{"categories":[{"label":"Text Processing","url":"https://skillfed.io/packages/category/text-processing/3"}],"enrichment":{"capability":"Extracts text from PDF files, including password-protected documents, and exposes pages as iterable strings or a joined text block.","skillfed_tags":["pdf-extraction","document-processing"],"use_cases":["Index PDF documents for full-text search by extracting all text and storing it in a search engine.","Batch convert PDF content to plain text for processing or analysis pipelines.","Read text from password-protected PDFs programmatically in automated workflows.","Extract page-by-page text for document summarization or NLP tasks.","Build a document ingestion layer that accepts PDFs and outputs structured text data."],"what_it_does":"pdftotext is a Python wrapper around the Poppler C++ library that extracts text content from PDF files. It provides a simple interface: load a PDF file (optionally with a password), then iterate over pages or join all text into a single string. The package handles the low-level Poppler integration so you don't have to.\n\nThe main trade-off is installation complexity. Because it wraps a C++ library, you must have Poppler development headers and a C++ compiler on your system before installing via pip. Once those are in place, the API is straightforward\u2014just open a file, create a PDF object, and read pages as strings.","worth_installing":"Yes, if you can meet the system dependency requirement. The package is actively maintained, has no known vulnerabilities, uses a permissive license, and solves a common problem with a clean API. The high install friction (C++ compilation) is a real barrier on some systems but not insurmountable\u2014install the platform-specific Poppler headers first, then pip install. Worth the effort for production PDF text extraction."},"id":"pdftotext","links":{"html":"https://skillfed.io/packages/pdftotext","md":"https://skillfed.io/packages/pdftotext.md","pypi":"https://pypi.org/project/pdftotext/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-06-26","license_spdx":"MIT","license_treatment":"permissive","name":"pdftotext","python_support":"unspecified","summary":"Simple PDF text extraction"},"popularity":{"monthly_downloads":169686,"position":10409,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"4.0.0"}