To ensure optimal results when working with Khmer PDFs in Python:
from fpdf import FPDF # 1. Initialize PDF pdf = FPDF() pdf.add_page() # 2. Register your Khmer font (crucial: use a .ttf file) # Replace 'fonts/Battambang-Regular.ttf' with your actual path pdf.add_font("KhmerFont", style="", fname="Battambang-Regular.ttf") pdf.set_font("KhmerFont", size=16) # 3. Enable the shaping engine for Khmer clusters # This ensures characters like '្' or 'ុ' render correctly pdf.set_text_shaping(True) # 4. Write Khmer text khmer_text = "សួស្តីពិភពលោក (Hello World)" pdf.cell(w=0, h=10, text=khmer_text, align='C', new_x="LMARGIN", new_y="NEXT") # 5. Output PDF pdf.output("khmer_verified.pdf") Use code with caution. Copied to clipboard Common Issues & Fixes
import khmereasytools as kh_tools
: The PDF uses a custom font encoding matrix ( ToUnicode mapping is missing or broken).
with pdfplumber.open("khmer_document.pdf") as pdf: for page in pdf.pages: khmer_text = page.extract_text() if khmer_text: print("Extracted Khmer Text:") print(khmer_text) python khmer pdf verified
from pdf2image import convert_from_path import pytesseract def ocr_khmer_pdf(pdf_path): # Convert PDF pages into images pages = convert_from_path(pdf_path, dpi=300) for page_num, page_img in enumerate(pages): # Perform OCR using the Khmer language model # '--oem 3' uses the default LSTM engine for complex scripts custom_config = r'--oem 3 -l khm' text = pytesseract.image_to_string(page_img, config=custom_config) print(f"--- OCR Page page_num + 1 ---") print(text) ocr_khmer_pdf("scanned_khmer_document.pdf") Use code with caution. Troubleshooting Common Errors 1. Square Boxes (Missing Glyphs)
Stop struggling with broken Khmer characters in your PDF exports! After testing various libraries, here is the "verified" stack for handling Khmer script reliably: To ensure optimal results when working with Khmer
: The "industry standard" for creating complex PDFs. To support Khmer, you must embed a Unicode-compliant Khmer font (like Hanuman or Khum) using pdfmetrics .
: Studies on Khmer news classification have successfully used Python-based neural networks with word embeddings to categorize thousands of Khmer articles with high accuracy. 2. Generating Khmer PDFs with Python Enable the shaping engine for Khmer clusters #
For example, the Aspose.PDF Cloud SDK allows you to validate a signature with just a few lines of Python code. The process involves creating a PdfApi instance, uploading the signed PDF, and then calling a method to verify the signature. Similarly, the certysign-sdk provides a Python wrapper for its trust services, enabling you to sign and verify documents.
Note: ReportLab may still struggle with complex sub-consonant stacking in older versions. If character splitting occurs, revert to the WeasyPrint HTML-to-PDF pipeline. Part 2: Verified Khmer PDF Text Extraction