pdfminer.six

PDF parser and analyzer

pdfminer-six Permissive license MIT Active ★ 7,017 v20260107 released 2026-01-07

Install

pdfminer-six on PyPI

pip

pip install pdfminer-six

uv

uv add pdfminer-six

poetry

poetry add pdfminer-six

Package facts

License	MIT (permissive)
Python support	supports the current Python release (>=3.10)
Install friction	low — pure-Python wheel
Runtime dependencies	2 — charset-normalizer, cryptography
Maintenance	actively maintained — 218 days since the last release
Last repo commit	2026-03-13
First released	2014-09-19
Popularity	one of the top 1,000 most-downloaded packages on PyPI (30-day window, as of 2026-08-13)
Known vulnerabilities	none known (OSV.dev, checked 2026-08-13)

Evidence: pdfminer_six-20260107-py3-none-any.whl

Keywords: layout analysis, pdf converter, pdf parser, text mining

Development Status :: 5 - Production/StableEnvironment :: ConsoleIntended Audience :: DevelopersIntended Audience :: Science/ResearchProgramming Language :: PythonProgramming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Text Processing

About pdfminer.six

from the package's own PyPI description — quoted content, verbatim

pdfminer.six

Continuous integration (image) PyPI version (image) gitter (image)

We fathom PDF

Pdfminer.six is a community maintained fork of the original PDFMiner. It is a tool for extracting information from PDF documents. It focuses on getting and analyzing text data. Pdfminer.six extracts the text from a page directly from the sourcecode of the PDF. It can also be used to get the exact location, font or color of the text.

It is built in a modular way such that each component of pdfminer.six can be replaced easily. You can implement your own interpreter or rendering device that uses the power of pdfminer.six for other purposes than text analysis.

Check out the full documentation on Read the Docs.

Features

Written entirely in Python.
Parse, analyze, and...

Read as markdown · JSON record · Source repository · Homepage

AI interpretation — verify before relying

AI-generated interpretation of the package facts above; every digit, version, license, or vulnerability id it cites is grounded in the facts already shown on this page

Extracts and analyzes text, images, and metadata from PDF documents using pure Python, supporting encryption, CJK languages, and various compression formats.

Low friction install with just two runtime dependencies (charset-normalizer, cryptography). Active maintenance with recent releases and 7017 GitHub stars; last commit 2026-03-13 indicates ongoing development.

MIT license permits commercial and private use with minimal restrictions, requiring only attribution and inclusion of the license text.

Usage

pip install pdfminer.six

from pdfminer.high_level import extract_text
text = extract_text("example.pdf")
print(text)

Requires Python 3.10 or newer.

Verdict: Production-stable PDF extraction library with active maintenance, permissive MIT licensing, and low install friction. Well-suited for text and metadata extraction workflows; no known vulnerabilities as of 2026-08-13.