PDFs are a ubiquitous part of our digital lives, but extracting meaningful text from them is challenging due to their object-based structure, which makes it difficult to distinguish between individual characters and their placement on the page. However, Python provides several libraries that can help with PDF processing tasks such as reading, extracting text and metadata, creating, merging, and splitting PDFs. The PyPDF2 library is useful for basic operations like adding custom data, viewing options, and passwords to PDF files, while pdfminer.six excels at text extraction. Additionally, the ReportLab library allows for the creation of new PDFs from scratch with various elements like text, images, and graphics. Other libraries such as PyMuPDF offer advanced features including image extraction and table detection. When choosing a library, consider the specific requirements of your project and handle exceptions and edge cases, especially when dealing with large or complex PDF files.