Skip to main content

High-performance Microsoft Office document extraction to Markdown

Project description

undoc

High-performance Microsoft Office document extraction to Markdown.

Installation

pip install undoc

Usage

Basic Usage

from undoc import parse_file

# Parse a document
doc = parse_file("document.docx")

# Convert to Markdown
markdown = doc.to_markdown()
print(markdown)

# Convert to plain text
text = doc.to_text()

# Convert to JSON
json_data = doc.to_json()

With Context Manager

from undoc import parse_file

with parse_file("document.xlsx") as doc:
    print(doc.to_markdown(frontmatter=True))
    print(f"Sections: {doc.section_count}")
    print(f"Resources: {doc.resource_count}")

Parse from Bytes

from undoc import parse_bytes

with open("document.pptx", "rb") as f:
    data = f.read()

doc = parse_bytes(data)
markdown = doc.to_markdown()

Extract Resources (Images)

from undoc import parse_file

doc = parse_file("document.docx")

# Get all resource IDs
resource_ids = doc.get_resource_ids()

for rid in resource_ids:
    # Get resource metadata
    info = doc.get_resource_info(rid)
    print(f"Resource: {info['filename']} ({info['mime_type']})")

    # Get resource binary data
    data = doc.get_resource_data(rid)

    # Save to file
    with open(info['filename'], 'wb') as f:
        f.write(data)

Document Metadata

from undoc import parse_file

doc = parse_file("document.docx")

print(f"Title: {doc.title}")
print(f"Author: {doc.author}")
print(f"Sections: {doc.section_count}")
print(f"Resources: {doc.resource_count}")

Supported Formats

  • DOCX - Microsoft Word documents
  • XLSX - Microsoft Excel spreadsheets
  • PPTX - Microsoft PowerPoint presentations

Features

  • RAG-Ready Output: Structured Markdown optimized for RAG/LLM applications
  • High Performance: Native Rust implementation via FFI
  • Asset Extraction: Images and embedded resources
  • Metadata Preservation: Document properties, styles, formatting
  • Cross-Platform: Windows, Linux, macOS (Intel & ARM)

API Reference

Functions

  • parse_file(path) - Parse document from file path
  • parse_bytes(data) - Parse document from bytes
  • version() - Get library version

Undoc Class

Conversion Methods

  • to_markdown(frontmatter=False, escape_special=False, paragraph_spacing=False) - Convert to Markdown
  • to_text() - Convert to plain text
  • to_json(compact=False) - Convert to JSON
  • plain_text() - Get plain text (fast extraction)

Properties

  • title - Document title
  • author - Document author
  • section_count - Number of sections
  • resource_count - Number of resources

Resource Methods

  • get_resource_ids() - List of resource IDs
  • get_resource_info(id) - Resource metadata
  • get_resource_data(id) - Resource binary data

License

MIT License - see LICENSE for details.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

undoc-0.1.20-py3-none-any.whl (4.0 MB view details)

Uploaded Python 3

File details

Details for the file undoc-0.1.20-py3-none-any.whl.

File metadata

  • Download URL: undoc-0.1.20-py3-none-any.whl
  • Upload date:
  • Size: 4.0 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for undoc-0.1.20-py3-none-any.whl
Algorithm Hash digest
SHA256 c3df3fb7632dc918df3fa39de3179528e144d185db9323a4e70498be66db3912
MD5 e8ae35b114228d83d4fd452ec17ec2d7
BLAKE2b-256 9e195389dc5ebf3b53dbfb33c181aaf7906bab47fedb656f22f531c21f0544a1

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page