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In this tutorial, we explore PDF usage in Python, highlighting its significance in digital media for presenting and exchanging documents. PDFs can contain diverse content such as information, links, buttons, form fields, audio, video, and business logic. Python is favored for PDF processing due to its text analytics capabilities, with most libraries designed for this purpose. Extracting useful information from PDFs facilitates the use of that data in machine learning and natural language processing applications. Key Python libraries for handling PDF files include PDFMiner, a tool for extracting data from PDF documents, and PyPDF2, among others.