If you are a data scientist, you know the importance of PDFs. They are everywhere, from digital receipts to online tax documents. But dealing with them can be a pain. Not only are they often password-protected, but extracting data from them is also a challenge.
That’s where Python comes in. Python is a programming language with many libraries that make it an advantageous tool for PDF creation and manipulation. In this blog, we will talk about five of the best Python PDF libraries according to online reviews.
PDFMiner is a text extraction tool for PDF documents that allows you to obtain the exact location of text as well as other layout information (fonts, etc.). It also performs automatic layout analysis and can convert PDF into other formats (HTML/XML). It provides a PDF parser that can be used for other purposes as well.
Additionally, it can extract an outline (TOC) and tagged contents. It supports various font types (Type1, TrueType, Type3, and CID) as well as CJK languages and vertical writing scripts.
PyPDF4 opens up a limitless world of new features to PDFs with its ability to read metadata and encryption information as well as split, merge together, crop, and transform the pages inside pdf files. This puts PyPDF4 in an elite class of python PDF libraries.
One way you can use it is by adding custom data along with viewing options so that your PDF files are more secure. You can also use this library to merge multiple PDFs together into a single document.
pdflib is a Python package and tool that allow to read and write PDF documents.
Operation features subsetting, merging, rotating, modifying metadata, etc. The fastest pure Python PDF parser available with excellent performance while running against large complex (OCR scanned) PDF documents.
The library can be used either standalone or in conjunction with reportlab to reuse existing PDFs in new ones. Permissively licensed.
It supports these Python versions: 2.6, 2.7, 3.3, 3.4, 3.5, and 3.6.
Slate is a library that makes it easy to extract text from PDF files. It depends on the PDFMiner package, which also aims to help with extracting text from various other sorts of documents and images.
Within this library, there is one class, called PDF. As you might’ve guessed by its name, this will extract all text from a PDF document and present it to you as a string of text.
This can be useful in a number of ways, such as helping with data entry by automatically extracting text from PDFs that contain structured information. Additionally, since Slate works with images as well as PDFs, you could also use it to help create OCR (optical character recognition) models.
Python has a host of libraries for working with PDFs, pikepdf is one of the best. It’s based on QPDF, a powerful library that enables you to manipulate and repair PDFs.
If you’re comfortable with the PDF specification, Pikepdf will let you do just about anything you want with your PDFs. You can edit and transform existing PDFs.