Run2 file text extraction

Robust File Text Extraction Skill

Description

When classifying a large number of documents (PDFs, PPTXs, DOCXs), extracting a sample of text (e.g., the first few pages) is sufficient and highly performant. This skill handles text extraction robustly, catching errors to avoid failing the entire batch.

Prerequisites

Install required Python packages:

pip install PyPDF2 python-docx python-pptx

Python Implementation

import os
from PyPDF2 import PdfReader
import docx
from pptx import Presentation

def extract_text_for_classification(file_path, pdf_pages=3):
    """
    Extracts text from a file based on its extension.
    Returns lowercase text to simplify keyword matching.
    """
    ext = file_path.lower().split('.')[-1]
    text = ""
    
    try:
        if ext == "pdf":
            reader = PdfReader(file_path)
            for i in range(min(pdf_pages, len(reader.pages))):
                page_text = reader.pages[i].extract_text()
                if page_text:
                    text += page_text + " "
        
        elif ext == "docx":
            doc = docx.Document(file_path)
            for para in doc.paragraphs:
                text += para.text + " "
                
        elif ext == "pptx":
            prs = Presentation(file_path)
            for slide in prs.slides:
                for shape in slide.shapes:
                    if hasattr(shape, "text"):
                        text += shape.text + " "
        else:
            print(f"Warning: Unsupported file type '{ext}' for file {file_path}")
            
    except Exception as e:
        print(f"Error reading {file_path}: {e}")
        
    return text.lower()