: A modern version of FPDF that supports Unicode. You must embed a Khmer Unicode font (like Khmer OS Battambang ) for the script to appear.
According to reports, set_text_shaping(True) may still have bugs for specific methods like text() versus cell() and write() . Therefore, reportlab remains the more battle-tested choice for Khmer.
Khemara-Krub: A Python Toolkit for Cryptographic Verification and Text Extraction of High Unicode Khmer PDFs python khmer pdf verified
import pdfplumber def extract_khmer_text(pdf_path): with pdfplumber.open(pdf_path) as pdf: for page_num, page in enumerate(pdf.pages, 1): text = page.extract_text() print(f"--- Page page_num ---") print(text) # usage # extract_khmer_text("your_khmer_file.pdf") Use code with caution. Method B: Scanned PDF Extraction (Using Tesseract OCR)
Alternative: fpdf2 supports TTF embedding similarly. : A modern version of FPDF that supports Unicode
Processing Khmer text in PDFs with Python is a specialized task due to the complex script, unique font rendering (like Khmer Unicode subscripts), and the lack of standard word spacing in the Khmer language. To achieve —meaning text that is accurately rendered or extracted without breaking the script's visual logic—developers must use specific libraries and configurations. 1. Generating Verified Khmer PDFs with fpdf2
Khmer is a complex script. Unlike Latin characters, Khmer characters do not just sit side-by-side. They stack vertically, use dependent vowels, and rely on specific rendering engines (like HarfBuzz) to display correctly. Processing Khmer text in PDFs with Python is
import PyPDF2
Before diving into the coding ecosystem, it is important to understand why PDFs are notoriously difficult for scripts like Khmer.
If you want, I can produce a ready-to-run end-to-end script that generates a Khmer PDF, verifies font embedding, extracts text, and reports pass/fail.