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pdfplumber

Project10.8K

Inspect machine-generated PDFs and extract text, tables, and page-level objects with Python or the command line.

Added 2026-10-07
Replaces
GitHub

What you can build

  • Extract text and table data from machine-generated invoices, then route uncertain rows to a human review step.
  • Store extracted text alongside page numbers and PDF metadata so staff can search and trace report content.
  • Inspect character positions, fonts, and page objects to investigate why a particular PDF extracts incorrectly.
  • Use the documented form-value extraction workflow to prepare fields from PDFs for a follow-up review.
  • Create a batch utility that exports selected PDF object types and page ranges to CSV or JSON for analysis.

Try this prompt

Build a small Python workflow that reads machine-generated PDF files from a configured input folder, extracts page text and tables with pdfplumber, and writes results plus source filenames and page numbers to a separate output folder. Keep the original PDFs unchanged. Add clear error reporting for files that cannot be parsed and a reviewable record of extracted results. Keep the implementation limited to documented pdfplumber capabilities; do not add OCR or external services.

Get started

  1. Check the runtime

    Use a Python environment; the README lists Python 3.10 through 3.14 as tested versions.

  2. Install and choose an interface

    Follow the README’s Installation section to install pdfplumber. Use its Python library to open a PDF, or its command-line interface to export text or object data.

  3. Explore extraction and debugging

    Use the README sections on Extracting text, Extracting tables, and Visual debugging to choose an extraction approach for your PDFs.

License & notes

MITMIT-licensed; retain the copyright and license notice when distributing. The library requires Python and uses local compute and storage you provide; no model or paid API is required by the documented core workflow. Hosting costs depend on your application.

  • Works best with machine-generated PDFs; scanned documents may need a separate OCR step. Extraction quality can vary with document layout.
  • This is a parsing library and CLI, not a hosted document-processing service or a complete workflow for storing, reviewing, and approving extracted records.

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