Project Finder

A full-stack web application for collecting, storing and presenting consultant assignment listings from multiple external sources. The project was developed during my internship at Rejlers as a way to centralize assignment data and make it easier to search, filter and review relevant consultant opportunities.

Overview

The application consists of a Spring Boot backend, a Vue frontend and a PostgreSQL database, all running together through Docker Compose.

The backend fetches assignment data from several sources using a combination of REST APIs, GraphQL endpoints, sitemap parsing and HTML parsing. The collected data is normalized and stored in a PostgreSQL database, then displayed in a searchable frontend interface.

Features

• Scrapes assignment listings from multiple external sources

• Supports different scraping strategies:

  • REST API integration
  • GraphQL requests
  • Sitemap parsing
  • HTML parsing with Jsoup

• Stores normalized assignment data in PostgreSQL

• Frontend interface for browsing and filtering assignments

• Keyword-based filtering

• JWT-based authentication

• Admin-only scraper trigger

• Docker Compose setup for frontend, backend and database

Tech Stack

Backend

• Java
• Spring Boot
• Spring Security
• Spring Data JPA
• PostgreSQL
• Jsoup
• Jackson
• JWT authentication
• Maven

Frontend

• Vue 3
• Vite
• Tailwind CSS
• Axios

DevOps

• Docker
• Docker Compose
• Nginx

Architecture

Frontend (Vue + Nginx)
        |
        v
Backend (Spring Boot REST API)
        |
        v
PostgreSQL Database
        ^
        |
External assignment sources

Getting Started

Prerequisites

Make sure you have the following installed:

• Docker
• Docker Compose

Run the application

Clone the repository:

git clone <repository-url>
cd <repository-folder>

Start the application:

docker compose up --build

The application will start three services:

• Frontend
• Backend
• PostgreSQL database

Access the application

Frontend:

http://localhost:5173

Backend API:

http://localhost:6767

Authentication

The application includes a simple JWT-based authentication system for demonstration purposes. To keep the project easy to run locally without additional configuration, it uses a simplified JWT authentication setup with predefined users and does not implement production-grade security practices.

Two predefined users are available for local testing:

• User
• Admin

The administrator account has permission to manually trigger scraper executions through the application.

Project Structure

.
├── backend/        # Spring Boot application
├── frontend/       # Vue application
├── docker-compose.yml
└── README.md

Scraping Sources

The application was built to handle several types of external data sources, including:

• JSON-based public APIs
• GraphQL endpoints
• Static HTML pages
• Sitemap-based page discovery
• JavaScript-hydrated pages where relevant data could be extracted from embedded page data

Each scraper maps external assignment data into a common internal project model.

What I Learned

This project gave me practical experience with:

• Building a full-stack application from scratch
• Designing a backend API with Spring Boot
• Working with PostgreSQL and JPA
• Containerizing a full-stack application with Docker Compose
• Handling inconsistent external data sources
• Implementing different scraping strategies depending on the structure of each website
• Structuring a frontend with Vue and reusable components
• Authentication and role-based access control with JWT

Notes

This project was developed as an internship project and is intended as a portfolio project. Some external sources may change their structure over time, which can affect scraper behavior.

Future Improvements

Possible improvements include:

• More advanced error handling and retry logic
• Improved logging and monitoring
• More detailed project filtering
• Unit and integration tests
• CI/CD pipeline
• Deployment to a cloud environment