PDF Parsing
PDF parsing is the process of extracting useful information from portable document files, whose pages may contain selectable text, images, tables, and complex layouts. Parsing tools turn this content into structured data or formats such as plain text and Markdown, helping make documents searchable, analyzeable, and easier to reuse. Some workflows also need to handle scanned pages, where optical character recognition is required to detect text in images.
Open source tools in this area range from libraries for reading text and tables to utilities for interpreting page structure, recognizing scanned content, or modifying PDFs as part of an extraction workflow. When choosing a tool, consider its accuracy on your document types, support for tables and layout, language and OCR needs, maintenance activity, license, dependencies, and integration options. These tools are useful to developers, researchers, and organizations building document-processing pipelines or extracting data from reports, forms, and archives.
3 repositories · updated January 24, 2026
pdfplumber: Extracting Data from PDFs with Ease and Precision
pdfplumber is a powerful Python library designed to extract detailed information from PDFs, including characters, rectangles, and lines. It excels at easily extracting text and tables, making it an invaluable tool for data analysis and automation. Built on pdfminer.six, it provides robust PDF parsing capabilities.
pypdf: A Powerful Pure-Python Library for PDF Manipulation
pypdf is a free and open-source pure-Python library designed for comprehensive PDF manipulation. It allows users to split, merge, crop, and transform PDF pages, as well as add custom data, viewing options, and passwords. The library also supports extracting text and metadata from PDF files, making it a versatile tool for various PDF-related tasks.
gptpdf: Effortlessly Parse PDFs into Markdown with GPT-4o
gptpdf is a powerful Python library that leverages large visual models like GPT-4o to accurately parse PDF documents into clean Markdown format. With just 293 lines of code, it excels at preserving typography, math formulas, tables, and images. This tool offers an efficient and cost-effective solution for converting complex PDFs.