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Python utilities to simplify document files management

Project description

polytext

polytext

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Doc Utils

A Python package for document conversion and text extraction.

Features

  • Convert various document formats (DOCX, ODT, PPT, etc.) to PDF
  • Extract text from PDF, Markdown, IMAGE, and audio files
  • Support for both local files and S3/GCS cloud storage
  • Multiple PDF parsing backends (PyPDF, PyMuPDF)
  • Transcribe audio & video files (local or cloud) to text/markdown
  • Extract YouTube video transcripts
  • Extract text from URLs

Installation

# Library only – assumes system requirements are already present
pip install polytext

Heads-up: Polytext’s PDF generator relies on [WeasyPrint] under the hood.
The PyPI wheel contains only Python code; you still need WeasyPrint’s native libraries (Pango, Cairo, GDK-PixBuf, HarfBuzz, Fontconfig) installed at the OS level.

System requirements

Requirement Notes macOS (Homebrew) Ubuntu / Debian
Python Supported on 3.11 – 3.13
WeasyPrint still requires its native libraries
brew install python@3.11 sudo apt install python3.11
WeasyPrint – native stack installs Pango, Cairo, etc. brew install weasyprint sudo apt install weasyprint
LibreOffice used for Office → PDF conversion brew install --cask libreoffice sudo apt install libreoffice

Usage

Converting Documents to PDF

from polytext import convert_to_pdf, ConversionError

try:
    # Convert a document to PDF
    pdf_path = convert_to_pdf('input.docx', 'output.pdf')
    print(f"PDF saved to: {pdf_path}")
except ConversionError as e:
    print(f"Conversion failed: {e}")

Features that require the API key for Google Gemini are:

  • audio
  • video
  • image
  • youtube
from polytext.loader.base import BaseLoader

llm_api_key = "your_google_gemini_api_key"  # Set your Google Gemini API key here

# Instantiate the loader 
loader = BaseLoader(llm_api_key=llm_api_key)

Text or Markdown Extraction

from polytext.loader.base import BaseLoader

markdown_output = False # Change if you want to extract text as markdown
source = "local" # Change to "cloud" if you want to extract from cloud storage (s3 or GCS)

# Instantiate the loader (optionally set markdown_output, llm_api_key, etc.)
loader = BaseLoader(markdown_output=markdown_output, source=source)

# Extract text from a local file
result = loader.get_text(input_list=["/path/to/document.docx"])
print(result["text"])
# Extract text from cloud file
result = loader.get_text(input_list=["s3://your-bucket/path/to/document.docx"])
print(result["text"])

# Extract text from a markdown file (local)
result = loader.get_text(input_list=["/path/to/document.md"])
print(result["text"])
# Extract text from cloud file
result = loader.get_text(input_list=["s3://your-bucket/path/to/document.md"])
print(result["text"])

# Extract text from an audio file (local)
result = loader.get_text(input_list=["/path/to/audio.mp3"])
print(result["text"])
# Extract text from cloud file
result = loader.get_text(input_list=["s3://your-bucket/path/to/audio.mp3"])
print(result["text"])

# Extract text from a video file (local)
result = loader.get_text(input_list=["/path/to/video.mp4"])
print(result["text"])
# Extract text from cloud file
result = loader.get_text(input_list=["s3://your-bucket/path/to/video.mp4"])
print(result["text"])

# Extract text from Image (local)
result = loader.get_text(input_list=["/path/to/image.jpg"])
print(result["text"])
# Extract text from cloud file
result = loader.get_text(input_list=["s3://your-bucket/path/to/image.jpg"])
print(result["text"])

# Extract transcript from a YouTube video
result = loader.get_text(input_list=["https://www.youtube.com/watch?v=xxxx"])
print(result["text"])

# Extract text from a URL
result = loader.get_text(input_list=["https://www.domain-name.com/path"])
print(result["text"])

License

MIT Licence

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