadsheet import error: {str(e)}")
raise HTTPException(status_code=400, detail=f"Error processing spreadsheet: {str(e)}")
except Exception as e:
logger.error(f"Unexpected error occurred: {str(e)}")
raise HTTPException(status_code=500, detail=f"Failed to upload file. Please try again. Error: {str(e)}")
@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()
# Ensure we've cleaned the value before validation
expected_type = 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}")
try:
# Construct a dictionary with the expected format for validation
validation_data = {col_name: cleaned_value}
SpreadsheetModel(**validation_data)
logger.info(f"Validation succeeded for row {row_num}, column {col_name}")
return {"is_valid": True, "message": ""}
except ValidationError as e:
# Extract the first error message
message = e.errors()[0]['msg']
logger.error(f"Validation failed for row {row_num}, column {col_name}: {message}")
return {"is_valid": False, "message": message}