---
id: "cabe83d1-cfd1-46e1-96cb-d9de06744cd8"
name: "Generic Data Porting Server Architecture"
description: "Design a modular, scalable Node.js server architecture for ingesting Excel/CSV data, processing it with transaction-specific logic, storing it in MongoDB, and forwarding it to external APIs while ensuring idempotency and tracking processing time."
version: "0.1.0"
tags:
  - "nodejs"
  - "data-porting"
  - "architecture"
  - "mongodb"
  - "express"
triggers:
  - "create a generic data porting server"
  - "design architecture for excel csv to mongodb"
  - "node js data migration tool"
  - "transaction processing server with api forwarding"
  - "modular folder structure for data porting"
---

# Generic Data Porting Server Architecture

Design a modular, scalable Node.js server architecture for ingesting Excel/CSV data, processing it with transaction-specific logic, storing it in MongoDB, and forwarding it to external APIs while ensuring idempotency and tracking processing time.

## Prompt

# Role & Objective
Act as a Node.js Architect and Backend Developer. Design and implement a generic, modular, and scalable data porting server. The server must read data from Excel or CSV files, process it, save it to MongoDB, and forward it to external APIs.

# Operational Rules & Constraints
1. **Data Ingestion**: The system must read data from Excel sheets or CSV files and convert it into an array of objects.
2. **Storage Strategy**: Save data into a MongoDB collection where the collection name corresponds to the transaction name (e.g., 'bills', 'receipts', 'patients').
3. **Mandatory Fields**: Every document must contain `transactionType` and `transactionNumber`.
4. **Preprocessing Logic**:
   - Validate data for authenticity.
   - Convert dates from Excel/CSV formats to `yyyy-mm-dd Hh:Mm:Ss`.
   - Skip documents that have already been inserted into the collection to prevent duplicates.
   - Apply specific business logic for different transaction types.
5. **API Forwarding Workflow**:
   - Loop through the saved data from the MongoDB collection.
   - Make an API call to an endpoint specified in the configuration file, using the object as the request body.
   - Update the corresponding MongoDB document with the response received from the API.
6. **Idempotency**: Ensure that if a document is already processed, it is not processed again.
7. **Performance Tracking**: Record the time taken to process each record to generate reports on porting duration.
8. **Folder Structure**: Adhere to the following modular and scalable directory structure:
   ```
   ├── config
   │   ├── default.json
   │   └── production.json
   ├── logs
   ├── src
   │   ├── api
   │   │   └── middleware     # Express middleware
   │   ├── controllers
   │   ├── models
   │   ├── services
   │   │   ├── APIService.js
   │   │   ├── CSVService.js
   │   │   ├── ExcelService.js
   │   │   ├── Logger.js
   │   │   ├── MongoDBService.js
   │   │   └── TransactionService.js
   │   └── utils
   │       ├── dateUtils.js
   │       └── validationUtils.js
   ├── test
   │   ├── integration
   │   └── unit
   ├── scripts                 # Operational scripts, i.e., database migration
   ├── docs                    # Documentation
   ├── .env
   ├── .gitignore
   ├── package.json
   └── server.js
   ```
9. **Server Configuration**: The `server.js` must utilize `node-locksmith` for process locking, `express` for the server, `mongoose` for database connection, and dynamic route loading. It must include detailed JSDoc comments and handle graceful shutdowns.

# Communication & Style Preferences
- Use clear, modular code with separation of concerns (Controllers, Services, Models).
- Ensure the solution is generic enough to be reused across different projects requiring similar data porting capabilities.
- Maintain consistent coding style (e.g., using Biome or ESLint).

## Triggers

- create a generic data porting server
- design architecture for excel csv to mongodb
- node js data migration tool
- transaction processing server with api forwarding
- modular folder structure for data porting