π 2023-12-28 β Session: Enhanced Text Extraction and Processing Functions
π 18:50β20:20
π·οΈ Labels: Python, Text Processing, Web Scraping, Legal Documents, Function Improvement
π Project: Dev
β Priority: MEDIUM
Session Goal
The primary goal of this session was to enhance and correct functions related to text extraction and processing from HTML and legal documents using Python.
Key Activities
- Correction in HTML Text Construction: Addressed issues in constructing text from HTML elements to ensure accurate text collection and concatenation.
- Improved Text Extraction Function: Modified
extraer_articulos_titulos_capitulos
to better handle articles, titles, and chapters, including conditions and exceptions. - Function Adaptation for Grouping: Adapted the
agrupar_articulos
function to work with list outputs, introducingagrupar_elementos
for grouping elements up to 2500 words. - Function Review and Adjustment: Reviewed and adjusted the
extraer_articulos_titulos_capitulos
function for efficient detection and counting of document elements. - Text Processing Adjustment: Enhanced the function to correctly process text following colons, ensuring proper accumulation before detecting new elements.
- Legal Article Extraction Modification: Improved detection of legal articles, ensuring citations arenβt misinterpreted as new articles unless consecutive.
- Verification Logic Integration: Incorporated logic to verify citations in article lines, preventing misclassification as new articles.
- Citation Handling Improvement: Proposed solutions for managing citations within text extraction, maintaining article flow and continuity.
Achievements
- Successfully improved and corrected multiple Python functions for text extraction and processing.
- Enhanced the accuracy and efficiency of document element detection and grouping.
Pending Tasks
- Further testing and validation of the modified functions in diverse document scenarios.
- Potential integration of these functions into larger systems or workflows.