---
id: opendataloader-pdf
version: "2.5.0"
license: Apache-2.0
license_treatment: permissive
maintenance: active
---

# opendataloader-pdf — A Python wrapper for the opendataloader-pdf Java CLI.

License: permissive · Maintenance: active · Downloads: 184.2K/mo

## What it is and what it does

OpenDataLoader PDF is a Python wrapper around a Java-based PDF parser that extracts text, tables, images, and structural metadata from PDFs into multiple formats (Markdown, JSON with bounding boxes, HTML). It offers two modes: a deterministic local mode for standard digital PDFs, and a hybrid mode that routes complex pages (nested tables, scanned documents, formulas, charts) to an AI backend. The package also includes auto-tagging functionality to convert untagged PDFs into Tagged PDF format, which is the foundation for PDF accessibility compliance.

The tool is designed for two main workflows: building AI-ready datasets for RAG and LLM pipelines (with structured output and source citations via bounding boxes), and automating PDF accessibility remediation at scale. It requires Java 11+ as a system dependency but has no Python runtime dependencies, making installation straightforward. The core extraction and auto-tagging features are open-source under Apache-2.0; PDF/UA export and visual editing tools are enterprise add-ons.

Use it for:

- Extract structured Markdown and JSON from PDFs for RAG pipelines, with bounding boxes for source citation and retrieval.
- Auto-tag untagged PDFs into screen-reader-ready Tagged PDF format to meet accessibility regulations (EAA, ADA, Section 508) at scale.
- Parse complex or scanned PDFs (tables, formulas, charts, poor-quality scans) using hybrid mode for accurate structured output.
- Build document processing workflows that preserve reading order, heading hierarchy, and list structure for downstream NLP tasks.
- Extract tables and images with precise coordinates for document layout reconstruction or visual document analysis.

## Worth the install?

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

Extracts structured data (Markdown, JSON, HTML) from PDFs with bounding boxes and semantic tagging, and auto-tags untagged PDFs into Tagged PDF format for accessibility compliance.

Yes. Active, well-maintained project with strong benchmark performance (0.907 overall accuracy, 0.928 table extraction), no security vulnerabilities, and low install friction. Apache-2.0 license covers core features. Java 11+ system dependency is the only real prerequisite. Suitable for production RAG pipelines and accessibility automation workflows; hybrid mode adds cost (API calls) but handles complex documents well.

## Install

pip install opendataloader-pdf
uv add opendataloader-pdf
poetry add opendataloader-pdf

## Installing opendataloader-pdf

Before you install: Low friction: pure Python wheel with no runtime dependencies. Active maintenance (last commit 2026-08-13, 28406 stars) and recent releases. Requires Java 11+ as a system prerequisite, not a Python dependency.

License in practice: Apache-2.0 permissive license. Core extraction and auto-tagging are free and open-source; PDF/UA export and accessibility studio are enterprise add-ons.

Quickstart:

pip install opendataloader-pdf

import opendataloader_pdf

opendataloader_pdf.convert(
    input_path=["file.pdf"],
    output_dir="output/",
    format="markdown,json"
)

Requires Java 11+ installed and available on PATH before running Python code.

Verify before relying:

- Whether the hybrid mode (AI-assisted extraction for complex tables and scanned PDFs) requires external API calls or runs locally.
- Performance characteristics and resource usage when processing large batches or high-volume PDF collections.
- Whether OCR in hybrid mode supports all 80+ claimed languages equally or has language-specific accuracy variations.

## Package facts

- License: Apache-2.0 (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 184.2K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

pdf to markdown json extraction, pdf data extraction for rag, pdf accessibility auto-tagging, pdf parser with bounding boxes, pdf to structured data, tagged pdf generation, pdf layout analysis, pdf-extraction, rag-pipeline, accessibility

[View on SkillFed](https://skillfed.io/packages/opendataloader-pdf) · [View on PyPI](https://pypi.org/project/opendataloader-pdf/)