📊 AFAS file connector for key management system

Connecting AFAS Software to a Key Management System for seamless access control

I developed a connector for AFAS Software, a leading Dutch ERP system, to integrate with a key management system developed by Traka. The connector, built in Python, uses the AFAS Get Connector API to enable seamless synchronization of data between the two systems. This integration allows the client (a large Dutch company with over 1,000 employees) to manage employee access rights using AFAS software, which is primarily used for employee management and other business processes.

Key Features

🔗 AFAS Integration – The connector synchronizes data between the AFAS ERP system and the key management system, streamlining the management of employee access rights.

💻 Python & REST API – Built using Python, the connector communicates with AFAS via its Get Connector API, a REST API designed to retrieve data from AFAS.

📈 Data Transformation – The retrieved data, delivered as JSON, is converted into a CSV format for easier integration with the key management system.

🔑 Secure API Communication – The API uses a token-based authentication to ensure secure communication between the connector and AFAS. Technical Details

The connector relies on the requests library to interact with the AFAS API. The process involves generating a token to authenticate the connection, retrieving the necessary data, and converting it into a CSV file for use by the key management system. For more details, the AFAS Get Connector API is thoroughly documented on the AFAS website.

This solution significantly simplifies the process of managing employee access and enhances operational efficiency for the client.

Challenges & Learnings

🔐 Authentication & Token Management – Managing the token-based authentication for the AFAS API required careful attention to security and token expiration. Ensuring that tokens were securely stored and refreshed was crucial for seamless integration.

⚙️ API Limitations & Constraints – The AFAS API, while powerful, has some limitations in terms of data retrieval and processing. Understanding these constraints early on helped avoid unnecessary complexity during development.

💡 Optimizing Performance – As the connector handled a large amount of data, I had to optimize its performance to ensure quick synchronization without overloading the system. Efficient error handling and logging were essential to identify and address any issues in real-time.

This project provided valuable experience in API integration, data transformation, and system performance optimization, while overcoming the challenges of working with external systems and ensuring smooth communication between different platforms.

💡 Interested in learning more? Feel free to contact me!