Structured Text Processing Utilities

This repository contains two Python scripts for extracting structured information from .txt files in a given folder and exporting the results to a CSV spreadsheet. They are designed to process text-based datasets with consistent formatting, automatically identify matching elements, and organize them into an easily analyzable format.

Features

• Batch processing of all text files in a selected folder.
• Flexible tag/code matching using regular expressions.
• Customizable list-based validation for which data entries to include.
• Clean CSV output that can be opened in Excel, Google Sheets, or any spreadsheet tool.

Scripts

• script1.py – Reads input files, validates entries against predefined lists, and outputs structured rows of matched data.
• script2.py – Extracts code–number pairings from text files using multiple matching patterns, then compiles results into a CSV.

Requirements

• Python 3.8+
• No external dependencies (only built-in Python modules are used).

Usage

1. Place your .txt files and the required list files in the same directory as the scripts.
2. Run the desired script:

   python script1.py

   or

   python script2.py <folder_path>

3. Follow the on-screen prompts to select the folder and specify the output file name.

Folder structure (example)

.
├── script1.py
├── script2.py
├── list_a.txt
├── list_b.txt
└── README.md

Redaction note

Variable names, certain file names, and a few comments have been slightly generalized/redacted to avoid exposing project-specific terminology. This is a cosmetic change only — it does not affect the scripts’ functionality for similarly structured datasets.

License

MIT License — feel free to adapt and reuse for your own projects.