---
id: pdftotext
version: "4.0.0"
license: MIT
license_treatment: permissive
maintenance: active
---

# pdftotext — Simple PDF text extraction

License: permissive · Maintenance: active · Downloads: 169.7K/mo

## What it is and what it does

pdftotext is a Python wrapper around the Poppler C++ library that extracts text content from PDF files. It provides a simple interface: load a PDF file (optionally with a password), then iterate over pages or join all text into a single string. The package handles the low-level Poppler integration so you don't have to.

The main trade-off is installation complexity. Because it wraps a C++ library, you must have Poppler development headers and a C++ compiler on your system before installing via pip. Once those are in place, the API is straightforward—just open a file, create a PDF object, and read pages as strings.

Use it for:

- Index PDF documents for full-text search by extracting all text and storing it in a search engine.
- Batch convert PDF content to plain text for processing or analysis pipelines.
- Read text from password-protected PDFs programmatically in automated workflows.
- Extract page-by-page text for document summarization or NLP tasks.
- Build a document ingestion layer that accepts PDFs and outputs structured text data.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Extracts text from PDF files, including password-protected documents, and exposes pages as iterable strings or a joined text block.

Yes, if you can meet the system dependency requirement. The package is actively maintained, has no known vulnerabilities, uses a permissive license, and solves a common problem with a clean API. The high install friction (C++ compilation) is a real barrier on some systems but not insurmountable—install the platform-specific Poppler headers first, then pip install. Worth the effort for production PDF text extraction.

## Install

pip install pdftotext
uv add pdftotext
poetry add pdftotext

## Installing pdftotext

Before you install: High install friction: requires system-level compilation and platform-specific C++ libraries (libpoppler-cpp-dev on Debian/Ubuntu, poppler-cpp-devel on Fedora/RHEL, or poppler via Homebrew on macOS). Package is actively maintained as of 49 days ago.

License in practice: MIT license is permissive and imposes no restrictions on commercial or private use, modification, or redistribution.

Quickstart:

pip install pdftotext

import pdftotext

with open("document.pdf", "rb") as f:
    pdf = pdftotext.PDF(f)
    for page in pdf:
        print(page)

Requires libpoppler-cpp development headers and C++ compiler installed on your system before pip install will succeed.

Verify before relying:

- Whether password-protected PDF support works reliably across all PDF encryption standards.
- Performance characteristics when processing large PDFs or batch operations.
- Accuracy of text extraction from PDFs with complex layouts, images, or non-Latin scripts.

## Package facts

- License: MIT (permissive)
- Python support: unspecified
- Install friction: high
- Maintenance: active
- Downloads: 169.7K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

pdf text extraction, extract text from pdf, pdf to text python, read pdf content, pdf parsing library, simple pdf reader, pdf document text, pdf-extraction, document-processing

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