pdfplumber
Plumb a PDF for detailed information about each char, rectangle, and line.
Decision gist · record as of 2026-08-14
Yes. pdfplumber is actively maintained, has no known vulnerabilities, installs with low friction, and carries a permissive MIT license. It is well-suited for extracting data from machine-generated PDFs when you need programmatic access to individual objects rather than OCR. Not recommended for scanned image-based PDFs.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Works best on machine-generated PDFs rather than scanned images; requires Python 3.8 or later.
- Low friction install with three well-maintained runtime dependencies.
- Active maintenance with recent releases and strong community engagement (10659 stars).
License · maintenance · safety
permissive license (permissive) — MIT license permits commercial and private use with minimal restrictions.
last release 2026-06-15 (60 days) · last repo commit 2026-08-06 · 10,659 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 62,830,652 downloads/mo, #495 on PyPI
Alternatives
Verify before relying
pip install pdfplumber
import pdfplumber
with pdfplumber.open("path/to/file.pdf") as pdf:
first_page = pdf.pages[0]
print(first_page.chars[0])- Performance characteristics on large PDFs (memory usage, extraction speed)
- Accuracy of table extraction across different PDF layouts and formats
- Handling of complex or non-standard PDF structures
What it is and what it does
pdfplumber is a Python library for extracting structured data from machine-generated PDFs. It provides detailed access to individual text characters, geometric shapes (rectangles, lines, curves), images, and annotations within a PDF, built on top of pdfminer.six. The library is designed for programmatic PDF analysis rather than OCR of scanned documents.
The package offers both a Python API and command-line interface for accessing PDF objects. It supports table extraction, form value retrieval, and visual debugging capabilities. You can crop pages to regions of interest, filter objects by custom criteria, and export data in CSV, JSON, or plain-text formats. It handles password-protected PDFs and supports Unicode normalization.
Use it for
- Extract structured data from invoices, receipts, or financial reports for automation workflows.
- Build table extraction pipelines to convert PDF tables into CSV or database records.
- Analyze PDF layout and positioning to identify form fields or specific content regions.
- Debug PDF structure visually to understand object placement before writing extraction logic.
- Batch process machine-generated PDFs to collect metadata or validate document structure.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
pdfplumber is actively maintained, has no known vulnerabilities, installs with low friction, and carries a permissive MIT license. It is well-suited for extracting data from machine-generated PDFs when you need programmatic access to individual objects rather than OCR. Not recommended for scanned image-based PDFs.
Install
pdfplumber on PyPI
Before you install
Low friction install with three well-maintained runtime dependencies. Active maintenance with recent releases and strong community engagement (10659 stars).
Works best on machine-generated PDFs rather than scanned images; requires Python 3.8 or later.
License in practice
MIT license permits commercial and private use with minimal restrictions.
Quickstart
pip install pdfplumber
import pdfplumber
with pdfplumber.open("path/to/file.pdf") as pdf:
first_page = pdf.pages[0]
print(first_page.chars[0])Verify before relying
- Performance characteristics on large PDFs (memory usage, extraction speed)
- Accuracy of table extraction across different PDF layouts and formats
- Handling of complex or non-standard PDF structures
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.8 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagespdfminer.sixPillowpypdfium2 |
| Maintenance | Actively maintained 60 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 62,830,652 / month, #495 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Intended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14 |
Evidence: pdfplumber-0.11.10-py3-none-any.whl
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See also pdfminer.six · unPDF · pdftext · camelot-py · pdfminer · docling-ibm-models · playa-pdf · marker-pdf · pdftotext · pymupdf