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Community maintained fork of pdfminer

Home Page: https://pdfminersix.readthedocs.io

License: MIT License

Makefile 0.32% Python 99.68%

pdfminer.six's Introduction

pdfminer.six

Build Status PyPI version gitter

Pdfminer.six is a community maintained fork of the original PDFMiner. It is a tool for extracting information from PDF documents. It focuses on getting and analyzing text data. Pdfminer.six extracts the text from a page directly from the sourcecode of the PDF. It can also be used to get the exact location, font or color of the text.

It is build in a modular way such that each component of pdfminer.six can be replaced easily. You can implement your own interpreter or rendering device to use the power of pdfminer.six for other purposes that text analysis.

Check out the full documentation on Read the Docs.

Features

  • Written entirely in Python.
  • Parse, analyze, and convert PDF documents.
  • PDF-1.7 specification support. (well, almost).
  • CJK languages and vertical writing scripts support.
  • Various font types (Type1, TrueType, Type3, and CID) support.
  • Support for extracting images (JPG, JBIG2 and Bitmaps).
  • Support for RC4 and AES encryption.
  • Table of contents extraction.
  • Tagged contents extraction.
  • Automatic layout analysis.

How to use

  • Install Python 3.4 or newer

  • Install

    pip install pdfminer.six

  • Use command-line interface to extract text from pdf:

    python pdf2txt.py samples/simple1.pdf

Contributing

Be sure to read the contribution guidelines.

pdfminer.six's People

Contributors

euske avatar pietermarsman avatar tataganesh avatar goulu avatar cybjit avatar fakabbir avatar cathalgarvey avatar timb07 avatar jstockwin avatar pudo avatar mduggan avatar igormp avatar pquentin avatar vstoykov avatar sergei-maertens avatar orangain avatar sschuberth avatar mawoqiw avatar 0xabu avatar begnini avatar oculushut avatar jcushman avatar bittner avatar mpasternak avatar hason avatar yosida95 avatar kaushikacharya avatar jordanreiter avatar hughsw avatar daniel-km avatar

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