mForm Bulk Upload Backend

A FastAPI backend for parsing and storing Excel form data in MongoDB.

Prerequisites

Python 3.8+
MongoDB (local or cloud instance)
pip

Installation

Install dependencies:

pip install -r requirements.txt

Set up MongoDB:
- Install MongoDB locally or use MongoDB Atlas
- Create a database named mform_bulk_upload

Environment Configuration: Create a .env file in the backend directory:

MONGODB_URL=mongodb://localhost:27017
DATABASE_NAME=mform_bulk_upload

Running the Application

python main.py

The API will be available at http://localhost:8000

API Endpoints

File Validation

POST /api/validate - Validate Excel file structure
- Returns detailed validation information including sheet status, metadata, and counts

File Upload

POST /api/upload - Parse and store Excel file in MongoDB
- Saves form metadata, questions, and answer options to separate collections

Forms Management

GET /api/forms - Get all forms from database
GET /api/forms/{form_id} - Get specific form with questions and options
DELETE /api/forms/{form_id} - Delete form and all related data

Database Schema

Forms Collection

{
  "_id": "ObjectId",
  "title": "string",
  "language": "string",
  "version": "string",
  "created_at": "ISO timestamp"
}

Questions Collection

{
  "_id": "ObjectId",
  "form_id": "string",
  "order": "number",
  "title": "string",
  "view_sequence": "number",
  "input_type": "number",
  "created_at": "ISO timestamp"
}

Options Collection

{
  "_id": "ObjectId",
  "form_id": "string",
  "order": "number",
  "option_id": "number",
  "label": "string",
  "created_at": "ISO timestamp"
}

Excel File Structure

The application expects Excel files with three sheets:

Forms - Form metadata
- Columns: Language, Title
Questions Info - Question definitions
- Columns: Order, Title, View Sequence, Input Type
Answer Options - Answer choices for questions
- Columns: Order, Id, Label

Features

Excel file validation with detailed feedback
MongoDB integration for data persistence
RESTful API endpoints
Error handling and logging
CORS support for frontend integration

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