![]() ![]() Unlike other PDF-related tools, it focuses entirely on getting and analyzing text data. PDFMiner is a tool for extracting information from PDF documents. In this section, we will discover the Top Python PDF Library: Actually, PDF processing is a little difficult but we can leverage the below API for making it easier. PDFs are a good source of data, most organizations release their data in PDFs only.Īs AI is growing, we need more data for prediction and classification hence, ignoring PDFs as data sources for you could be a blunder. 2- Python Libraries for PDF ProcessingĪs a Data Scientist, You may not stick to data format. Unless they are proving an explicit interface for this, we have to convert pdf to text first. One more thing you can never process a pdf directly in existing frameworks of Machine Learning or Natural Language Processing. Most of the Text Analytics Library or frameworks are designed in Python only. 1- Why Python for PDF processingĪs you know PDF processing comes under text analytics. PDFs contain useful information, links and buttons, form fields, audio, video, and business logic. PDF is one of the most important and widely used digital media. Popular Python libraries are well integrated and provide the solution to handle unstructured data sources like Pdf and could be used to make it more sensible and useful. Photo by James Harrison on Unsplash Introductionīeing a high-level, interpreted language with a relatively easy syntax, Python is perfect even for those who don’t have prior programming experience.
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