Build a PDF Document Classification Script Using Python

We are looking for a Python developer to build a standalone script that automatically categorizes PDF documents into predefined categories. The script will extract text from each PDF, process the content, and output a structured result showing the category for each file. This is a small, self-contained task focused on clean, working code. Job Responsibilities: 1. Develop a Python script that reads PDF files from a folder. 2. Extract text from each PDF using a Python library (e.g., `PyPDF2` or `pdfplumber`). 3. Implement text preprocessing such as cleaning, tokenization, and stop-word removal. 4. Apply rule-based logic or a lightweight ML model to classify PDFs into predefined categories. 5. Generate an output file (CSV or JSON) containing: - PDF file name - Assigned category - Optional confidence score 6. Handle encrypted, empty, or unreadable PDFs gracefully and provide meaningful error messages. Requirements: - Strong Python experience - Familiarity with PDF text extraction libraries (`PyPDF2`, `pdfplumber`, or similar) - Experience with text processing / NLP (Pandas, NLTK, or similar) - Ability to implement clear, maintainable logic Deliverables: - Standalone Python script (`.py`) - Sample input PDFs and output file demonstrating the classification - Short instructions on how to run the script Notes: This task is focused on quickly producing a working, reliable script that can classify PDF documents according to predefined rules or categories.