📅 2023-12-28 — Session: Developed Python Algorithms for Legal Text Extraction
🕒 05:30–06:35
🏷️ Labels: Python, Text Processing, Legal Articles, Algorithm Development
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to develop and refine Python algorithms for extracting and processing legal articles from text documents.
Key Activities
- Algorithm Development: Created and enhanced Python algorithms to parse and extract legal articles, focusing on handling context variations and numerical sequencing using regular expressions.
- Word Count Implementation: Developed a function to count words in legal articles, ensuring the text is fully accessible.
- Article Grouping: Implemented an algorithm to group articles into sections of up to 2500 words, modifying extraction and word count functions accordingly.
- Distinguishing Articles from Citations: Developed strategies to differentiate between articles and citations in legal documents using sequence analysis and context evaluation.
- Troubleshooting: Addressed text truncation issues and network connection errors, providing insights and solutions for
NewConnectionErrorandMaxRetryError. - Code Updates: Made several updates to handle article numbering and missing articles, ensuring continuous extraction beyond article 177.
Achievements
- Successfully developed robust algorithms for extracting, grouping, and analyzing legal articles in Python.
- Enhanced error handling and troubleshooting for network and extraction issues.
Pending Tasks
- Further optimize algorithms for edge cases in article extraction and grouping.
- Implement automated testing for the developed functions to ensure reliability.