skillfed

pdfminer

PDF parser and analyzer

pdfminer v20191125 229.5K downloads/30d#9,131 on PyPI5,275
Permissive license MIT Abandoned released

What it is and what it does

PDFMiner is a pure Python PDF parser and text extraction tool that reads PDF documents and extracts rendered text along with precise layout metadata—font names, sizes, positions, and writing direction. It performs automatic layout analysis to reconstruct document structure and can output results as plain text, HTML, XML, or tagged content. It handles encrypted PDFs (RC4 and AES), multiple font types (Type1, TrueType, Type3, CID), and CJK languages with vertical writing support.

The package provides both a programmatic API for integration into Python applications and command-line tools (pdf2txt.py for extraction, dumppdf.py for debugging). However, it is no longer maintained—the repository was archived in 2022 with the last commit in December of that year, and no updates have been released since November 2019. While it remains functional for basic PDF text extraction tasks, it receives no security updates or bug fixes.

Use it for:

  • Extract text and position data from PDF documents for document processing or data mining workflows
  • Convert PDFs to HTML or XML for downstream analysis or republishing
  • Debug PDF structure and internal content using dumppdf.py for troubleshooting
  • Parse encrypted PDFs with password protection to access restricted content
  • Analyze document layout and reconstruct reading order from complex multi-column or figure-heavy PDFs

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Extracts text and layout information from PDF documents, including font details, positions, and structure, with support for encrypted PDFs and multiple output formats.

No—not recommended for new projects. The package is abandoned (last release 2019-11-25, repository archived 2022), receives no maintenance or security updates, and has high install friction due to source-only distribution. Use pdfminer.six instead, which is actively maintained and provides the same core functionality with ongoing support.

Install

pdfminer on PyPI

pip

pip install pdfminer

uv

uv add pdfminer

poetry

poetry add pdfminer

Installing pdfminer

Before you install

High install friction due to source-only distribution (pdfminer-20191125.tar.gz). The project is archived and abandoned as of 2022-12-07, with no maintenance since version 20191125 released 2019-11-25. Consider pdfminer.six if ongoing support is needed.

License in practice

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

Quickstart

pip install pdfminer
python -m pdfminer.six samples/simple1.pdf
# or via command line:
pdf2txt.py samples/simple1.pdf

Requires Python 3.6 or above; Python 2 is not supported. Source distribution requires build tools to compile.

Verify before relying

  • Whether the archived repository still accepts security patches or community contributions
  • Current compatibility with modern PDF specifications beyond PDF-1.7
  • Performance characteristics on large or complex PDF files

Package facts

License MIT (permissive)
Python support supports the current Python release (>=3.6)
Install friction high — source build required
Runtime dependencies none
Maintenance abandoned — 2,454 days since the last release
Last repo commit (repository archived)
First released
Downloads 229,484/month — #9,131 on PyPI (30-day window, as of 2026-08-14)
Known vulnerabilities none known (OSV.dev, checked 2026-08-14)

Evidence: pdfminer-20191125.tar.gz

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

Development Status :: 4 - BetaEnvironment :: ConsoleIntended Audience :: DevelopersIntended Audience :: Science/ResearchLicense :: OSI Approved :: MIT LicenseTopic :: Text Processing

Tags

pdf text extractionpdf parser pythonextract text from pdfpdf layout analysispdf to text converterpdf content analysispdf document parsing
pdf-parsingabandoned

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