Project Description: OpenELIS Global aims to streamline test management by integrating Open Concept Lab (OCL) data into its laboratory information system. This project focuses on importing OCL concepts from ZIP files containing JSON/CSV data and mapping them to OpenELIS Test entities. I’m developing the OclZipImporter to parse ZIP files and the OclToOpenElisMapper to transform OCL concepts (e.g., mnemonic, name, is active) into Test fields (e.g., localCode, description, isActive). The project includes validation, duplicate handling, and integration with existing services to populate the TEST table, enhancing lab workflows in low-resource settings.
Recently, GSoC 2025 results were announced, and I’m thrilled and grateful to my mentors and the OpenELIS Global organization for selecting me as a contributor. This is an exciting opportunity to contribute to global health through open-source software.
I’ve created this talk thread to share regular updates on my progress, post milestones, and ask questions if I encounter challenges during development or testing.
Mentors: @caseyi and other maintainers
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Week 2 Update (June 8 – June 22)
Progress:
OCL Initializer
The OCL (Open Concept Lab) initializer module has been successfully developed and is now fully functional. This lays the groundwork for initializing and configuring OCL instances within our system.
Mapper Component
The initial version of the mapper has been implemented. It currently supports core transformation logic required for converting external data formats into our internal representation. This serves as a critical link between the data ingestion layer and our internal processing pipeline.
Importer Integration Testing
The scope of the integration tests for the importer module has been broadened to cover a wider range of use cases. This includes additional validation scenarios and edge conditions, contributing to improved system stability and confidence in future releases.
Next Steps / To-Dos:
Enhance Mapper Logic
Extend the mapper to handle edge cases more effectively, ensuring it can gracefully process less predictable or malformed input data. This includes adding fallbacks and improved error handling.
Improve Test Reliability and Persistence
Strengthen the persistence and reliability of integration and unit tests, with a focus on ensuring consistent results across different environments and test runs. This involves refining test setup/teardown routines and handling asynchronous behavior more robustly.
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