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