📅 2024-12-22 — Session: Enhanced PDF Text and Transaction Parsing
🕒 23:15–23:55
🏷️ Labels: Pdf Parsing, Regex, OCR, Data Extraction, Python
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to improve the parsing of financial statements, focusing on extracting text from PDFs and refining transaction parsing logic using regex.
Key Activities
- Developed strategies for parsing financial statements using regex, targeting regular and installment transactions.
- Debugged PDF parsing issues, addressing regex misalignment, and explored OCR for text extraction.
- Implemented text extraction techniques using PyPDF2, pdfminer, and pdfplumber, focusing on maintaining layout and line breaks.
- Updated regex patterns for transaction parsing, ensuring accurate data extraction and handling of installment transactions.
- Resolved directory path errors in scripts and converted Spanish month abbreviations to datetime in Pandas.
Achievements
- Successfully extracted text from PDFs using OCR and refined regex patterns for transaction parsing.
- Improved PDF text extraction scripts to handle layout and line breaks effectively.
- Enhanced transaction parsing logic to accurately capture transaction details, including dates and installments.
Pending Tasks
- Further refine regex patterns to handle edge cases in transaction parsing.
- Explore additional PDF extraction libraries or tools for improved accuracy.