# pdfplumber vs PyMuPDF vs pypdf: Python PDF text extraction compared

> The three main Python libraries for extracting text from PDFs, compared honestly: speed, table handling, licensing, and when calling an API beats installing any of them.

Published: 2026-07-14 · Source: https://marklipi.com/blog/pdfplumber-vs-pymupdf-vs-pypdf


For extracting text from PDFs in Python, the choice is usually between three libraries: **pypdf** (pure Python, simplest), **PyMuPDF** (fastest, richest features, AGPL-licensed), and **pdfplumber** (best table introspection, built on pdfminer). All three read the text layer only — none of them does OCR — and each earns its place depending on what you're extracting and where the code runs.

## The three at a glance

| | pypdf | PyMuPDF (fitz) | pdfplumber |
| --- | --- | --- | --- |
| Implementation | Pure Python | C (MuPDF) bindings | Pure Python (pdfminer.six) |
| Speed | Moderate | Fastest by a wide margin | Slowest |
| Table extraction | No | Basic (`find_tables`) | Best-in-class (`extract_tables`) |
| Markdown output | No | Via `pymupdf4llm` add-on | No |
| Layout/geometry access | Limited | Full | Full, very ergonomic |
| License | BSD | AGPL-3.0 (or paid commercial) | MIT |
| Install weight | Light | Binary wheel | Light |

## When to pick each

**Pick pypdf** for simple jobs in constrained environments: page counts, merging/splitting, plain text where layout doesn't matter. Pure Python means it runs anywhere, and BSD licensing raises no questions.

**Pick PyMuPDF** when speed matters or you want Markdown: it's routinely an order of magnitude faster than the pure-Python options, and the `pymupdf4llm` companion package outputs LLM-ready Markdown with headings and tables. The catch is licensing — AGPL-3.0 obliges you to open-source network-served code that uses it, unless you buy a commercial license. Many companies discover this after shipping.

**Pick pdfplumber** when tables are the job: its `extract_tables()` with tunable strategies (ruling lines vs whitespace alignment) plus visual debugging (`page.to_image().debug_tablefinder()`) is the best table tooling in Python. MIT-licensed. Accept that it's the slowest of the three.

## The code, side by side

```python
# pypdf — plain text
from pypdf import PdfReader
text = "\n".join(p.extract_text() or "" for p in PdfReader("doc.pdf").pages)

# PyMuPDF — Markdown via pymupdf4llm
import pymupdf4llm
md = pymupdf4llm.to_markdown("doc.pdf")

# pdfplumber — tables
import pdfplumber
with pdfplumber.open("doc.pdf") as pdf:
    tables = [t for page in pdf.pages for t in page.extract_tables()]
```

## The fourth option: don't install anything

If what you need is *clean Markdown out of a text-layer PDF*, the library route means owning a dependency, its upgrades, and (for PyMuPDF) a licensing question — to reimplement what one HTTP call does:

```python
import requests

with open("doc.pdf", "rb") as f:
    md = requests.post(
        "https://api.marklipi.com/convert", files={"file": f}, timeout=60
    ).json()["markdown"]
```

No API key, free tier of 100 conversions/day, deterministic output, nothing stored. Libraries win when files can't leave your machine or you need cell-level geometry; the API wins on zero setup and no license text to read. ([Where each tool on the wider market fits.](/best-pdf-to-markdown-tools))

## FAQ

### Which Python PDF library is fastest?

PyMuPDF, and it isn't close — its MuPDF C core typically processes pages an order of magnitude faster than pypdf or pdfplumber on the same corpus.

### Which extracts tables best?

pdfplumber, thanks to configurable detection strategies and visual debugging. PyMuPDF's `find_tables` is serviceable; pypdf doesn't do tables.

### None of these work on my scanned PDF. Why?

All three read the embedded text layer, and a scan doesn't have one. You need OCR (e.g., Tesseract, Marker, Docling) for scans — [here's how to tell which you're dealing with](/blog/pdf-text-layer-vs-ocr).

### Is PyMuPDF free for commercial use?

It's AGPL-3.0: free if you comply with AGPL's obligations (including for network services), otherwise Artifex sells commercial licenses. Evaluate with your counsel — many teams choose pdfplumber (MIT) or an API to sidestep the question.