How to extract text from PDF using Python?

Portable Document Format (PDF) files are widely used for electronic document sharing, and extracting text from them can be challenging due to complex formatting. Python offers several libraries, such as PyPDF2, PyMuPDF, ReportLab, and PDFMiner, to facilitate efficient PDF text extraction. PyPDF2 allows for basic operations like splitting and merging PDF pages, while PyMuPDF, known for handling complex documents, can access metadata and extract text and images. Setting up a Python development environment with necessary installations like Python, pip, and these libraries is crucial for text extraction tasks. Advanced techniques, including Optical Character Recognition (OCR), pre-processing, layout analysis, and machine learning tools, enhance extraction accuracy, especially for intricate layouts. These methods address text extraction challenges by preserving formatting and improving data accuracy, with tools like Nanonets using AI for precise extraction. Memory optimization techniques in Python are essential when working with large datasets to prevent memory overflows during the extraction process.

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