Python PDF Libraries in ChatGPT

Python PDF Libraries in ChatGPT

Introduction to PDF libraries:

Welcome to the fascinating realm of PDF manipulation using Python! As a versatile file format, PDF (Portable Document Format) has become an integral part of document sharing and storage for individuals and businesses worldwide. Whether you're dealing with reports, invoices, research papers, or e-books, PDFs offer consistency in appearance across different platforms and devices.

Here we will be going through all the PDF python libraries currently included in the new ChatGPT coding enviroment.

FPDF (Version 1.7.2): Creating Dynamic PDFs with Ease:

Among the myriad of Python PDF libraries available, FPDF holds a special place as a user-friendly and efficient tool for generating PDF documents from scratch. The library provides an intuitive, high-level interface for creating PDFs, making it a popular choice for developers and content creators alike.

Here I instructed ChatGPT to: Create a professional PDF with a bar graph, include in the header.

FPDF (Version 1.7.2): Creating Dynamic PDFs with Ease:

Generating High-Quality Fake Data with the Faker Library:

When developing and testing applications or conducting data analysis, we often require sample data that mimics real-world data. While manually creating this data is an option, it can be a time-consuming and error-prone task. Thankfully, there's a Python library called Faker that can generate high-quality fake data for us!

Here I use Fakedata to populate a PDF document.

Generating High-Quality Fake Data with the Faker Library:

Converting PDFs to Images with the pdf2image Library:

pdf2image is a handy Python library that allows us to convert PDF files into images, with support for popular image formats such as PNG, JPEG, and more. The library offers flexibility in choosing which pages to convert, image resolution, and output format. This allows PDF files to be converted to any image format, this is how I'm using ChatGPT to make the PNG images for this blog.

Extracting Data Using the PDFMiner/PyMuPDF Libraries:

PDFMiner is an open-source Python library that specializes in extracting text, images, and metadata from PDF files. It's a popular choice for text mining and document analysis due to its ability to precisely locate text on a page and provide additional details, such as font types and lines.

However, users should be aware of a challenge known as data hallucination, which occurs when the tool generates information not present in the original document. For instance, in the case of reading a CV with PDFMiner, it might extract accurate lines but also include inaccuracies, such as claiming proficiency in a language that wasn't mentioned (I don't speak Italian nor Java).

While PDFMiner excels at analyzing text data, it's essential to cross-verify the results to ensure accuracy and avoid hallucinated data. The same test was repeated with similar results using PyMuPDF library.

Extracting Data Using the PDFMiner/PyMuPDF Libraries:

Merging PDFs using PyPDF2:

PyPDF2 is a widely-used Python library for working with PDF files. While it's a powerful tool for extracting metadata and manipulating pages, my text extraction tests once again resulted in hallucinations, although seemingly less than the previous libraries this may have been by chance.

Despite this, PyPDF2 excels in merging multiple PDF files into a single document. The PdfFileMerger class allows users to seamlessly append PDF files, creating a consolidated output. Whether you're combining chapters of an e-book or merging scanned documents, PyPDF2 makes the process simple and efficient. With just a few lines of code, you can unlock the full potential of PyPDF2 for all your PDF merging needs.

The coding enviroment allows you to upload a .zip file up to 100MB and prompt "Merge all these files into one file using PyPDF2. Be ready to fight a little bit to get a perfect output. Instructing ChatGPT to "Use the PdfFileMerger class" helped it produce a good document.


There we have it, the included libraries for PDF manipulation are:

• PyPDF2 - Useful for merging PDFs.
• fpdf - Useful for generating PDFs from any data format.
• pdf2image - Useful for turning PDFs into images.
• PyMuPDF - Was able to use for resizing with mixed results.
• pdfkit - Unusable in current state, meant to extract HTML data into PDFs.
• pdfminer.six - Currently produces Hallucinations.

Thanks for reading, Did I miss anything? Let me know!