📅 2024-09-17 — Session: Enhanced Schema Extraction and PDF Processing

🕒 00:00–01:20
🏷️ Labels: Python, Schema Extraction, Pdf Processing, Debugging, Data Quality
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to enhance Python functions for schema extraction and PDF metadata processing, ensuring robust handling of nested structures and accurate data extraction.

Key Activities

  1. Fixing Traversal Logic in extract_parameters Function: Modified the function to preserve nested keys, ensuring full structure retention for relevant keys.
  2. Preserving Nested Structures: Updated the traverse function to maintain the entire nested structure during schema extraction, especially for keys like convenios.
  3. Simplified Schema Extraction: Developed a Python function to extract top-level properties while retaining nested structures without recursion.
  4. Debugging TypeError: Resolved a TypeError in dictionary handling, ensuring correct assignment of dictionary structures.
  5. Fixing JSON Output in Pandas: Addressed JSON formatting issues in pandas.DataFrame.to_json(), ensuring valid JSON array outputs.
  6. PDF Metadata Extraction: Explored methods for extracting metadata and non-selectable content from PDFs using PyMuPDF and Tesseract OCR.
  7. Installation Guide: Provided installation instructions for PyMuPDF and Tesseract OCR, resolving common import errors.

Achievements

  • Successfully refactored Python functions for schema extraction, preserving nested structures.
  • Improved JSON output formatting in Pandas.
  • Implemented robust PDF metadata extraction techniques.

Pending Tasks

  • Further testing of the updated functions in diverse scenarios.
  • Integration of PDF processing techniques into existing workflows.