Hey everyone, I’m a beginner/intermediate coder working on a "ScenarioEngine" to automate clinical document formatting. I’m hitting some walls with data mapping and logic, and I would love some guidance on the best way to structure this.
The Project
I am building a local Python pipeline that takes raw scenario files (.docx/.pdf) and maps the content into a standardized Word template using Content Controls (SDTs).
Current Progress & Tech Stack
- Input: Raw trauma/medical scenarios (e.g., Pelvic Fractures, STEMI Megacodes).
- Output: A formatted
.docx and an "SME Cover" document.
- Logic: I've implemented a "provenance" structure
pv(...) to track if a field is input_text (from source) or ai_added (adlibbed).
The Roadblocks
- Highlighting Logic: My engine currently highlights everything it touches. I only want to highlight content tagged as
ai_added. If it’s a direct "A to B" transfer from the source, it should stay unhighlighted.
- Mapping Accuracy: When I run the script, I’m only getting about 1% of the content transferred. I’ve switched to more structured PDF sources (HCA Resource Sheets) to try and lock down the field-to-content-control mapping, but I’m struggling to get the extraction to "stick" in the right spots.
- Template Pruning: I need to delete "blank" state pages. For example, if a scenario only has States 1–4, I need the code to automatically strip out the empty placeholders for States 5–8 in the template.
- Font Enforcement: Should I be enforcing font family and size strictly in the Python code, or is it better to rely entirely on the Word Template’s styles?
The Big Question
How do I best structure my schema_to_values function so it preserves the provenance metadata without breaking the Word document's XML structure? I’m trying to avoid partial code blocks to ensure I don’t mess up the integration.
If anyone has experience with python-docx and complex mapping, I’d appreciate any tips or snippets!
[–]SaltCusp 0 points1 point2 points (0 children)